Ibero-Latin American Congress on Computational Methods in Engineering (CILAMCE)

N-M interaction curves for timber members cross-section under ambient and high temperature

2024-12-16T13:48:33+00:00

Widely used for structural calculation, axial force (N) - bending moment (M) interaction curves are suitable instruments for evaluating the structural elements cross-section capacity, relating the ultimate values of bending moment and axial force. Also known as resistance curves in ambient temperature and fire situation, the N-M curves become strongly dependent on the temperature field because of the physical and mechanical changes that occur in the material under elevated temperatures. Therefore, the present study aims to obtain the interaction curves of timber structural elements cross-section of commonly used members in civil construction, subjected to the action of thermal conditions (ambient and high temperatures), using a generalized numerical strategy based on the strain compatibility method (SCM) and Newton-Raphson method coupling. The adopted strategy is validated through the construction of N-M curves for timber cross-sections, subject to ambient temperature and different fire configurations and temperature distribution. The results obtained are compared with answers available in the literature.

Numerical nonlinear structural analysis of a timber truss roof under fire condition

2024-12-17T12:21:59+00:00

As greenhouse gases continue to rise and environmental impact reduction gains global attention, timber buildings have emerged as a vital asset in the pursuit of a sustainable future. Throughout history, timber has been linked to fire as a flammable material, and there have been numerous reports of out-of-control fires that highlight the importance of fire safety. Hence, the primary goal of this study is to assess the fire resistance of a timber truss roof. As the temperature rises, changes occur in the physical and mechanical characteristics of the timber members, causing the loss of the strength capacity and rigidity of part or the entire truss. Therefore, this research aims to explore the SAFIR computer program to carry out the following analyses: thermal analysis of the timber cross-section; and the structures thermo-mechanical analysis. By conducting the first analysis, it becomes possible to calculate the temperature field of timber members cross-section in a transient regime, while also obtaining information about the degradation of material properties. The second analysis provides the displacements, internal forces, critical time, and/or critical temperature of the timber truss during collapse. The numerical results obtained here were compared and validated with those from the literature (experimental results). The truss collapse time predicted by SAFIRs model was quite similar to the one observed in the laboratory. The developed numerical methodology allows for more realistic studies of timber elements or systems, enabling designs based on safety, economy, and sustainability.

Analysis of human intervertebral disc fracture mechanisms, case studies

2024-12-04T13:02:52+00:00

In the world, one of the leading causes of hospitalizations and disabilities is disc herniation. Therefore, understanding the mechanisms that lead to the development of this pathology is of high medical interest. For this purpose, a 3D model of a lumbar section (L5-S1) will be analyzed using tools commonly used in civil engineering, such as the Finite Element Method (FEM). The 3D model was generated from real imaging exams, such as computed tomography and magnetic resonance imaging. Subsequently, the mechanical properties (elastic modulus E and Poisson's ratio) of the structures of interest (annulus fibrosus, nucleus pulposus, and cartilaginous endplate) were incorporated into the models. Then, the model will be subjected to vertical compression forces combined with movements such as lateral, anterior, posterior flexions, and rotations. The primary objective of this project is to understand which combinations of loads and movements lead to structural damage, primarily affecting the annulus fibrosus, resulting in decompression of the nucleus pulposus. After analyzing the failure mechanisms of the structure, the variations in mechanical properties due to different degrees of pathology (protrusion, prolapse, extrusion, and sequestration) will be examined. This stage will contribute to a better understanding of the interaction between the components of the intervertebral disc following the development of pathology and the constraints imposed by its progression.

Analysis of thermal damage caused by retinal implant in a feline eye

2024-12-04T13:11:20+00:00

The advancement of the technology in the detection of some pathologies has provided several types of treatments that have been studied and applied to humans. Even hereditary diseases with no cure prognosis can be alleviated with the use of implanted devices. This is the case of Retinitis Pigmentosa, which has no cure. However, the use of retinal implants can help in partial recovery of the patient's vision. Several types of treatments have been studied and applied in humans. The present work was developed with the objective of obtaining insights that can help and guide a safe procedure for retinal implantation in patients with Retinitis Pigmentosa. In this process, certain precautions must be taken to avoid thermal damage of the patient's residual vision. Therefore, this work aims to calculate the thermal damage that may occur due to temperature increases as a result of the electrical power dissipated by the implant. To allow the validation of the three-dimensional geometry of the human eye, a previous study of a feline eye model with an epiretinal chip was carried out for which numerical simulation of temperature profiles and the calculation of thermal damage were done. In addition to temperature values, thermal damage is a function that quantifies the degree of cellular denaturation as a function of the power applied to the implant and its use time. Among some results presented, the main one proved that with the continuous application of an electrical power of 36.6 mW, the feline eye presented irreversible thermal damage after 5h12min. Furthermore, even after the implant is turned off, the thermal damage continues to increase, until the entire eye returns to its former thermal equilibrium. With the same methodology, an additional study is being carried out to calculate the advancement of the thermal damage in a human eye submitted to the ARGUS II implant, which was approved by the FDA (Foods and Drugs Administration USA) for use in humans. In this work, the SolidWorks® software was used for three-dimensional geometric modeling of the eyeball, its respective tissues and the epiretinal implant. The Ansys-Fluent® was adopted for simulation of temperature profiles. The calculation of the thermal damage as well as the heat source term due to the blood perfusion were programmed and inserted into the Ansys-Fluent® program, using the Finite Volume Method and unstructured meshes.

Bayesian parameter calibration of a one-dimensional hemodynamic model

2024-12-04T13:14:28+00:00

In this work, we couple a Bayesian optimization approach with a one-dimensional blood-flow model (known as ADAN86) to achieve a flexible and efficient strategy for the calibration of model parameters when in-vivo patient-specific data is available. The optimization step is addressed in the frequency domain, minimizing the discrepancies between the first harmonics of the in-vivo and predicted flow/pressure signals. The model parameters can be locally or globally perturbed, modifying the reference values in the same proportion for the whole system (global) or by region to account for the specificities of each location (local).

To test the proposed strategy, two cases are considered. The first one involves parameter calibration in a synthetic patient, where some parameters are locally modified, and the optimization process is compared in local and global scenarios. The second case addresses parameter optimization in a patient with in-vivo flow/pressure data, comparing the local and global calibration approaches.

The results show that the coupling between the Bayesian optimization process and the ADAN86 models yields an efficient strategy for the parameter calibration problem, which is naturally parallelizable and promising for data assimilation in computational hemodynamics.

Development of a Python Software for the Cardiovascular System Segmentation such as Arteries and Left Ventricle

2024-12-04T13:17:49+00:00

J. Festas, L.C. Sousa, S.S. Siusa, S.I.S. Pinto
Cardiovascular diseases (CVDs) are the leading cause of death globally, accounting for approximately 17.9 million deaths annually, with coronary artery disease (CAD) as a major contributor. CAD results from the build-up of atherosclerotic plaques, reducing myocardial perfusion and leading to conditions like angina and myocardial infarctions, severely affecting the left ventricles function. Advanced diagnostic tools are being developed to enhance the segmentation of cardiovascular structures, improving diagnostic accuracy and treatment outcomes.
Accurate segmentation is crucial for analyzing coronary behavior via Computed Tomography Angiography (CTA), a non-invasive alternative to coronary angiography, and for planning surgical interventions. Furthermore, the models retrieved after segmentation can be enlarged simulating hyperemia for further hemodynamic simulations. Similarly, segmenting the left ventricle in dynamic CT scans is vital for assessing cardiac health through measurements like ventricular volume and ejection fraction.
However, manual segmentation is time-consuming and suffers from variability, which can lead to significant diagnostic errors [1]. As such, there is a pressing need for more automated tools that enhance accuracy while reducing manual labor.
Most common advancements are in the realms of deep learning. These have propelled automated medical image segmentation, achieving results with high efficiency and reliability [2]; however, these require extensive data sets and high variability. In scenarios where such datasets are limited or exhibit low variance, these models risk developing biases or failing to achieve accurate results in cases that are very different then the norm of the training dataset.
To mitigate these risks, we are developing a Python-based semi-automatic algorithm that relies on existing open-source libraries, enhancing them with custom developments tailored to our specific needs, while relying on technician input to enhance classical image processing, ensuring adaptability to varied clinical conditions. We are testing this tool with patient data, with results that are very promising: segmentation similarity results of around 85%. We plan to release it as open-source software, encouraging a community-driven approach for continuous improvement and adaptation to clinical needs.
The initial tests allows to believe this tool can be a robust and accurate software that can be used in hospital or for investigation purposes. The semi-automatic nature allows for user input and post processing tailoring of the segmentation.
[1] Tavakoli, V. et al. (2013) A survey of shaped-based registration and segmentation techniques for cardiac images. Computer Vision and Image Understanding 117, no. 9: 966-989.
[2] Litjens, G. et al. (2017) A survey on deep learning in medical image analysis. Medical Image Analysis 42: 60-88.

Do gender-specific carotid plaque characteristics and stroke risk prediction suggest different biomarkers for men and women?

2024-12-04T13:21:05+00:00

There is convincing evidence for sex differences in carotid atherosclerosis although the relation between sex and plaque characteristics needs further insight accessing individual patient data characteristics to perform these analyses. The structure and composition of arterial walls can differ between genders. At every age, most women are of shorter stature and smaller size than most men. Height is related directly to arterial caliber and length as well as cardiac output through effects on stroke volume and heart rate.
Statistical comparisons for gender suggest that females appeared more vulnerable to the progression of arterial stiffening [1]. Carotid plaque measurements using maximum wall thickness as 1-dimensional (1D) size, wall area as 2D size, and wall volume as 3D size are larger in men opposed to women [2]. Nevertheless, the normalized wall index, which accounts for the total vessel size, shows no significant difference between males and females. Regarding the number of calcifications, it was found that men have higher calcification volumes than women and accordingly intraplaque hemorrhage is more common in men than in women [3]. Sex differences in stroke incidence, and complication rate have been reported [4].
The current study aims a review of recent publications on gender-specific differences regarding carotid plaque characteristics and stroke risk aiming different biomarkers for men and women what may benefit clinical management and specific treatment.
[1] Wang Z, Li W, Liu W, Tian J. Gender is a determinant of carotid artery stiffness independent of age and blood pressure. Br J Radiol. 2021 Mar 1;94(1119):20200796.
[2] van Dam-Nolen DHK, van Egmond NCM, Dilba K, Nies K, van der Kolk AG, Liem MI, Kooi ME, Hendrikse J, Nederkoorn PJ, Koudstaal PJ, et al. Sex differences in plaque composition and morphology among symptomatic patients with mild-to-moderate carotid artery stenosis. Stroke. 2022; 53:370378.
[3] Scheffler M, Pellaton A, Boto J, Barnaure I, Delattre BM, Remuinan J, Sztajzel R, Lovblad KO, Vargas MI. Hemorrhagic plaques in mild carotid stenosis: the risk of stroke. Can J Neurol Sci. 2021; 48:218225.
[4] Voigt S, van Os H, van Walderveen M, van der Schaaf IC, Kappelle LJ, Broersen A, Velthuis BK, de Jong PA, Kockelkoren R, Kruyt ND, et al; DUST study group. Sex differences in intracranial and extracranial atherosclerosis in patients with acute ischemic stroke. Int J Stroke. 2021;16: 385391.

Hand Vibration Analysis due Impact Equipment

2024-12-04T13:26:04+00:00

Several human health problems can arise due to the loads transmission from impact equipment manipulated directly with the operator's hands. These issues can also extend to the upper limbs. Equipment such as stone breakers exhibit significant vibration levels during operation, and understanding how the intensity and duration of this vibration affect the efforts transmitted to the operator is necessary to assess potential mitigation during work. Therefore, this study aims to perform an operator's hand numerical model, using the finite element method, while operating the stone breaker, having as input data the vibration caused by the stone breaker. The objective is to determine the level of stress imposed and the resulting transmissibility on the worker's hands. In addition, to examining the changes in these values resulting from the positions modifications where the worker holds the equipment.

Intelligent Methodology Using Machine Learning for Epileptic Seizure Identification Based on Time-Frequency Analysis of EEG Signals

2024-12-04T13:29:12+00:00

The diagnosis of epilepsy is conducted through visual inspection of electroencephalogram (EEG) signal recordings. However, due to the variations in convulsive disorders, it can be challenging for clinicians to constantly monitor the patient for seizure type, especially because EEG records contain hours of signal. Nevertheless, these patterns present in EEG signals can also be identified through signal classification methods based on signal processing and machine learning approaches. In light of this, this study proposes the development of a methodology for epileptic seizure type classification based on analysis of time-frequency characteristics of EEG signals, using Continuous Wavelet Transform (CWT) and joint moments of time-frequency distribution. Epileptic seizure classification was performed using a convolutional neural network (CNN), employing k-fold cross-validation methods. Accuracy, sensitivity, specificity, and area under the curve (AUC) metrics were obtained to validate this algorithm. The achieved results for the CNN classifier were 96.54% accuracy, 96.54% sensitivity, 96.54% specificity, and AUC = 0.90%.

Into the gray matter: construction and coupling of multiscale highly-detailed arterial networks in the human cerebral cortex

2024-12-04T13:32:25+00:00

Stroke-related diseases represent 11% of worldwide deaths. State-of-the-art medical imaging describes many aspects of cerebral circulation. Nevertheless, the limited resolution of these techniques hinders the study of the hemodynamics in smaller vessels. Computational models aid in this problem, providing tools to characterize cerebral hemodynamics in clinical scenarios of interest that are otherwise inaccessible. This work aims to build vascular networks in the human cerebral cortex to study hemodynamics across different regions of the gray matter. The method is based on the Constrained Constructive Optimization method (CCO), called PDCCO, which generates vascular networks following a set of anatomical rules. A patient-specific MRI geometry of the cerebral gray matter is used to register an existing vascular model of the major cerebral vessels in the pial surface of the brain, from where the network is expanded. The brain geometry is partitioned into three territories for each large cerebral artery. The vascular generation is conducted independently for each territory and merged into a single network. First, a thin volume of the pial surface is filled with blood vessels down to the scale of penetrating arterioles of 50 μm. The network is further extended downwards to penetrate the gray matter, and deep vascularization is achieved by appending sub-tree networks to each terminal vessel. These sub-trees are generated separately with vascular properties associated with the gray matter. The final network reaches 234000 vascular segments in the pial network, out of which 116977 are terminal vessels. In turn, each terminal vessel gives rise to a network of 50 terminals, yielding 5 million terminals, and 10 million vascular segments, for each hemisphere. Over the pial surface, the diameters vary between 2100 μm and 26 μm, with terminals between 50 μm and 60 μm, and the pressure drops from 100 mmHg to a range between 50 mmHg and 70 mmHg. The network can be coupled with existing blood flow models of the entire cardiovascular system for the simulation of pulsatile blood flow to study pressure heterogeneities along the cerebral cortex in normal and pathological systemic conditions. This novel approach proposes a strategy for the automatic vascularization of the brain, with the aim of understanding microcirculation under different conditions, allowing the study of the risk of stroke, among other mechanisms involved in the onset and progress of degenerative diseases.

Simulation of Blood Flow in Arteries for Functional Assessment of Coronary Disease: Implementation of Numerical Code

2024-12-04T13:36:00+00:00

Cardiovascular diseases are a major cause of mortality and morbidity in developed countries. Coronary atherosclerotic disease (CAD) is a degenerative process that is characterized by the development of atheromatous plaques on the wall of coronary arteries. Clinical manifestations of CAD range from stable angina, resulting from progressive plaque growth with partial obstruction of the arterial lumen (stenosis) and consequent limitation of coronary blood flow. In clinical practice, a diagnostic strategy is widely used to assess the functional relevance of CAD: the invasive assessment of myocardial fractional flow reserve (FFR).
Coronary Computed Tomography Angiography (CTA) is an established non-invasive diagnostic tool for evaluating CAD. However, CTA can overestimate anatomic stenosis and is limited in that it does not provide information on the hemodynamic relevance of coronary stenosis. Thus, the implementation and numerical simulation of blood flow in arteries in the most real physiological conditions has been one of the main areas of interest of the authors [1]. The main purpose of this work is to develop and validate a computational tool for calculating the FFR and hemodynamic descriptors.
In this way, to obtain the most accurate non-invasive FFR, the hemodynamic numerical tool was hardly improved to establish real conditions, specific to each patient case with CAD. Therefore, to achieve accurate pressures, Windkessel models, mainly based on the resistance of blood flow [2], were implemented considering hyperemia conditions (maximal dilation of the coronary tree), since the patient must be subjected to this condition during the catheterization to obtain the invasive FFR (reference value for validation). Moreover, the 3D patient-specific geometry of the artery was modified to simulate blood flow in hyperemic conditions. The numerical code development was performed in ANSYS® software.
After validation, the authors aim to create a software for local use, allowing a comprehensive assessment of CAD in an accessible, fast, reliable, and non-invasive way.

[1] Pinto, S.I.S. et al. (2020). The impact of non-linear viscoelastic property of blood in right coronary arteries hemodynamics a numerical implementation. International Journal of Non-Linear Mechanics 123, 103477.
[2] Boileau, E. et al. (2018) Estimating the accuracy of a reduced-order model for calculation of fractional flow reverse (FFR). Int J Numer Meth Biomed Engng 34, e2908.

Use of hyperelastic models and sliding connections to model the mechanical behavior of musculoskeletal structures

2024-12-04T13:39:30+00:00

The generation of movement and force produced by the musculoskeletal system in various parts of the body is a topic of high interest in academic research. The increasingly detailed and precise knowledge of the biomechanical behavior of these structures is required to meet the demands of health care and human well-being. The use of structural analysis tools is essential for that purpose. In some situations, in vivo or in vitro tests present a series of inconveniences; therefore, computational simulations prove to be complementary to experimental tests to analyze human movements and generally offer advantages in terms of cost and time. To contribute to the construction of a more precise understanding of the mechanical behavior of biological structures, this work aims to numerically simulate the planar behavior of the upper limb of the human body through the action of skeletal muscles and the movement of adjacent joints. The mechanical simulation is performed through a computational code developed based on the Positional Finite Element Method (PFEM), capable of performing geometric nonlinear analyses directly in its formulation. The proposed modeling treats the muscle tissue as a composite material made of a three-dimensional matrix and embedded simple bar elements, which represent the muscle fibers. Despite the three-dimensional nature of the model, it is important to emphasize that the work aims at a two-dimensional application, simulating the mechanical behavior of musculoskeletal structures on a single plane. The Saint-Venant-Kirchhoff hyperelastic constitutive model is used to define the relationship between stresses and strains in the materials, highlighting its potential and limitations. Additionally, the active muscle behavior is considered through a numerical strategy that represents fiber contraction by allows controlling the initial length of the bar element. The joint studied in the model is the elbow, modeled through the formulation of sliding connections, allowing relative movement between connected surfaces. Since the mechanical simulation is planar, only flexion and extension movements are reproduced. The kinematic conditions imposed on the system to promote sliding are introduced into the problem using Lagrange multipliers. The proposed model has the potential to describe the mechanical response of human body members in a simplified manner.

A Preliminary Numerical Thermal Analysis of an Endometrial Ablation Procedure Based on Foleys Catheter

2024-12-06T14:46:45+00:00

Dysfunctional uterine bleeding (DUB) is an ailment affecting a substantial number of women during a significant part of their reproductive years. This condition usually leads to discomfort, mild or severe pain, or, in some extreme cases, anemia. It may be caused by diverse factors such as hormonal issues, structural abnormalities, or even cancer in a womans reproductive tract. A typical DUB treatment requires a pharmacological approach through the prescription of drugs. Nonetheless, some patients require a more involved treatment calling for surgical procedures. In order to avoid hysterectomy, which is the complete removal of the uterus, the medical community has devised, over the years, alternative surgical schemes to handle DUB issues. One such treatment is the endometrial ablation technique where the inner lining of the uterus is subjected to a controlled destruction by using a hot, approximately constant-temperature fluid inside a balloon, which is placed in contact with the uterine wall of the patient. As a means to avoid the high costs associated with such devices, the medical community has proposed a similar treatment in which the fluid inside the balloon is no longer held at a high constant temperature but rather diminishes as the treatment progresses. The main purpose of this contribution is to critically assess the effectiveness of this second, low-cost endometrial ablation treatment. Consequently, a mathematical model is devised in which Pennes bioheat equation is employed to predict the transient temperature field of the uterine wall together with an energy balance that yields the temperature of the saline solution inside the thermal balloon, throughout the duration of the treatment. These equations aresolved by utilizing the finite volume method and the numerical predictions are verified by comparing the present results with similar cases from the literature. Once the verification phase is authenticated, the uterine wall and fluid balloon transient temperature fields are obtained for typical situations reported in the medical literature. On general grounds, the simulations indicate that the extent of the affected tissue is strongly dependent on the volume,on the type of fluid inside the thermal balloon, and on the magnitude of the perfusion of the uterus. Moreover, it was found that the proposed low-cost treatment can indeed be a successful alternative to the standard endometrial ablation process under some viable circumstances that are described in the contribution.

An efficient Matlab code for two-dimensional heat transfer analysis applying the finite-volume theory.

2024-12-09T10:56:22+00:00

In engineering, professionals must understand the properties and performance of a specific material before exposing it to the conditions of a specific application. In this context, engineers and scientists have been searching for materials with peculiar properties that withstand extreme adversities, responding with high performance to the challenges imposed. Heat transfer studies are essential and have been extensively explored due to their relationship with our daily lives, such as in thermal insulation systems and electronic device applications. Over the past few decades, computational models have been used and have achieved excellent results in studying and predicting material properties. The Finite Volume Theory (FVT) was first introduced in 2003, using Cartesian coordinates. It establishes the continuity and boundary conditions through the faces of the discretized analysis domain in a surface-averaging sense. The theory also satisfies the flux balance equations in the subvolumes in a volume-averaged sense. The temperature fields are approximated by second-degree polynomials that are expressed in the local coordinates of the subvolumes. Despite the versatility and efficiency of numerical methods, the long processing time has led researchers to look for ways to improve the performance of computational models. One solution is to use computational language tools that simplify operations and reduce code execution times, even for large-scale problems. This study aims to present an efficient code that uses MATLAB computational resources to analyze two-dimensional heat transfer by applying the finite-volume theory.

An Eulerian-like interface-capturing approach for modeling the fouling process by crystallization

2024-12-09T10:59:32+00:00

Calcium carbonate (CaCO3) is an inverse solubility salt commonly scaled in heat exchangers when the fouling mechanism by crystallization occurs. Several models have been proposed to predict the fouling behavior, considering the growth of fouling mass as the difference between deposition and removal rates. Despite the different alternatives suggested in the literature to approximate these rates, there has been limited discussion regarding the fouling layer growth interface capture within a continuous domain during the time-dependent crystallization process. Hence, in this work, we propose an Eulerian interface-capturing approach for modeling the fouling process by crystallization (EICAFC). This scheme will be implemented using the standard Galerkin Finite Element Method with linear interpolation polynomials. The EICAFC procedure will be outlined employing the Bohnet fouling model. Results about fouling thickness, mass accumulation, fouling resistance, and the EICAFC performance will be discussed.

Application of Artificial Neural Networks in predicting the thermal performance of grooved heat pipes

2024-12-09T11:04:07+00:00

Heat pipes are versatile, relatively easy to construct, and capable of exchanging large amounts of heat between small temperature differences, even without external pumping. On the other hand, these devices have complex equations, which usually complicates their development, generating more extended periods of research and expenses. Methods that use computational intelligence, such as Artificial Neural Networks (ANN), have the ideal characteristics for use in problems of this type. ANN are algorithms that can solve complex problems using only experimental data, even without knowledge about the physics of the problem, limited only by the quality of the data used and the available computational power. In many cases, the results found using ANN have lower error percentages than those obtained using conventional methods. The database used was generated from an experimental investigation of the thermal behavior of heat pipes with a wicked structure of axial grooves and using water as the working fluid. The results were used to train two different Artificial Neural Networks. The Neural Networks used were the Multi-Layer Perceptron (MLP) and the Extreme Learning Machine (ELM). Filling ratio, slope, and dissipated power were used as inputs to the networks, and as output, we have the expected thermal resistance of the heat pipe. The results show that both ANN were able to generalize the problem, presenting errors of less than 25%. It is also possible to note that the MLP presents better results, with an error of about 18%. These values show that ANN are viable as a tool to improve the development of grooved heat pipes.

Application of computer simulation to study heat transfer in concrete with different densities

2024-12-09T11:07:44+00:00

Thermal comfort in buildings has been researched through new materials that reduce energy consumption. Lightweight concrete appears as an alternative for civil construction as it presents particular characteristics such as lower specific mass and a higher thermal insulation capacity than conventional concrete. The objective of this work was to evaluate the heat transfer process in concretes with different densities using computational modeling. A mathematical model for heat transfer in concrete blocks with different densities was implemented and all simulations were carried out using the Ansys Student 2023 R2 program. Normal Density Concretes (CDN) and Foamy Cellular Concretes (CCE) were produced with two different proportions, one with 10% foam (CCE10) and the other with 20% foam (CCE20), using air-entraining additives to generate foam. The simulation results presented a good representation of the heat transfer phenomenon when compared with the experimental results. They showed that the addition of foam to concrete reduces thermal conductivity, improving energy efficiency in buildings, demonstrating the potential of these materials for applications in civil construction.

CFD-based prognosis of hydrate dissociation operation inside X-mas tree with slickline intervention

2024-12-09T11:10:10+00:00

This study evaluates the use of a retrievable heating tool, deployed via slickline, for dissociating hydrate plugs within a subsea well Christmas Tree (WCT). The focus was on a specific hydrate plug located within the WCT bore, analyzed through multi-phase Computational Fluid Dynamics (CFD) simulations enhanced by adaptive mesh refinement techniques. Findings indicate that a power setting of approximately 3.1 kW is optimal, effectively balancing operational efficiency with safety. This power level maintains temperatures just below the critical threshold of 120°C and achieves complete hydrate dissociation in around three hours. The investigation underscores the importance of precise power calibration and management of its associated uncertainties to ensure the integrity and effectiveness of hydrate dissociation operations.

Comparison between a stabilized mixed finite element formulation for Hershel-Bulkley fluid and regularized models

2024-12-09T11:15:16+00:00

In this work, a mixed stabilized finite element formulation with continuous interpolations for velocity and descontinuous formulation for pressure is used to approach pseudoplastic materials with yield stress, that is, non linear viscoplastics. Here, Herschel-Bulkley model, [1], and regularized ones for the apparent viscosity are considered. This formulation is based on two well succeeded stabilized methods, separately, one for pseudoplastic problems (non linear) without yield stress [2], and the other for linear problems with yield stress (ideal plastic), [3],which are modeled by linear constitutive equations with inequality restriction.
Firstly it is presented the difficulties encountered by classical formulations in solving the problems separately, as well as solutions proposed before for each of those problems.
Regularized generalized alternatives (based on simple, Papanastasiou [4] and Bercovier-Engelman [5] schemes) are presented to deal with the discontinuity of the constitutive relations for the materials with yield stress and results are presented showing their limitations. They are compared with the proposed stabilized formulation which allows obtaining stable results without the necessity of regularizations, applied directly to the Herschel-Bulkley constitutive relation.
References
[1] A.H.P. Skelland. Non-Newtonian Flow and Heat Transfer. John Wiley & Sons, Oxford, 1967.
[2] Bortoloti, M. A. A. and Karam F., J. A Stabilized Finite Element Analysis for a Power-Law Pseudoplastic Stokes Problem, Applicable Analysis, V. 95, n.2, pp. 467-482, 2016.
[3] Faria, C. O. ; Karam F., J. . A Regularized Stabilized Mixed Finite Element Formulation for Viscoplasticity of Bingham Type, Computers and Mathematics with Applications, 2013. V66, no.6, pp. 975-995, 2013.
[4] T. C. Papanastasiou e A. G. Boudouvis. Flows of viscoplastic materials: Models and Computations. Computers & Structures, 64(1-4):677694, 1997.
[5] M. Bercovier e M. Engleman. A Finite-element method for incompressible non-Newtonian flows. Journal of Computational Physics, 36:313326, 1980.

Conjugated Heat Transfer of the stator of an synchrounous electrical machine

2024-12-09T11:18:40+00:00

Electrical energy generation in remote islands and ships are mainly due the energy conversion from chemical (fuel) to mechanical by an engine and converted from mechanical to electrical by an alternator. The losses in the alternator during the energy conversion are responsible for the increase of its temperature. In order to control the temperature level of the equipment, it is necessary to control how heat is evacuated. The present work numerically evaluates the heat dissipation in the stator of an electrical machine and its temperature maximum levels. Heat is generated in the cooper (windings) and steel (stator main body) during the energy conversion and is evacuated due the forced airflow throughout the stator. In order to reduce computational costs, due geometrical symmetry, one quarter of the machine was modeled. In addition to symmetry, the momentum boundary conditions consist in inlet, outlet and noslip at the walls and the thermal boundary conditions consist in imposed heat fluxes. In order to isolate the inlet and outlet boundary conditions, they were positioned at least 10 times the respective channel height far from the stator. The model is transient and the initial flow field is at rest (0 m/s) and at ambient temperature (300 K). The geometry was constructed using Salome-Meca software and the mesh was generated using the snappyHexMesh solver from OpenFOAM v11. The foamMultiRun solver from OpenFOAM was employed to create the numerical model. It solves the mass, momentum and energy equations in transient regime. The numerical schemes employed were linearUpwind (second order) for the advective terms, Gauss for the diffusive terms (linear) and the backward time discretization (second order). The turbulence model employed was the K-omega SST. The model predicted where were the regions inside the stator with intese heat transfer, which implies in lower temperature magnitudes and also where there were temperature peaks. Then correlation between the temperature and flow fields were discussed.

Effects of Soil Hygrothermal Properties on the Performance of an Earth-Air Heat Exchanger

2024-12-09T11:21:44+00:00

Buildings are responsible for a large part of energy demand worldwide. To collaborate to reduce this demand, the use of passive air conditioning has proven to be beneficial for energy savings. In order to improve thermal comfort in built environments, Earth-Air Heat Exchangers (EAHE) can be installed as a low-cost option. Using low energy consumption, in this system, the ambient air circulates through a pipe buried at a certain depth in the ground, causing it to heat up or cool down, depending on weather conditions. These effects are possible due to the high thermal inertia of the soil. In this context, the climatization performance of EAHE depends directly on the hygrothermal properties of the soil, and the effects of heat, moisture, and air transport on the operation of an EAHE are barely explored in the literature due to many difficulties, such as modeling complexity, computer run time, numerical convergence and highly moisture-dependent properties. Therefore, to analyze the effects of hygrothermal properties of soil, a 2D model has been developed to calculate the coupled heat, air, and moisture transfer. The linearized set of discretized governing equations was obtained using the finite-volume method and solved via the MultiTriDiagonal-Matrix Algorithm, substantially improving the numerical stability and reducing the computer run time. To validate the temperature distribution along EAHE, a prototype was built on the Federal University of Technology of Paraná (UTFPR) - Campus Ponta Grossa, which includes 100 mm diameter Polyvinyl Chloride (PVC) ducts, a fan for airflow control, where a series of k-type thermocouples were inserted along the EAHE. Data were recorded hourly using a data acquisition system during the summer period.

Evaluation of the Effect of Natural Gas Enrichment with Hydrogen on Gas Turbine Emissions: Numerical Study Based on Chemical Equilibrium

2024-12-09T11:24:59+00:00

Decarbonization involves the intensive use of renewable energy to obtain a sustainable energy matrix. Brazil has an electrical matrix strongly anchored in renewable sources, historically in hydraulic energy, and more recently, in solar, photovoltaic, and wind sources. The latter are stochastic and, therefore, have strong restrictions on their insertion into the matrix in a broad and dominant manner. Due to these limitations, excess supply can be used to produce green hydrogen and even methane in a process called methanation (chemical reaction between CO2 and H2). The use of electrical energy from renewable sources for the production of fuels is known in literature as power-to-gas. These fuel vectors (H2 and CH4) can be used directly to generate energy or can be mixed with natural gas to enrich it in terms of energy and potentially reduce emissions. This study evaluates the effect of enriching mixtures of natural gas and hydrogen on CO, CO2, and NOx emissions, considering combustion applications in Gas Turbines. The analyses were numerical and involved the use of a thermodynamic combustion model with chemical equilibrium. The chemical equilibrium model is based on chemical equilibrium constants and assumes that the reactants and products are ideal gases. The volumetric fractions of H2 in the mixture from 0 to 30% and the effect of the combustion pressure were investigated. The pressure was varied according to the application chosen. Gas turbines are part of the combined power cycles, and plants can operate with gas turbines of different pressure ratios according to the model, power, and manufacturer of the Gas Turbine. The analyses focused on medium and large gas turbines, and the chosen pressure range was 12:1 to 24:1.

Numerical analysis of trajectory and range for different boattail angles of an artillery projectile

2024-12-09T11:29:10+00:00

This article aims to compare the different trajectories of a 155 mm artillery shell when changing the angle of its trailing edge, also known as boattail. To this end, an iterative numerical analysis computer program was developed where the differential equations of the projectile trajectory are solved with 4 degrees of freedom, that is, through the modified mass-point method. When solving the system of differential equations, the 4th order Runge-Kutta method is used. The trailing edge angle is a geometric characteristic that is directly related to the base drag force experienced by the ammunition. Furthermore, the magnitude of the drag force has a great influence on the firing range and this, in turn, is of great relevance for the development of a projectile. Drag coefficients for Mach numbers between 0.5 and 3.0 are obtained using the PRODAS ballistic calculation software. Each boattail angle generates a curve of drag coefficients as a function of Mach number. These values are then used as input data in the source code and thus the simulation can be performed. The results obtained are validated by existing data in the literature and highlight variations in trajectories, showing that the maximum range can be obtained by determining an ideal boattail angle.

Numerical Study of the Effects of Residual Stress in Welded Pipe Joints

2024-12-09T11:58:55+00:00

In general, welding processes can be understood as the establishment of the union of parts, generally metallic, using a heat source to promote the fusion of materials, with or without the presence of pressure efforts. Studies related to the distributions and levels of residual resistance arising from the thermal cycles involved in welding processes are of vital importance for evaluating and guaranteeing the integrity of welded pipes. This work proposes the implementation of a routine in PYTHON language to automate the production of thermomechanical coupling welding models using the ABAQUS® CAE finite element tool, considering the heat distribution model of the welding source according to Goldak et al. (1984), better known as the double ellipsoid model. The studies are produced considering an ambient temperature of 20 °C and another with preheating of the tubes to 300 °C. The results achieved by this study are related solely to analyzes of the residual stress fields in a thin walled tube joint manufactured in AISI 304 stainless steel, welded using TIG (Tungsten Inert Gas) processes in a single pass. Thus, this study seeks to analyze the hoop and axial residual stress distributions on the internal or external walls of post-welded tubes in angular positions 0°, 90°, 180° and 270°, whether or not there is uniform preheating of the pre-welding pipes. The results show that, in general, residual stresses differ slightly with the angular position, being relatively high when compared to the yield stress of the steel, and therefore have a considerable impact on reducing the mechanical strength of the welded joint. It should also be noted that when considering the preheating of the pipes there is a significant decrease in the peak temperatures reached in the transfer process, in the cooling rates and in the residual stress levels of the joints, especially in the most critical regions, located in the proximity from the center of the weld beads.

Thermal and fluid flow simulation of a compact heat exchanger with micropillar

2024-12-09T12:08:04+00:00

Technological advances in manufacturing processes and materials have enabled the miniaturization of electronic components, which is positive in many ways but also introduces thermal management challenges due to the increased power density of components and reduced surface area for heat dissipation. In this sense, the use of compact heat exchangers presents itself as a possibility for controlling the temperature of these devices, such as those based on micropillars and microchannels. This study is based on the numerical simulation of a compact heat exchanger of square micropillars with 0.3 mm width and height and 0.2 mm inter-fin spacing, with different arrangement configurations. Deionized water is used as the working fluid for the single-phase flow regime under different mass velocities (442 to 1096 kg/m²s) and input heat powers (9 to 15 W). The modeling was implemented in the Ansys Fluent software, and the results obtained were validated and compared with experimental data, where data adherence was verified. Moreover, the numerical results were compared with another numerical reference case based on a plain surface without micropillars. Considering the thermo-hydraulic behavior through the Thermal Performance Index (TPI), the staggered arrangement presents the best performance, even though its pressure drop is greater than in the aligned arrangement. Regardless of the micropillar arrangement, a TPI greater than one was found, indicating that micro-pin fin heat sinks can be very effective as a thermal management technique.

Thermal Parameter Estimation of Sandwich Panel using Numerical Solution of Inverse Heat Conduction Problem

2024-12-09T12:12:27+00:00

In this work, a numerical formulation to solution of the inverse heat transfer problem, based in the implicit finite difference method and Monte Carlo method, is developed to estimate the thermal properties of the sandwich panel. It is realized the sensitivity analysis of the parameters and the thermal contact resistance along the layers interface is used. Experimental results of temperature are used in the numerical formulation to determine the thermal properties (conductivity and the specific heat) of the layers materials and to predict the thermal behavior of the panel. The results obtained show that the formulation estimates with adequate accuracy the material thermal proprieties.

Thermoregulation of integrated photovoltaic panels with bio-based phase change materials

2024-12-09T12:17:43+00:00

Although photovoltaic (PV) technology has achieved significant advancements in harnessing irradiation to generate electricity, different questions remain open, especially regarding the adverse effects of high temperatures on the PV system. As the temperature of PV panels increases, their energy-conversion efficiency decreases, reducing the overall electricity production. High temperatures also accelerate the degradation of the PV panel, leading to shorter operational lifespans and higher maintenance costs. Hence, reducing the PV panel temperature throughout the day can prevent thermal degradation and increase its efficiency. In the present work, we numerically evaluate the thermal behavior of a PV system integrated with a phase change material (PCM). The numerical model uses the Finite Volume Method to solve the conservation equations of mass, momentum, and energy. A 3D transient thermal model incorporating the PCM enthalpy formulation was developed to analyze the PV panel temperature. The thermal model considers the energy transfer by conduction, convection, and radiation throughout the day. A mean absolute deviation of 3% was obtained for the PV panel temperature by comparing it with experimental data available in the literature. After the numerical model validation, the PCM was changed to a bio-based PCM (bioPCM) consisting of la uric acid, whose melting point is relatively high (from 4446 °C), allowing its use in regions of high solar incidence. Furthermore, it has a high latent heat of fusion, being chemically stable and non-toxic. Using the proposed bioPCM, a temperature reduction of 9 °C was obtained, increasing the energy production, on average, by 9% compared to a conventional PV without PCM. Overall, using the proposed bioPCM can avoid excessive losses of energy-conversion efficiency under high irradiance conditions and extend the lifespan of photovoltaic panels.

A study on the usage of magneto rheological elastomers for non-linear aeroelastic oscillations control

2024-12-12T12:41:54+00:00

Magneto Rheological Elastomers (MRE) are composite intelligent materials, which can substantially change their viscoelastic properties due to their high magneto-sensitivity in response to different regimes of external magnetic field. Under the influence of a magnetic field, both storage shear and loss factor of MREs increase, this field-induced phenomenon is often referred to as the magnetorheological effect. The practical application of MR materials demonstrates great potential for several areas, as indicates the increasing number of patents registered in the last decade. This research is included in a line aimed to develop MRE devices for structural vibrations' control, exploring the magnetorheological effect and its capacity to promote gains in viscoelastic properties, thus enabling changes of relevant magnitudes in structural systems, such as the natural frequency and damping ratio. This adaptive behavior can be studied by the analysis of qualitative numerical simulations, this study proposes to investigate the effectiveness of MRE devices on wind induced aeroelastic oscillations (galloping equation), the results are obtained by the Multiple Scale Method and numerical integrations, showing a trajectory suppression on the phase-plane of limit cycles to focal points, as well as a three-fold change in the critical speed and alterations on the shape of the Hopfs bifurcation diagram.

Analysis of dynamic response on aircraft runway and taxiway bridges

2024-12-12T13:13:18+00:00

This paper presents a computational analysis of the dynamic responses of an aircraft bridge subjected to a moving mass and corresponding load in conditions of taxiway and runway, moving through its entire length. It aims to understand the dynamic behavior of the bridge and to determine its transversal response. The Euler-Bernoulli beam model is here, discretized in finite elements and a dynamic algorithm was applied, using numerical integration by Newmarks Method for the solution of ordinary differential equations to obtain the transversal displacements of the structure in the time domain, to evaluate its responses comparing the results with different velocities, damping ratios, and the effect of contribution of moving mass. The main objective is to apply the results obtained with the method to obtain displacements due to moving masses and corresponding loads contributing to the design of aircraft bridges with reliability.

Comparison of the performance of a cylindrical Hall thruster with different anode voltages via numerical simulations

2024-12-12T13:16:01+00:00

Plasma propulsion, or electric propulsion, arises from the need to explore deep space in a more economical and efficient manner. The cylindrical Hall Thruster (CHT) is an electric propulsion device that offers high propellant utilization and performance at smaller dimensions and lower power levels than traditional plasma propulsion devices. The reduced dimensions of the CHT operating at lower power levels make it an interesting option to provide propulsion of CubeSats and small satellites. The CHT consists of a channel with an annular anode through which neutral gas is injected. The neutral gas is then ionized by magnetized electrons injected from an external hollow cathode. The resulting plasma ions are ejected from the device due to the positive electrostatic potential at the anode, giving thrust. The aim of this work is to understand and study the plasma in the discharge channel of a CHT through numerical simulations. The numerical code describes the plasma with a hybrid model in which the electrons are treated as a fluid and the ions and neutral atoms as pseudo particles. The simulations were conducted for two different potential values at the anode, namely, 150 V and 300 V, representing different modes of operation. The results obtained with this simplified model allow to obtain an optimal configuration for a future prototype to be implemented at the Plasma Physics Laboratory at the University of Brasilia.

Dynamic effects on different rotor profiles for eVTOL applications

2024-12-12T13:19:05+00:00

Electric Vertical Take-Off and Landing (eVTOL) aircraft, commonly known as eVTOLs, represent a recent and promising concept for enhancing urban mobility, particularly in densely populated areas. However, the development of eVTOLs has been accompanied by various technical and technological challenges, primarily due to the rapid introduction of new concepts. Among these challenges, this study focuses on investigating the dynamic effects on rotor blades designed for such aircraft. Rotor blades, being subject to rotational dynamic effects, exhibit behavior distinct from components lacking angular velocity. Therefore, they are of particular interest for dynamic analysis. The study begins by defining a simplified geometry representative of a rotor blade, which serves as the basis for applying finite element methods using Ansys software. This approach enables the observation of the system's response to rotation. Following, more detailed geometries representing rotors are modelled, respectively in NACA 0012, VR 08 and VR 12 airfoils, which are then subject to the rotational effects numerical calculations. The results obtained for the different aerodynamic profiles are then compared, presenting the differences caused by the different geometries and mass distributions implied. The results obtained from the analysis highlight the significant impact of angular velocity on the fundamental frequencies and modes of the dynamic system. These findings suggest the presence of effects such as spin softening and strain stiffening, along with identifying important frequency coupling points.

Enhancing UAV Propulsion: Insights into Toroidal Propeller Dynamics through CFD Simulations

2024-12-12T13:21:48+00:00

Toroidal propellers have emerged as a transformative breakthrough in aeronautical propulsion, promising enhanced efficiency, maneuverability, and notably, noise reduction. Utilizing Fluent/ANSYS for computational fluid dynamics (CFD) simulations, this study endeavors to delve into the performance dynamics of toroidal propellers in aeronautical applications, with a specific focus on assessing thrust generation, efficiency, and acoustic pressure, especially pertinent in the context of unmanned aerial vehicles (UAVs).

The simulations meticulously modeled the intricate airflow dynamics around toroidal propellers, using Fluent/ANSYS's steady, turbulent flow solver, incorporating parameters such as airspeed, propeller rotational speed, and toroidal rotor geometry. The comprehensive three-dimensional computational domains accurately represented the propeller geometry and airflow interactions, facilitating a nuanced analysis of performance metrics.

Through comparative analyses of toroidal propellers against a conventional design, aerodynamic advantages emerged, notably in noise reduction. The unique closed-loop structure of toroidal propellers minimizes drag effects from swirling air tunnels, significantly attenuating the propeller's acoustic signature. These findings represent a pivotal step forward in our understanding of toroidal propeller aerodynamics, underscoring their immense potential in UAV applications. Moreover, they serve as a compass for future design refinement and practical integration into aeronautical engineering practices. With the groundwork laid for experimental validation and real-world deployment, the prospect of using toroidal propellers in both commercial and military aviation appears increasingly tangible.

Frequency and stress optimization of an engineered wood portal frame suporting a rotating machine

2024-12-12T13:25:13+00:00

We consider a portal frame with 3 prismatic bars. The horizontal beam, of length L, is articulated at the top of the vertical columns, of height h, embedded in the base. The cross sections are rectangular with thickness b, constant, and width d, which can be different in the beam (dv) and in the columns (dc), always greater than or equal to the thickness. The material is considered linear and homogeneous elastic, with given modulus of elasticity (E) and density. In the middle of the beam span, a motor of mass M is mounted, rotating at a frequency of N rpm.
Considering only the Service Limit State, we present the minimization of the mass of the structure so that the motor rotation frequency is always at least 20% above any of the first 2 undamped free vibration frequencies of the frame.

Implementation of a control project based on Tuned Liquid Column Dampers optimized by Teaching-Learning Based Optimization

2024-12-12T13:28:02+00:00

Tuned Liquid Column Dampers (TLCDs) are passive control devices implemented in buildings to reduce the structural response of the controlled system when subjected to dynamic environmental loads. These devices consist of U-shaped tanks containing a liquid, usually water, where the oscillating motion of the fluid in the tank columns is used to generate inertial forces that counteract the motion caused by the excitation, thereby dissipating the incoming energy into the system. These devices have been the focus of research in recent decades and have attracted the attention of the scientific community interested in finding reliable, simple, and economical mechanisms to reduce the effects of dynamic loads on civil structures. Thus, this research aims to develop and evaluate the performance of an optimal control project based on the operation of a TLCD installed on the top floor of a mid-rise building excited by different seismic records. For this purpose, a metaheuristic algorithm known as Teaching-Learning Based Optimization (TLBO) is employed to execute the process of selecting optimal parameters for the control device, maximizing the effectiveness of the controller in reducing the overall response of the controlled building. The results obtained allow to establish that the implementation of TLCD in the structure leads to a significant reduction in the structural response of the building, highlighting the efficiency of the device in mitigating displacements during seismic events.

Model Updating in Dynamic Finite Element for Damage Detection on an Aircraft Wing

2024-12-12T13:33:02+00:00

SHM is a fundamental area for aerospace engineering. Within this broad area, there are non-destructive ways to assess integrity. This paper presents an approach to damage detection through optimization of a finite element model, where the design variables are the characteristics of the sections forming the components of the structural system, and the objective function is the dynamic parameters: natural frequencies and modal shapes. This allows for the detection of damage that caused alterations in the modal parameters of the structure through an optimal combination of design variables that generate responses obtained in the modal analysis of the damaged structure once the model is calibrated. The practical application used is damage detection in a simplified model of an aircraft wing.

Nonlinear dynamic analysis of prestressed cable structure under random aerodynamic loading

2024-12-12T13:36:59+00:00

Abstract. This paper includes the development and dynamic analysis of a mathematical model of an elastic prestressed cable structure such as those used in light roof structures known as tensile structures in which the external loads are balanced by tensile forces in the cables. Due to the light weight of this structural model the aerodynamic loads are critical and determine the design.
The model consists of four same length and section cables arranged in an X-shape in a planar view, fixed at one end, with an equivalent mass of the system in the center node, their other extremity. The cables are not in a plane: two opposite cables have their supports in the same positive vertical height, and the other two opposite cables have their support in the same negative vertical height.
There are forces acting on the central node in the x, y and z directions modeling random aerodynamic loading simulated by a Monte Carlo-type procedure inspired by Prof. Francos Synthetic Wind Method. This technique involves creating several loading series combining different harmonic components with amplitudes and frequencies obtained from an adopted PSD (Power Spectrum Density Function) with randomly chosen phases. This results a large number of response displacements and tensions to be statistically treated to render sound engineering design decisions.
The model admits large displacements so that a nonlinear dynamic approach is adopted. A numerical step-by-step finite differences time integration scheme is also implemented.

Nonlinear linear dynamics and numerical analysis of a sloshing tank

2024-12-12T13:42:25+00:00

Sloshing motion in liquids refers to the phenomenon of oscillation or agitation that occurs when a liquid is subjected to movement or disturbance. This can happen in containers, tanks, ships, or any other object that contains liquid and is subject to movement, such as acceleration, deceleration, turning or tilting. These oscillations can be caused by several factors, such as sudden changes in speed, changes in the direction of movement, winds, waves, or even internal movements of the liquid due to its own inertia. Sloshing can have significant effects in different contexts, such as naval engineering, liquid cargo transportation, storage tank projects, among others. Therefore, the study of sloshing is important to ensure the safety and stability of structures that contain moving liquids, as the forces resulting from these oscillations can affect structural integrity and even lead to accidents if they are not properly considered and controlled. Mathematical models and computer simulations are often used to predict and mitigate the effects of sloshing in different applications. Thus, this work investigates a mathematical model that describes a tank coupled to an electric motor, and therefore we determine the parameter space of the Lyapunov Exponent, basins of attraction, bifurcation diagrams and phase maps. These numerical analyzes are important to determine the range of parameters that diagnose chaos in the system.

Reliability analysis of space debris mitigation strategies using the Monte Carlo process

2024-12-12T13:47:46+00:00

In light of growing space exploration, the risk of collisions involving satellites, rockets and the International Space Station has increased significantly due to the significative number of space debris (objects in orbit that are no longer useful). In this scenario, several public and private organizations have developed strategies to mitigate this problem. The CBERS-1 satellite, launched in 1999 in a Brazil-China collaboration, is still in orbit, despite being decommissioned in 2003. This study aims to evaluate the effectiveness and reliability of various mitigation strategies that could have been implemented during the decommissioning of CBERS-1, using the DRAMA (Debris Risk Assessment and Mitigation Analysis) program and the OSCAR (Orbital Spacecraft Active Removal) application, which uses the Monte Carlo method. The objective is to ensure that CBERS-1 re-enters the Earth's atmosphere within a period of 25 years, meeting the ESA (European Space Agency) space debris mitigation requirements. This work contributes to understanding and improving space debris mitigation practices in the context of increasing activity in space.

System identification of a lead-acid battery based on experimental data

2024-12-12T13:50:16+00:00

This paper aims to identify a battery model using experimental data obtained from the discharge of a lead-acid battery. In particular, obtaining a representative mathematical model for the system is important to accurately determine the electrical characteristics of the battery and analyze its discharge behavior during use. Additionally, the model is extremely useful for the design of the Battery Management System (BMS), which consists of an electronic circuit that manages the rechargeable batteries and at the same time protects the circuit from operating outside its safe operating area. Regarding the functioning of lead-acid batteries, although there are complex chemical reactions and laws from physics that can be employed to describe the system dynamics, mathematical models obtained from identification techniques can be an alternative to modeling and understanding their behavior. Even though there are simple models to more sophisticated models, the degree of complexity of the model will be determined by the application for which it will be used. In this sense, this work presents the identification of an electrical model for a lead-acid battery from data gathered. Jackey's model was adopted to represent the battery dynamics, since this model, in addition to having the parameters modeled as resistive and capacitive elements and being well suited to the experimental data, offers the advantage of not presenting a high level of complexity. Furthermore, it is intended to extend the methodology applied to obtain a Matlab/Simulink model that simulates the energy generation and storage system from a photovoltaic system. In this work, experimental data are sampled for different battery discharge rates using the Arduino. Then, the optimization tools of Matlab environment were used for system identification. The objective is to apply the optimization techniques to obtain the parameters of Jackey's model. Finally, according to the results obtained, the mathematical model identified is representative of the system, and, therefore, the tool is a viable alternative for the mathematical modeling of lead-acid batteries.

The Application of Monte Carlo Simulation and Finite Element Method in Structural Reliability of Aircraft Wing Structures

2024-12-12T13:56:37+00:00

The aerospace industry increasingly demands performance and efficiency, therefore ensuring the structural integrity of aircraft components such as wings is crucial. In this context, reliability analysis methods offer a more robust assessment than classical deterministic approaches, once those consider the uncertainties present in the system. This work aims to determine the probability of failure of aircraft wing structures through the Monte Carlo Simulation (MCS), treating material properties and applied loads as random variables. Different profiles of wings were modelled in a computer-aided design (CAD) environment and their geometries were exported to MATLAB®, where the limit state function was evaluated using the finite element method (FEM).

A micromechanical approach to effective elastic properties of fiber-reinforced fractured cementitious materials

2024-12-13T12:16:14+00:00

A micromechanical model is formulated in this work to predict the effective elastic properties of fiber-reinforced fractured cementitious materials. Fractures refer to a region of small thickness, along which mechanical and physical properties of the material are degraded. Unlike cracks, fractures are discontinuities able to transfer stress and, therefore, can be regarded from a mechanical viewpoint as interfaces endowed with a specific behavior under normal and shear loading. The presence of fibers enhances the post-cracking strength of cementitious materials due to the bridging effect of the fibers and improves their ductility. The present work employs a micromechanical approach to formulate the homogenized elastic behavior of fiber-reinforced fractured cementitious materials. In the context of Eshelbys equivalent inclusion theory, the approach makes use of the Mori-Tanaka scheme to estimate the homogenized elastic moduli. Fractures and fibers are modeled as oblate and prolate spheroids endowed with appropriate elastic properties. Particular emphasis is given to the situation of a cementitious matrix reinforced by aligned or randomly distributed fibers with randomly distributed microfractures.

A preliminar study on RVE homogenization for phase-field multiscale analysis

2024-12-13T12:22:01+00:00

Despite the phenomenological approach presents excellent results in material behavior analysis, real-world materials are inherently heterogeneous. A material is considered heterogeneous when, at a particular observation scale, it becomes feasible to discern multiple mixture phases within it. This level of observation is commonly referred to as the microscale, where interactions between constituents occur, ultimately leading to the emergence of cracks.
Modeling a material at the microscale begins with defining a Representative Volume Element (RVE), which is the smallest part of the material that is large enough to statistically represent the entire mixture. This ensures that other samples of the same size exhibit similar properties with minor variations. The analysis of the RVE leads to obtaining the effective properties of a portion of the material. That process is called homogenization.
Modeling a RVE can be a challenging task, as it requires the use of highly refined meshes to accurately capture the geometric representation of all mixture components. Therefore, phase-field models present themselves as a suitable choice for this type of modeling, once due to the intrinsic features of its variational formulation, they already need refined meshes and do not present localization effects.
Thus, the objective of this work is to model a heterogeneous RVE and obtain its homogenized properties. This homogenization of the material parameters is fundamental for the upscaling operation of multiscale analyses.
All implementation were done in INSANE, an opensource software developed by the Engineering Structures Department (DEES) of Federal University of Minas Gerais (UFMG).

Experimental and numerical study of damage mechanisms in cementitious materials reinforced with twisted steel fibers

2024-12-13T12:25:47+00:00

This study proposes to investigate damage mechanisms in the fiber/matrix interface, considering the use of twisted steel fibers incorporated into conventional and high-strength cementitious matrices. The methods employed include fiber pull-out tests and X-ray tomography for the detection and analysis of microcracks in the interface region. Additionally, elastoplastic finite element models will be developed, integrated with contact formulations, using the commercial software ABAQUS. Validation of the numerical models will be performed by comparing the characteristics of damage propagation obtained through microCT images with the simulated results.

Exploring the Influence of Heterogeneity on Determination of a RVE for Concrete Structures

2024-12-13T12:30:12+00:00

The mechanical behavior of a heterogeneous material is strongly influenced by the response of its constituents (and their respective interactions) at lower scales. This fact accounts for the nonlinearities observed at the macroscale, and consequently, the challenges in formulating constitutive models capable of providing accurate predictions in a practical application context. Essentially, there are two primary ways to represent a heterogeneous material, either through Phenomenological Models at a Single Scale or through Multiscale Models. Multiscale models represent the most robust approach to depicting a heterogeneous material. In these models, the connection between macro and meso levels is typically made through the concept of a Representative Volume Element (RVE). The RVE is the smallest sample of the material that can statistically represent the mechanical behavior of the material. Typically, in multiscale model applications, it is assumed that an RVE exists and that its size is initially prescribed. However, the appropriate determination of an RVE for quasi-brittle materials remains a subject of study. This paper discusses the determination of RVEs for concrete using normalized graded aggregate curves. For this purpose, numerical simulations were performed using the Finite Element Method, employing constitutive models based on Phase Field theory. Throughout the study, issues related to the size of the RVE and the
determination of ergodic properties are discussed. The influence of the aggregate gradation curve on the mechanical behavior of the RVE and the influence of the aggregate-mortar interface are also examined. Finally, the difficulties encountered in determining the RVE in a practical application context are presented.

Machine Learning based Analysis of RVE in Concrete Structures

2024-12-13T12:33:46+00:00

In the numerical modeling of structural elements, particularly utilizing the finite element method (FEM), multiscale models represent the most robust approach for analyzing heterogeneous materials such as concrete. These models incorporate information from multiple scalestypically, macroscopic and mesoscopicto more accurately capture the material's response and its impact on structural behavior. In this context, each material point in the numerical model is associated with a Representative Volume Element (RVE), which is the smallest statistically representative portion of the material. During the analysis of a multiscale model via FEM, each integration point in the model requires the execution of an independent computational model that simulates the RVE and is processed in parallel to the main model (on the fly process). Deformations originating from the macroscale are applied to the mesoscale models, and the responses obtained are then reintegrated into the macroscale. This approach results in significant demand on processing resources and time, which can limit its practical application in large-scale projects or situations requiring rapid responses. This article propose the representation of the RVE through a Machine Learning model (ML) capable of simulating the mechanical behavior of the material. This approach eliminates the on the fly processing. Throughout the text, examples of RVEs represented by ML models are presented, and their specificities are discussed. Finally, the advantages and disadvantages of this methodology are examined.

Parametric study of combined tensile and shear-frictional damage models on the simulation of mesoscopic compressive failure in concrete

2024-12-13T12:37:00+00:00

One approach that provides a more realistic numerical prediction of concretes mechanical behavior is the use of a mesoscopic scale, considering the different phases of the composite. To represent the non-linear material behavior, appropriate constitutive models must be employed, such as non-linear elasticity, damage or plasticity, among others.
A Mesh Fragmentation Technique that places high aspect ratio interface elements between the regular mesh elements, delineating the potential crack paths, has been employed to model the complex crack propagation process in quasi-brittle materials such as concrete. Recently, an extension of this technique introducing a two-layer condensed interface element has been proposed. This two-layer element allows to describe compressive failure as a combination of debonding (mode-I) and sliding (mode-II) cracking, so that each layer is respectively ruled by tensile and shear-frictional constitutive damage models.
One advantage of the proposed model is that it requires a reduced number of material parameters: tensile strength, fracture energy, cohesion, friction angle and shear softening. A parametric study aiming to evaluate the role played by each one of the parameters on the mechanical behavior of concrete is presented. A series of mesoscale uniaxial compression tests is simulated and the obtained predictions are compared to the correspondent experimental results. The influence of each parameter is evaluated in terms of the resulting average stress-strain curve, as well as the qualitative aspect of the specimen failure, described by the cracking patterns. This parametric study contributes to determining which parameters are more influential in the combined material failure, providing insights for future structural members simulations using the proposed technique.

Ablation study of a non-intrusive data-driven surrogate model for the Rayleigh-Bénard convection problem

2024-12-16T19:35:22+00:00

Non-intrusive data-driven models are promising class of methodologies to build surrogate models for challenging parametric engineering problems. POD-DL [1,2], a method from this class uses deep neural networks as the main data-driven ingredient. Following a first linear dimensionality reduction, based on a POD basis, it applies a second nonlinear dimension reduction, in this case a deep autoencoder, and a nonlinear regression using a forward neural network to account for the temporal and parametric coefficients.

This setting generates a large number of hyperparameters, such as the number of modes of the POD basis, the number of layers and amount of neurons per layer for each network (the autoencoder one and the regression one), besides all typical hyperparameters of neural networks, as learning rate, batch size, etc. This all impacts the amount of time for the training process and the surrogate model accuracy.

Based on our previous experience with this methodology for coupled transport-fluid problems, we decided to study the Rayleigh-Bénard convection problem [3] with a fixed Prandtl number, a well documented heat transfer problem coupled with fluid flow. Besides the temporal character of the problem, the Rayleigh number serves as a parameter, i.e., each different number generates a different dynamic that is learned by the surrogate model. Then, the regression neural network can predict the dynamics for an unseen Rayleigh number. In order to understand the contribution of each component of the method, we perform an ablation study in this controlled setup.

[1] - M. Cracco et al., Deep learning-based reduced-order methods for fast transient dynamics, Arxiv Preprint 2212.07737, 2022.

[2] - S. Fresca and A. Manzoni, POD-DL-ROM: Enhancing deep learning-based reduced order models for nonlinear parametrized PDEs by proper orthogonal decomposition, Comput. Methods Appl. Mech. Engrg., 2022.

[3] - R. Kessler, Nonlinear transition in three-dimensional convection, Journal of Fluid Mechanics, 1987.

An information-theoretic Machine Learning for upscaling and downscaling of uncertainty stochastic reservoir

2024-12-16T19:39:21+00:00

This work brings together theoretical formulation and computational strategies for upscaling random heterogeneous media. In this context, heterogeneous means multiphysics models at different scales and correlated random parameters at different locations in the physical domain, such as Stokes-Brinkman flow and fractures at the microscale and heterogeneous Darcy flows at the macroscale when the target problem is hydrocarbon reservoir simulation, or a matrix with random inclusions on the rich scale and a homogeneous matrix on the poor scale when the target problem is solid mechanics. The approach uses information-theoretic machine learning methods to extract relevant probabilistic information from the rich scale and adaptively control the stochastic distance between the responses of the two scales. A goal-oriented upscaling procedure is defined to ensure equivalence between poor targets and rich scales for specific outcomes and its generalization to a multi-goal-oriented mathematically sound response, where users control distinct accuracies of specific target responses. Preliminary applications for elliptic and transient equations are presented with their respective results comparisons. Applications use a series of realizations of rich-scale parameter distributions, producing a reduced number of equivalent poor-scale realizations as required by the user's desired accuracy. The full formulation requires solving a difficult optimization problem for an extended Lagrangian formulation which is solved with a new Parallel Deterministic Annealing. The mathematical formulation is such that parallelization is done over realizations, so the overall cost of calculating stochastic upscaling is of the same order as deterministic. Furthermore, a regression with Tikhonov regularization in linear Machine Learning was used to interpolate and extrapolate data from Parallel Deterministic Annealing in order to find an optimal rich scale.

Improving accuracy of parametric surrogate model for turbidity currents using diffusion-based super-resolution

2024-12-16T19:42:06+00:00

Turbidity currents are a sort of density-driven flow carrying particles that are generated between fluids with small density differences. They also are a mechanism responsible for the deposition of sediments on a seabed. A deep understanding of this phenomenon may help geologists on strategic knowledge in oil exploration. We simulate such currents using a stabilized finite element formulation in a Eulerian-Eulerian framework.

This brings the challenge of a high computational cost for the evaluation of the high-fidelity model. We thus use a surrogate model composed of one linear (Proper Orthogonal Decomposition) and one non-linear (Autoencoder) reduction [1,2]. Once the surrogate is trained for a set of parameters with data generated by the high-fidelity model, one can use such a surrogate model for predicting the dynamics for unseen values of the parameter.

Denoising Diffusion Probabilistic Models (DDPM) [3] is the method behind SOTA generative AI algorithms with very good performance in tasks like super-resolution. Based on such usage of diffusion for generative AI, the authors in [4] developed a framework for flow field reconstruction using a super-resolution task. Such a diffusion model is trained only using high-resolution data, without a pairing between low and high-resolution data, common in other techniques in the area.

The present work aims to use the dataset of high-fidelity parametric simulations of turbidity currents for training both the surrogate and the diffusion model for the super-resolution task. The goal is: using the trained super-resolution model, improve the fields predicted by the reduced model for unseen points of the parametric space.

[1] - M. Cracco et al., Deep learning-based reduced-order methods for fast transient dynamics, Arxiv Preprint 2212.07737, 2022.

[2] - S. Fresca and A. Manzoni, POD-DL-ROM: Enhancing deep learning-based reduced order models for nonlinear parametrized PDEs by proper orthogonal decomposition, Comput. Methods Appl. Mech. Engrg., 2022.

[3] - J. Ho, A. Jain and P. Abbeel, Denoising Diffusion Probabilistic Models, arXiv: 2006.11239, 2020.

[4] - D. Shu, Z. Li, A. Barati Farimani, A physics-informed diffusion model for high-fidelity flow field reconstruction, Journal of Computational Physics, Volume 478, 2023

Machine Learning aided Phase-Field Method in Constitutive Modeling of Concrete Structures

2024-12-16T19:45:42+00:00

Phase-field modeling has emerged as a promising approach for modelling crack propagation. Different from Griffiths theory, which deals with discrete cracks, phase-field modeling transforms cracks into diffusive entities that propagate within a defined region, regulated by a length scale parameter. This methodology introduces a phase-field variable as a novel nodal degree of freedom, governed by an additional equation integrated into the model. This variable quantifies the damage of the material at each point, with zero representing intact material and unity indicating complete damage.
However, the practical implementation of phase-field modeling presents significant computational challenges. Its requirement of very refined meshes makes the process computationally expensive. In this context, machine learning techniques can be used to simulate the constitutive model and ensure that the process enhance efficiency. The article aims to use the machine learning technique to train a neural network capable of simulating the constitutive behavior of a phase-field model. The validation of this approach will be carried out by comparing its results with those obtained through finite element numerical analysis. All simulations will be conducted using the INSANE software.

Physics-informed neural networks approach for one-dimensional beams

2024-12-16T19:49:24+00:00

Physics-informed neural network (PINN) is a machine learning technique where the physics of the problem is embedded into the loss function. The straightforward approach is to define the loss function using the problem governing differential equations and its boundary/initial conditions in a sort of collocation method. In general, the hyperparameters of neural networks for each problem at hands are defined via a grid search-like procedure, or simply by trial and error. In this paper, the application of PINNs is illustrated for one-dimensional beam problems, and the influence that the network weights initialization procedure has on the training is investigated. The code was built using SciANN, a Python package that uses TensorFlow and Keras for scientific computing and physics-informed deep learning employing artificial neural networks.

Piecewise Dynamic Mode Decomposition of Fluid Flow Simulations

2024-12-16T19:52:10+00:00

The computational simulation of fluid flows over structures still is a major research area in fluid mechanics. Because of the multiscale nature of many of the application models and consequent large amount of data, these simulations are computationally expensive, but can benefit from modern Reduced Order Models and data-driven methods. In this work, Dynamic Mode Decomposition (DMD) and its recent variation, Piecewise DMD (pDMD), are presented and compared in terms of dynamic modes extracted from the data, accuracy in reconstructing an approximation for the original dataset as a reduced order model and, most importantly, computational cost. The pDMD method is shown to be a variation of the traditional DMD that aims to improve and overcome some of the caveats of the standard version. This variation consists in decomposing the entire data into smaller datasets and applying a linear mapping independently on each one of these subsets instead of calculating a global linear fitting. Basically, it is an application of multiple DMD on small subsets instead one DMD over the whole data. Piecewise DMD is a simple and elegant idea that is based on the "divide and conquer" approach well known in the numerical analysis literature. Even though pDMD is new and should be carefully and extensively tested, it can be considered as a promising improvement over the standard DMD. The preliminary results presented in this work show how DMD can capture the dynamics and accurately reconstruct the simulation data and how pDMD can provide more accurate results when traditional DMD reaches its limitations, capture the specific dynamics of different stages of transient flows, and reduce the computational cost by 90% for a two-dimensional flow over a cylinder when compared to standard DMD. Future applications of Reduced Order Models using both DMD and pDMD include future state predictions, computationally cheap parametric simulations, and qualitative dynamic analysis of fluid flows.

Uncertainty quantification analysis in porous media using differential evolution McMC method with selection (DESk)

2024-12-16T19:55:40+00:00

Reservoir rocks display high spatial variability hydraulic properties. In general, this variability can not be deterministically described, and therefore, geostatistical methods come into place to approach the problem from a stochastic perspective. In particular, Markov chain Monte Carlo methods are often used on those applications. The most significant difficulty in using McMC methods for flow problems in porous media is related to the large stochastic dimension of the fields, which leads to low acceptance rates. Adaptive McMC methods have been a strong ally on this matter. Among them, differential evolution-based Markov chain Monte Carlo methods showed promising results. These methods exchange information among multiple chains running in parallel. Thus, improving its acceptance rate is not something as well explored in the literature. Additionally, to reduce the stochastic dimension of the problem, neural network techniques have become pretty popular as an alternative to using classical Karhunen-Loève expansion (KLE) to generate permeability fields. This work generates the proposed fields through variational autoencoders (VAE). A novel differential evolution Markov chain Monte Carlo with selection mechanisms (DESk) is proposed for solving a Bayesian inference problem involving a single fluid flow in a heterogeneous media. The scheme combines the faster convergence characteristic from the DE, which is improved by selection steps. The results showed that DESk performed better than the standard DE strategy for different selection pressures.

A compliance-based topology optimization approach using conservative convex separable approximations and PSB Hessian estimation

2024-12-17T13:27:19+00:00

In topology optimization, methodologies for updating design variables, such as the widely-used Optimality Criteria (OC), play a pivotal role in efficiently addressing problems with monotonically decreasing objectives subject to certain design constraints. However, despite its effectiveness, the OC method is derived from first-order optimality conditions. These conditions may not fully capture the nuances of more complex optimization problems, potentially leading to suboptimal or inefficient solutions. In this work, we use conservative convex separable approximations (CCSA) of the objective function, alongside with a PSB method for estimating the diagonal terms of the Hessian matrix. Three variations are considered: quadratic, logarithmic, and square-root approximations. This approach aims to enhance the efficiency and effectiveness of objective minimization in topology optimization problems subject to a volume constraint. To demonstrate the efficacy of the aforementioned methodology, several case studies are presented and evaluated using both the OC method and the CCSA update scheme. The obtained results and performance metrics are compared, providing clear evidence of the advantages offered by the proposed approach.

3D Topology optimization considering multiple loading

2024-12-17T13:30:27+00:00

Topological optimization looks for determining the ideal material distribution within a design domain (2D/3D) in order to optimize structural performance following imposed design constraints. This material distribution can vary continuously, resulting in complex shapes that are lighter than the original structure and take better advantage of material strengths. Incorporating multiple loads into topology optimization increases the complexity of the problem, as it requires simultaneous consideration of different types of loads and their interactions with the structure in problems that have several degrees of freedom. This can include the analysis of load combinations due to self-weight, other load combinations or even dynamic or thermal loads. This work aims to develop and implement a 3D structural topological optimization model that takes these multiple loads into account using MATLAB program language. Practical examples of optimization cases considering multiple loads are presented, as well as comparisons with existing results in the literature, in order to demonstrate the accuracy of the proposed algorithm.

Applications of topology optimization considering physical nonlinearity

2024-12-17T13:32:30+00:00

Topology optimization is a powerful computational tool that assists designers in determining efficient structural configurations. In civil engineering, most applications are still limited to the field of theoretical/computational analysis. This limitation restricts the scope and applications of topology optimization concepts for practical problems. Extensive research has focused on topology optimization using isotropic material with linear elastic behavior. However, there is a paucity of studies comparing linear and nonlinear material behaviors, highlighting a research gap in result analysis and structural application fields. For concrete structures, in particular, there is generally a deeply nonlinear behavior, including effects such as cracking, creep, and shrinkage. Therefore, it becomes a challenge to realistically optimize this type of material. This study investigates the applications of topology optimization for evaluating the structural behavior of beams considering the physical nonlinearity of the material. Using the ABAQUS® software and the SIMP method, a finite element numerical analysis is conducted to determine the density distribution in a design domain. The obtained results of the optimized models are compared, and it is observed that the presence of plastic deformations influences relevant aspects of structural behavior. This study contributes to the dissemination of the use of nonlinear constitutive models, highlighting the potential of the concept of optimization-assisted design.

Exploring Topology Optimization in Geotechnical Engineering

2024-12-17T13:34:56+00:00

Despite recent advancements in utilizing topology optimization in geotechnical engineering design, practical applications primarily focus on simple foundation design. In the view of this, this study aims to explore the application of topology optimization methodology to various geotechnical design problems. The optimization takes place in a finite portion of the soil, modeled via Finite Element Method (FEM) which is coupled with the rest of the semi-infinite soil, modeled via Indirect Boundary Element Method (IBEM). The optimization is carried out considering a linear bi-material interpolation through the three field Floating Point Topology Optimization (FPTO) method. Numerical results for the optimized foundations of plates, bridges and linings are presented and discussed.

Geometrically Nonlinear 3D Topological Optimization: An Efficient MATLAB Code for the SESO Method

2024-12-17T13:37:09+00:00

The study of Topological Optimization (TO) in three-dimensional structures with geometrically nonlinear formulation is scarce. This work aims to apply TO in elasticity problems extended to consider geometric nonlinearity, using the total Lagrangian formulation. To achieve this goal, we developed a numerical model in MATLAB, employing the finite element method with hexahedral elements. We used the TO method Smoothing Evolutionary Structural Optimization (SESO) in conjunction with the Method of Moving Asymptotes to accelerate the optimization procedure, especially in the calculation of sensitivity factors. SESO is based on a bidirectional heuristic, systematically removing and adding elements with lower compliance compared to the maximum compliance of the structure. The results show that Smoothing - Evolutionary Structural Optimization Geometrically Non-Linear (SESO-GNL) is robust and efficient in solving classic problems from the literature.

Investigation of the structural behaviour of non-conventional beams designed using a Topology Optimisation procedure

2024-12-17T13:39:14+00:00

In this research we use topology optimisation to design statically determinate rectangular beams with different heights. For the sake of simplification, the constitutive material is assumed to be homogeneous. The aim is to verify the efficiency level that topology optimisation procedure has in removing material from the structural member still preserving the bending strength capacity. Topology optimisation is based on the Bi-directional Evolutionary Structural Optimisation (BESO) and Solid Isotropic Material with Penalisation (SIMP) methods. To use the SIMP method, a 3D parametric model of the beams was implemented in the Rhinoceros3D (Computer-Aided Design) software with the aid of the Grasshopper (Algorithm-Aided Design) plugin. The optimization was performed using the tOpos plugin. For the BESO method, the BESO 2D code developed in RMIT Univervity was used. The output for both codes are compared, highlighting the coherence of the results based on computational time efficiency and physically plausible generated shapes. After Topology Optimization, the structural behaviour was investigated using Karamba3D plugin. To obtain the maximum load for the beams with different heights and their final volume coming from topology optimisation, an additional optimisation method based on genetic algorithms was adopted to maximise an objective function based on deformation. This analysis was performed for local maximum displacement respecting limiting state serviceability criteria considering increasing distributed load and different volume fractions. In all the cases analysed, the width and span are fixed. The results of the optimisation procedure for beams with different heights are compared based on economic-sustainability criteria (volume of material) and load-bearing capacity (maximum bearing moment).

Multi-material topology optimization of 2D structures using the SESO and SIMP method with reliability

2024-12-17T13:41:58+00:00

Topology optimization is essential for the efficient distribution of structural form within the desired design domain, ensuring that structural elements are positioned to resist the requested forces and the specific boundary conditions for which they were designed. Therefore, the main objective of the article is the multimaterial topological optimization of a variety of two-dimensional structural problems, based on literature benchmarks, such as Michell structures and the MBB beam. These problems are approached considering a multi-material perspective, to distribute different materials throughout the structure, thus seeking their optimal solution. The methodology was generated based on the use of the finite element method for structure analysis and computing techniques were implemented for multi-material topology optimization (M.T.O.), Smoothing-ESO (SESO), and Solid Isotropic Material with Penalization (SIMP) via MATLAB. Furthermore, a reliability analysis is incorporated to deal with uncertainties, using Reliability-Based Topology Optimization (RBTO) with the First-Order Reliability Method (FORM), dealing with the random variables involved, such as geometry, modulus of elasticity, volume fraction, compliance, and loading, such as normal and lognormal probability distributions. The results obtained show a satisfactory convergence between the two topological optimization methods studied, thus highlighting the potential for applying these techniques to various structures as an effective tool in the search for economic efficiency in structural design.

Robust topology optimization of trusses with automatic grouping of cross-sections

2024-12-17T13:44:26+00:00

The ground structure method is a topology optimization strategy that tends to generate complex structural solutions to structural optimization problems. One of the main causes of this complexity is the large number of different cross-sections present in the topologies optimized by this method, in which the solutions obtained often have dozens of bars with different cross-sections. This excessive diversity of cross-sections makes the solutions obtained impractical for the manufacture and assembly of real structures, which require standardized cross-sections for economic and constructive viability. Therefore, in order to improve the workflow during the design stage, we propose the development of a strategy that allows the number of cross-sectional areas available to be restricted during the optimization process. The proposed method acts independently of the number of members present in the initial structure and ensures that the optimized solution has a predefined number of cross-sections with equal areas. To do this, an initial optimization is carried out to obtain an ordered vector of optimized design variables with a higher tolerance. From this ordering, the groupings of members that will be associated with the same design variable are defined, which generates a new optimization problem with a reduced number of design variables. The material of the structure is again redistributed among the members and the new optimization problem is solved. Structures were optimized with a robust compliance minimization formulation that introduces uncertainty in the loading directions. This formulation naturally increases the complexity of the final structure compared to a nominal formulation. As a result, simpler topologies are obtained that benefit the construction process by reducing the number of elements with different cross-sections in the structure. Numerical examples are presented to demonstrate the efficiency of the strategy developed.

Topology Optmization Applied to Problems with Local Fatigue Constraints Based on Augmented Lagrangian Method

2024-12-17T13:46:20+00:00

Fatigue is the most usual failure mode of any mechanical structure subject to loading. There are several methods to predict the structure life, and different approaches can be applied to extend this life. From the point of view of materials engineering, new materials can be proposed to deal with this issue. However, developing and producing these materials can be expensive. A different approach consists of optimizing the design using some optimization algorithm, determining the optimized material distribution that ensures a higher fatigue life. This work proposes to use topology optimization to design structures subjected to permanent loads to increase the component life. The objective is to minimize the volume, considering fatigue constraints. The works in the literature deal with fatigue constraints using aggregate methods, which are common in problems considering stress constraints. Our proposed approach uses a norm of the stress field to represent the stress constraint. However, stress and fatigue are local phenomena. Thus, in this work, the Augmented Lagrangian method is used to deal with the large number of constraints in the problem. This approach, previously used in stress-constraints problems, makes treating fatigue as a local phenomenon. The Modified Goodman method is used to measure local fatigue. This method considers a sensitivity factor that accurately estimates fatigue life. Numerical examples show the efficiency of the proposed method.

Active suspension using a PID controller with an inerter device

2024-12-02T11:56:29+00:00

This article is dedicated to a thorough investigation of the behavior of an active suspension system that incorporates the PID controller in a vehicle quarter, adding an inerter component to the system. Through comprehensive analysis of a variety of track profiles, the active suspension system demonstrates its ability to precisely control wheel movements, with the primary aim of improving passenger comfort and vehicle handling. By using the PID controller in conjunction with track sensors, the system is able to continuously evaluate road conditions, identifying the most effective movements to optimize the driving experience. The PID controller, incorporating proportional, integral, and derivative components, plays a fundamental role in minimizing error, integrating corrections, and adjusting response time as needed. The inerter, an innovative mechanical device with two terminals, is introduced to provide inertia without adding mass to the system, utilizing the difference in angular acceleration between the terminals. To validate and compare the performance of the active suspension system with and without the inerter, detailed simulations are conducted using the powerful tools of MATLAB and Simulink. The inclusion of the inerter in the active suspension system, along with the PID controller, aims to enhance the overall effectiveness of the system, even if it results in a slight increase in manufacturing costs. However, the substantial benefits in terms of passenger comfort and vehicle safety fully justify this additional investment. This approach represents a significant advancement in the field of automotive suspension systems, offering an ideal balance between performance, cost, and user satisfaction.

Performance comparison of an Inerter Suspension

2024-12-02T12:54:13+00:00

Recent enhancements in automotive suspension systems have significantly increased vehicle safety, comfort, and dynamics. The inerter integration is an innovation, improving stability and comfort by dampening vibrations. As a two-terminal inertial element, the inerter creates a resistance force proportional to the relative acceleration between the terminals, quantified by the inertance constant in kilograms (kg). This research investigates the dynamics of a passenger vehicle using a 14 Degrees of Freedom (DOF) vehicle model that includes an inerter, alongside traditional springs and dampers. Comparisons are drawn between this comprehensive model and quarter-model and half-transversal car models. Employing VI-CarRealTime and MATLAB/SIMULINK for simulations, the study seeks to elucidate the enhancements in suspension performance attributable to the inerter across different road conditions.

Dynamic Modeling of Suspension with Air Spring

2024-12-02T12:44:30+00:00

The present work aims to model a ¼ vehicle semi-active suspension, using a combination of air spring and magneto-rheological damper. The modeling of the magneto-rheological damper will be based on the Wang model, which will be calibrated through experimental tests. The air spring model will be employed to compare performance between discrete mechanical models and the thermodynamic model. Various semi-active control strategies, such as bang-bang type skyhook/groundhook and PID, will be explored for comparison with existing selective passive systems on the market. The study of the air suspension with magneto-rheological damper will be evaluated from the perspective of comfort and drivability, following standardized parameters (ISO 2631:1978).

Passenger vehicle behavior modeled by Power Flow using different mathematical tire models

2024-12-02T12:50:41+00:00

Ground Vehicles can be approached as a set of integrated subsystems, with cause-effect relationships. Through the Power Flow Modeling approach, each of these subsystems can be interpreted as a black box, and interrelated with the others in a modular way, as long as causalities are respected. This work aims to take advantage of the modularity of the automobile interpreted as a set of integrated subsystems and evaluate the influence of mathematical tire models on its acceleration and braking behavior. Each of the subsystems is mathematically modeled in individual blocks that are then integrated, without loss of causality, in MATLAB/Simulink® software. The purpose is to provide a fully modular vehicle model, taking advantage of this Power Flow feature, in an open-source code. Furthermore, Inverse Problems are applied to estimate parameter values of the Burckhardt and Dugoff mathematical models in order to obtain similar behaviors of the corresponding tire model by the Magic Formula.

Distortional Strength and DSM Design of Cold-Formed Steel Lipped Channel Beams under Transverse Loadings

2024-12-16T19:58:16+00:00

This paper reported the results of an ongoing numerical (ABAQUS shell finite element) investigation on the distortional buckling, post-buckling and ultimate strength behaviours and DSM (Direct Strength Design) Design of cold-formed steel beams subjected to major-axis non-uniform bending due to one midspan point load (transverse applied load). The beams analysed consisted of single-span lipped channel members exhibiting (i) 15 geometries, (ii) end sections that are locally and globally pinned and may warp freely, (iii) triangular bending moment diagrams, and (iv) 8 yield stresses, selected to cover a wide distortional slenderness range. After acquiring in-depth insight into how the triangular bending moment diagram influences the beam distortional buckling and post-buckling behaviours, an extensive numerical (shell finite element) parametric study is carried out in order to gather significant distortional failure moment data concerning lipped channel beams. These failure moments are then employed to assess the merits of the available DSM beam distortional strength curves in predicting them, namely (i) the one currently codified in North America (AISI 2016) and (ii) those proposed by Martins et al. (2017). The above curves were found to be inadequate for providing safe and accurate predictions of failure moments, highlighting the need to continue developing an efficient and reliable DSM-based design approach for beams failing in distortional modes under non-uniform bending.

Local-distortional-global buckling interaction os lipped channel steel cold-formed columns

2024-12-16T20:02:46+00:00

It is well-established that axially loaded thin-walled steel cold-formed members are susceptible to elastic buckling. This has been a focal point of numerous research studies, leading to insights into various buckling interaction cases, including local-global (LG), local-distortional (LD), distortional-global (DG), and local-distortional-global (LDG) interactions. This investigation specifically focuses on the triple buckling interaction LDG, building upon the authors' previously proposed design solution for LD buckling interaction. The study was conducted using experimental and finite element method (FEM) column results, creating a comprehensive database to validate the proposed solutions. The first research step involved verifying the accuracy of the shell FEM model by calibrating with experimental results of lipped channel (LC) columns developing the LDG buckling. Once the FEM model's accuracy was confirmed, a parametric study was conducted to support the development of the proposed LDG design solution for LC columns. The proposed design equations adhere to the core principle of the direct strength method, capable of incorporating all single buckling modes (L, D, and G) and their combinations (LG, LD, and LDG). Comparisons were made using LRFD-based reliability analysis, which confirmed that the proposed solution is reliable, easy to apply, and aligns with the usual design principles and parameters found in current codes and standards for steel cold-formed structures. Additionally, DG and LDG design approaches from other authors are mentioned and discussed in the context of the findings of the present investigation.

Numerical analysis of circular hollow section bar with stiffened flattened ends

2024-12-16T20:06:47+00:00

Circular hollow sections are usually used in long-span roof truss systems due to the advantages they offer. One of the typology for connecting elements in such structures involves the flattening of bar ends, in order to provide a simpler and more economical connection. A new flattening typology called stiffened flattening is proposed, characterized by a non-flat geometry, with the creation of stiffeners in the lateral edges of the bar flattened ends. A theoretical, numerical and experimental study was carried out on the behavior of a plane truss composed of circular hollow sections, in which diagonal bars have stiffened flattening ends. The diagonal connecting system with the chord members uses connecting plates. The plates are welded to the chords and the diagonals are connected to latter through a single bolt. This work presents the numerical analysis of a circular hollow section bar with stiffened flattening ends subjected to compression. This is a study of the behavior of an isolated bar compressed from the truss, which corresponds to the most requested diagonal composed by circular hollow sections with stiffened flattening ends. The numerical analysis using finite elements method was developed through ANSYS software with the Parametric Design Language (APDL), in which parameters such as geometry, material, element type, definition of the finite element mesh, boundary conditions and application of compression loads are specified. A non-linear analysis was performed using shell element on the bar with stiffened flattened ends. The numerical analysis result satisfactorily represented the structural behavior of the isolated circular hollow section bar with stiffened flattening ends. It was possible to observe the buckling effect of the compressed circular hollow section bar and the effect of the axial load eccentricity due to the stiffened flattening of bar ends.

Web shear buckling capacity of a stiffened Z-purlin: reporting of experimental tests

2024-12-16T20:11:16+00:00

Over the last few years there was a growing demand for structural solutions with lower steel consumption in the design of portal frames. It is considered that cold-formed steel (CFS) represents a consumption of 30 to 40% of steel in the entire structure, due to its great applicability in roof systems. Purlins with Z-sections have capabilities to achieve greater spans than other sections due to the continuity provided by overlapping connections. Greater spans require higher sections, thus increasing the susceptibility to local buckling of the web when the purlin is subjected to bending. Therefore, there is the need to introduce web stiffeners with complex geometry, providing better structural performance to local buckling strength. However, this also introduces complex web behaviour in the presence of shear, as result it requires advanced analytical, experimental and numerical studies to assess the web shear buckling mode of failure of such sections. In this context, as a first incursion in this field, the authors report in this paper some experimental tests of a new stiffened web cold-formed Z-section in the Brazilian market aiming the web shear buckling mode of failure. Consequently, an experimental setup of simply-supported purlins with short spans under 3-point bending are carried out. The flanges were locked to investigate the structural behaviour of CFS under predominantly shear. The resistances are compared between experimental data and direct strength method (DSM) as prescribed in the AISI S100. The results were evaluated providing a rich understanding of the structural behaviour of the CFS Z-sections with stiffened web and complex geometry.

A low-cost system for continuous dynamic monitoring and autonomous data analysis using the Internet of Things and Machine Learning

2024-12-11T17:55:36+00:00

Structural health monitoring using the Internet of Things (IoT) is the latest tech-nique employed in the field of structural damage detection. Although conventional systems based on commercial sensors, such as piezoelectric accelerometers, pro-vide high accuracy, their high cost often limits their application. To address this is-sue, one possibility has been the development of strategies using low-cost sen-sors. However, there are several challenges to be addressed, such as the optimiza-tion of the low-cost devices to increase their reliability in reading and processing data, and the development of data storage and data transmission strategies, mainly for dynamic monitoring applications, which requires working with large amounts of data. In this regard, this paper presents the development of a low-cost SHM so-lution, which is able to collect, store, process and transmit vibration data to the cloud from an instrumented aluminum beam. For this purpose, a prototype is de-veloped using an ESP32 board, an MPU6050 triaxial accelerometer and a mi-croSD card. A completely low-cost system is adopted, where the data processing and availability of results to the final user is performed in the free version of ThingSpeak IoT platform from MathWorks. As a result, a fully automatic dynam-ic monitoring strategy able to collect, store and transmit raw vibration data to the cloud is developed. Then, the raw acceleration data is processed and analyzed in the cloud, where the Fast Fourier Transforms (FFT) are computed and visualized in quasi-real time.

Aspects of Identifying a Damaged Site of a Wind Turbine Blade Using Power Spectral Density (PSD) Signature Curves and Energy Correlation Referenced Distance

2024-12-11T17:59:08+00:00

The following procedure is based on the energy correlation distance applied to the PSD (power spectral density) signature curves. Each PSD curve is calculated from the measurements at a point in the structure. The energy correlation distance between a single PSD curve and the set of all PDS curves of the measurement mesh is a metric. This metric is called the energy correlation referenced distance. In this work, to increase the difference between a healthy site and a damaged site, frequency bands of PSD curves are used. Using the temperature compensation properties of the referenced distance, the results are computed for a wide range of temperatures and then an analysis is made considering the structural constraints. The data used comes from a composite wind turbine blade whose data is housed in a public repository.

Damage identification using Bayesian derivative method

2024-12-11T18:01:42+00:00

Structural Health Monitoring (SHM) is one of the most challenging topics in structural dynamic analyses. This challenging characteristic comes from several uncertainties related to boundary conditions, damping description, material properties, and unknown excitation inputs. In this regard, formulating damage identification strategies based on the Bayesian framework is a feasible alternative to conjugating prior information, computational models, and measured data. Nevertheless, building metrics based on comparisons between experimental and computational dynamic features of structure leads to difficulties in determining the likelihood model. In this context, the present work brings an approach for damage identification that considers a metric for the inverse problem, which contains information about the relative difference of natural frequencies. The lack of knowledge about the likelihood structure is tackled using the Approximate Bayesian Computation (ABC), where draws from the approximate posterior are obtained using the Sequential Monte Carlo Approximate Bayesian Computation (SMC-ABC). The feasibility of this approach is assessed considering data from an experimental set-up composed of an aluminium beam containing lumped masses at some positions. The present strategy estimates the position and magnitude of the lumped masses attached to the supported beam. The central role of these lumped masses is to simulate structural anomalies. The inference process considers uncertainties related to structural damping by calibrating several concurrent structural models whose differences reside in the model damping. Finally, the strategy provides the probability of each concurrent model at the end of the process.

Finite Element Model Updating using Bayesian Optimization Algorithm

2024-12-11T18:05:22+00:00

Structural engineering projects require reliable information about parameters of the designed systems that convey precise predictions about the behavior of the system under different load cases. These predictions are derived from numerical engineering models containing real structure geometry and parameters, resulting in responses using the well-established Finite Element Method (FEM). However, due to the presence of uncertainties and assumptions made during the construction of the model, the resulting response may not well represent the real structural behavior. Thus, the established approach involves supplying the numerical model with experimental data to reduce numerical-experimental error, improving the correlation between numerical and observed structural behavior of the system, in a process called Finite Element Model Updating (FEMU). Overall, engineers have developed many different approaches to solve this problem, mainly consisting of sampling or optimization algorithms, applying these methods in FEMU, damage detection, and optimization of sensor placement. The focus of this paper is on the implementation of the Bayesian Optimization Algorithm (BOA) to solve FEMU problems. BOA is a derivative-free optimization algorithm that aims to minimize the number of evaluations of the objective function by trading some computational resources for the construction and optimization of a cheaper auxiliary function, which evaluates the best point to evaluate next. This can be beneficial when heavy sampling of the optimization function can be very time-consuming or when limited evaluations are available, rendering sampling methods and some heuristic algorithms inefficient. To assess the behavior of the algorithm, many cases are analyzed from lower evaluation time to higher complexity cases and then compared with other methods, such as Bayesian Inference, Particle Swarm Optimization, and Genetic Algorithm. The first case is to optimize test functions, followed by some FEMU applications on an uncertain boundary condition beam and finally, a honeycomb plate, in which evaluation of the objective function is more expensive. Results show that BOA can attain good results in a short amount of time when applied to FEMU for low dimensionality problems compared with well-established methods. Overall, this paper reviews FEMU methods and proposes the implementation of a novel approach, demonstrating its effectiveness in solving model updating problems.

Identification of Single and Multiple Damage in Beams Using Natural Frequencies and Bayesian Data Fusion

2024-12-11T18:07:59+00:00

Monitoring the changes in geometric or structural properties of systems during their operation to evaluate the presence of damage is a well-established process entitled Structural Health Monitoring (SHM). It is one of the most widely discussed topics in mechanical, aerospace, and civil engineering, and exhibits an increasing importance in many other fields. SHM has a crucial relevance in determining the remaining useful life of a structure, which is essential in avoiding catastrophic failure. However, these analyses can be complicated and sometimes require destructive methods in order to achieve accurate results. Nonetheless, vibration-based methods have shown promising results as non-destructive approaches, relying primarily on variations of the modal parameters. In addition, previous studies demonstrated that natural frequencies are easily determined and provide great accuracy of results. The present work proposes the identification of single and multiple damages in beam-like structures using measures of natural frequencies. First, the beam is modeled using three different methods with increasing complexity. The first model is built in Ansys® APDL module with 100 elements using BEAM188 element type, and damage is introduced as a stiffness reduction in a particular element; the second model is constructed as a beam with solid elements, and damage is presented as a local reduction in stiffness; the third one is also built with solid elements, but with the damage mechanically introduced in the beam. The results for the natural frequencies are obtained via simulation. Then, an experimental setup is assembled in order to acquire results for the beam's natural frequencies and compare them to the values obtained via numerical analysis. These results are further processed by employing a Bayesian data fusion algorithm to predict the location of damage. Three possible damage locations are examined with varying intensities, ranging from a decrease in local stiffness from 10% to 50%. Different types of beam supports are also investigated. The results demonstrate that the algorithm successfully detects single and multiple damage and locates it with great accuracy under various types of supports.

Structural damage identification through machine learning approaches using FRFs

2024-12-11T18:10:51+00:00

In this paper, experimental tests and numerical simulations are conducted to evaluate the performance of different models for structural damage identification and quantification. For this purpose, an aluminum beam in Laboratory conditions is utilized as a test structure. Firstly, impact tests are performed to identify the modal parameters and frequency response functions (FRFs) of the healthy structure. Then,
different damages are induced in the beam by means of rectangular notches, and FRFs from each damage scenario are measured. Meanwhile, a simplified numerical model of finite elements of the beam is developed and calibrated with respect to experimental data. The calibrated model is used to generate a set of simulations representing the different damage scenarios induced experimentally. The damage is introduced in the numerical model by reducing the cross-sectional area. Normalized FRF amplitudes are used as the damage indexes. To increase the predictive capability of the models, uncertainties are introduced considering the FRF amplitudes as random variables. Afterward, different datasets are constructed and several well-established machine learning classifiers such as Decision Tree, SVM and KNN are trained to perform damage identification and quantification. Finally, experimental data measured on the damaged beam are used as input variables to evaluate the prediction capacity of the trained classifiers. Undamaged and damaged data are correctly classified by most of the classifiers. However, to quantify the degree of damage some shortcomings are found.

Continuous-discontinuous modeling of failure in micromorphic media

2024-12-05T11:56:07+00:00

Deformation and failure are typically developed at multiple scales for the majority of engineering materials. At the macroscopic level of observation, structural rupture is triggered by a localized failure that corresponds to a loss in the material continuity within a specific region of the body. This localized failure is preceded by microcrack coalescence that can be observed at lower observation levels. This study investigates the propagation of a discrete fracture within a continuum damage process zone within the framework of micromorphic media. The adopted generalized continuum theory is well suited for modeling microstructured materials and also recognized in the relevant literature for its regularization properties due to its non-local formulation. Microcracking prior to coalescence is represented by continuum damage models based on a recently proposed formulation for elastic degradation in micromorphic media. The propagation of a discrete fracture is based on the analysis of a generalized micromorphic acoustic tensor, which is here derived considering the concepts of acceleration waves. When instability is detected, a discontinuity is introduced by the Extended/Generalized Finite Element Method. The required implementations for the numerical investigation of the proposed model are conducted in the open-source software INSANE.

Damage detection in 2D beams using wavelet and boundary elements

2024-12-05T12:00:11+00:00

Damage detection in structures is crucial to prevent the collapse of structural elements. Research suggests using numerical methods to aid in damage detection in structures, typically based on finite element modeling (FEM) and comparisons of modal responses of structures before and after damage. This article proposes a new approach to identify damage using Wavelet Transform (WT) and Boundary Element Method (BEM), these methods can detect singularities present in displacement parameters caused by damage and, consequently, do not require the condition of the structure before damage. To validate the methodology, a simply supported and bi-supported beam with damage will be modeled using the open-source programs Bemlab2d and Bemcracker2d, along with an algorithm in Matlab language for manipulation of wavelet coefficients and damage localization. The results indicate that WT is a useful tool for identification and monitoring of structural damage.

Integrating mesh adaptivity and digital image correlation for full-field displacement evaluation of cracked bodies

2024-12-05T12:03:27+00:00

The study of crack initiation and propagation is primary to the fracture mechanics domain and essential for developing new materials. Such a study is relevant for refractory ceramics adopted as thermal insulators in high-temperature industrial applications. In particular, mechanical and thermal tests are essential in measuring properties and contribute to the material selection process. Such tests can be assisted using non-intrusive measurement techniques, in particular, by the Digital Image Correlation (DIC) technique, which enables to obtain full-field information concerning the displacement and strain fields in a loaded configuration. Identifying the crack location is a challenge for DIC techniques and requires special treatment of the correlation process to get reasonable resolution around the crack. Global DIC approaches can benefit from mesh refinement strategies to improve the identification of the displacement field and, consequently, the crack's location. In this context, the present article introduces mesh refinement strategies to improve the image correlation, allowing to identify the crack location in cracked specimens better. The adaptivity approach is developed using Correli framework and the Application Programming Interface (API) of the GMsh software, which has several features to control the element mesh size distribution, particularly by controlling mesh size parameters using strain and local gray-level residue. Herein, the mesh strategies are applied in a model composite system submitted to temperature variation. The composite consists of a brass inclusion surrounded by an alumina matrix. The thermal expansion coefficient mismatch between the phases leads to a radial crack pattern when the material is heated. The evaluation of the mesh refinement algorithm is established in terms of reducing global gray-level residual in the correlation procedure, and the enhanced definition of the crack location. The present article contributes to the DIC processing, getting more information on specific regions based on strain and gray level residual information, and also furnishes information to verify computational fracture mechanics tools.

Numerical Analysis and Validation of Fracture Toughness Factors using BEMCRACKER2D through Boundary Element Method

2024-12-05T12:08:57+00:00

Fracture Mechanics (MF) represents a complex domain in the study of materials and structures that exhibit flaws, known as cracks. Over the last century, we have witnessed progress in the development of studies related to MF, consolidating it with practical applications in the field of structural engineering, particularly in prominent sectors such as the naval and aerospace industries, where crack prediction is of paramount importance. However, given the inherent complexity of these challenges, there is an increasing reliance on the application of numerical methods, particularly the Boundary Element Method (BEM), to perform computational analyses of crack propagation, based on the principles of Linear Elastic Fracture Mechanics (LEFM). In this scenario, the present study conducts an analysis of fracture toughness factors, k1 and k2 comparing numerical curves derived from models found in the literature with those obtained through the implementation of crack propagation prediction criteria (such as Maximum Circumferential Stress, Maximum Potential Energy Release Rate, and Minimum Strain Energy Density), using BEM. To generate these curves, the software BEMLAB2D and BEMCRACKER2D were used, developed for modeling and analysis via BEM, respectively. The results obtained confirm the efficacy of numerical methods, demonstrating good convergence between the numerical curves from the literature and those generated by the applications. Among the prediction criteria, the Maximum Circumferential Stress method stands out as having the greatest correspondence with experimental results.

Numerical Modelling of Crack Propagation Using BemCracker2D Program and Comparison of Different Criteria

2024-12-05T12:12:10+00:00

In this study, we explore crack propagation through numerical modelling using the academic software BemCracker2D. Developed in C++ and based on object-oriented programming, BemCracker2D provides an intuitive graphical interface for modelling and mesh generation of boundary elements. Specifically designed for 2D analysis of problems involving cracks, the software employs the Dual Boundary Element Method (DBEM) to handle crack faces. Additionally, BemCracker2D supports a variety of crack propagation criteria, including the maximal circumferential stress criterion, the strain energy density fracture criterion and the maximal strain energy release rate criterion. These criteria are crucial for predicting crack behavior in different scenarios and situations. The software also allows for the calculation of Stress Intensity Factor (SIF), evaluation of fatigue life, analysis of crack coalescence, among other functionalities. By investigating crack propagation and comparing the results obtained with different propagation criteria, this study aims to enhance our understanding of crack behavior in materials. Insights derived from these analyses are essential for the development of more resilient and safe materials in a variety of industrial applications.

Phase-field modeling of hydraulic fracture interaction with natural fractures

2024-12-05T12:15:46+00:00

The problem of hydraulic fracturing has been the subject of several studies in recent years, including different proposals for analytical, experimental, and numerical models. This interest is justified by the complexity of the problem and its great relevance, with applications in various areas including the industrial, energy and engineering sectors. Several applications deal with natural reservoirs which are usually characterized by the presence of inclusions, heterogeneities and natural fractures, the latter being the subject of this study. These pre-existing fractures affect the circulation of the pressurized fluid inserted into the reservoir, influencing the path of the hydraulic fracture. The interaction between hydraulic and natural fractures generates complex fracture propagation patterns involving arrest, cross and branch phenomena between the cracks. In this sense, an interesting approach to modeling hydraulic fracturing is the use of phase-field models (PFM). Through its variational approach, the PFM is able to automatically deal with any number of cracks without restricting their shapes or trajectories and the crack path is obtained directly as part of the solution to the energy minimization problem. Therefore, this paper proposes a study of the interaction between hydraulic fractures and different networks of pre-existing natural fractures using a PFM that considers the pressure load on the surface of the hydraulic fractures. Numerical examples are presented to illustrate different possible interactions between the cracks and to explore different initial crack scenarios. All simulations were performed using the INSANE (INteractive Structural ANalysis Environment) software.

Simulation of cohesive fracture method in concrete structures

2024-12-05T12:18:29+00:00

The objective of fracture mechanics is to analyze the materials behavior and its failure modes applied to structures. Thereby, it is possible to identify the parameters that impact directly on crack evolution. Geometry, loading, and material properties are examples of crucial failure factors. There are some existing methods to analyze structural collapses, but the cohesive fracture is well known because of its efficiency, being used to calculate many different engineering materials. This paper uses the fundamental concepts of cohesive fracture to link experimental and numerical data. In other words, this paper aims to study two different concrete structures in which were applied cohesive fracture method and then compare the theoretical results with experimental ones. Moreover, some parameters such as crack position, width, thickness, and fracture energy, were defined by finite element analyses. In general, the obtained results show conformity between both simulations.

Defining the Best Strain Gauge Placement through Numerical Simulations of the Mechanical Behavior of the Modified-WOL Specimen

2024-12-05T12:24:20+00:00

In structural steels, cracks are an inevitable occurrence, demanding an examination of their ability to resist crack propagation under expected loads and various environmental conditions. The process of experimentally determining fracture toughness comes at a significant expense, involving the use of multiple specimens and extended testing periods, which hinders the swift acquisition of crucial parameters. An alternative approach entails the execution of a constant displacement test using the Modified-WOL specimen, which is equipped with an instrumented bolt for self loading. The primary objective of this method is to provide the Threshold Stress Intensity Factor for Environment-Assisted Cracking, utilizing only a single specimen. The incorporation of electronic instrumentation is essential for obtaining reliable, real-time data. Despite its importance, a consensus is lacking in the literature regarding the best location for sensor installation on the Modified-WOL specimen, potentially influencing its mechanical response. This study aims to explore the mechanical behavior of the three components constituting the Modified-WOL specimen test in accordance with the guidelines outlined by ISO 7539-6. Employing the Finite Element Method with two- and three-dimensional models, this investigation utilizes the Augmented Lagrangian method for formulating the contact regions. Additionally, quarter-point singular elements are employed to accurately represent stress singularity behavior at the crack tip. The numerical computation of fracture parameter (KI) is conducted using the Displacement Correlation Technique. Comparative analyses are then carried out between the numerical and the analytical values of KI determined based on the ISO 7539-6 standard. The findings demonstrate alignment with empirical literature values, ultimately contributing to the identification of the best location for strain gauge installation among the highlighted regions of considerable interest.

A numerical procedure to identify vugs and fractures in rock samples based on CT scan data

2024-12-06T13:29:37+00:00

This article introduces novel algorithms for fractures and vugs recognition in computed tomography (CT) rock images. The proposed algorithms can be used in both two-dimensional (2D) and three-dimensional (3D) approaches to accurately identify fractures and vugs within rock samples. A detailed explanation of the implemented method is provided, elucidating the underlying principles of the algorithms. Furthermore, the method's applicability is investigated through testing with various models of pre-trained neural networks.The study contributes to rock image analysis by introducing effective techniques for identifying fractures and vugs in CT scans that can be applied for geological and engineering purposes. In a demonstrative application, this methodology was implemented to generate a two-dimensional finite element mesh, thereby facilitating the simulation of the Darcy equation using the Finite Elements Method.

Assessment of reactive surface and kinetic parameters of basaltic rocks during CO2 storage

2024-12-06T13:45:49+00:00

Carbon capture and storage (CCS) is a novel technology that aims to reduce the presence of carbon dioxide from the atmosphere. This technology involves capturing CO2 from industrial sources or directly from the air, treating, transporting, and storing it in long-term safe rock formations. Basaltic rock comprises reactive minerals and glassy phases, which trap CO2 permanently through the mineralization mechanism. However, this method is complex mainly due to the rapid interaction between solid and liquid phases. The mineralization occurs at the interface between the reactive fluid and the basaltic rock surface, converting the dissolved CO2 into solid carbonate mineral that precipitates in the pores and fractures of the rock matrix. The reaction rate of a basaltic rock depends significantly on the CO2 wettability and rock-fluid interfacial interactions. However, there is limited information about the influence of the reactive surface on the reaction rate of minerals present in basalt formations. This work investigates the influence of kinetics parameters such as pH, temperature, and reactive surface area in the reaction rate of basaltic rocks. Basaltic rock dissolution and precipitation is assessed using the geochemical software PHREEQC. The proposed numerical model solves the reactive transport problem and provides feedback on the influence of the kinetics reaction parameters. The dynamics of the reactive surface during the reaction of basalt rocks is evaluated. The numerical results show the potential of basaltic rock for CO2 mineral storage as solid carbonates and identify the main factors that limit the mineralization process. Finally, this work provides a deeper understanding of CO2 mineralization that can provide valuable findings to guide Brazilian CCS projects.

Assessment of the uncertainties' impact of relative permeability curves on mature field oil production: a case study in unisim-i-h

2024-12-06T13:48:30+00:00

Relative permeability is a crucial parameter in reservoir characterization as it directly influences the behavior of the rock-fluid system and, consequently, oil production. However, estimating this parameter is difficult due to uncertainties that can originate from various sources, such as geological, parametrical modelling, computational, and so on. If not properly examined, these uncertainties might undermine prediction accuracy and impair final production. Over time, several correlations were created to estimate relative permeability better. Although no parametrical correlation can adequately predict the exact shape of the curve, most of them reasonably approximate it within specific uncertainty limits. For mature oil fields, a novel kind of industry for Brazil, the research of relative permeability and associated uncertainties is still in its early stages. The main objective of this study is to numerically investigate the effects of uncertainties on relative permeability curves via software CMG® and the geological model UNISIM-I-H developed by UNICAMP. The LET correlation was used to estimate the relative permeability curves. Initially, a base case known as UNISIM-I-H was simulated, upon which the remaining analyses were built. This case consisted of a 15-year production phase followed by a 5-year production pause, a 10-year production restart, the abandonment of the three less productive wells and the drilling of the three new wells to represent a mature oil field better. Four cases were created with relative permeability parameter uncertainties increased by 5%, 10%, 15%, and 20%. The effects of these uncertainties on the relative permeability curve, production curve, net product value, and recovery factor were then examined. The data analysis revealed that these uncertainties mostly affect the forecasts relating to net product value, reservoir recovery factor, and cumulative production, with the latter being the most impacted. Every uncertainty case increased the maximum and minimum values of the curves. Compared to the base case, an intriguing pattern also showed up, where the maximum increased much more quickly than the minimum, suggesting that the risk of estimating the values for each curve above the actual is significantly higher with increasing uncertainty than the opposite.

CO2 injection modeling in a reservoir: Phase transition study

2024-12-06T13:52:02+00:00

The study explores the phase transition of carbon dioxide from liquid to gas after injection and storage in a confined aquifer at a temperature of 30°C. By utilizing a compositional isotropic model and data from the NIST webbook (Linstrom and Mallard, 2024), the simulation analyzes, using compositional mesh model in tNavigator software (by Rock Flow Dynamics), the behavior of CO2 within a confined aquifer, seeking to identify the phase transition of the fluid. The effects of capillarity are neglected, and the main parameters of the reservoir are a pressure of 65 bar at the wellhead and a constant temperature of 31°C throughout the aquifer to evaluate the phase transition close to the supercritical point of CO2.
The analysis reveals that the drastic pressure reduction within the confined aquifer leads to the formation of free gas within the reservoir after the closure of injection wells, which becomes a problem, as occurred in the Ordos CCS Project in China, allowing fluid backflow during non-injection (CAI, Yuna et al.). The results showed that the closer the temperature approaches the supercritical point of CO2, the greater the probability of free gas formation within the reservoir.
Therefore, the conclusions emphasize the impact of the pressure reduction on the stability of CO2, which will undergo a phase transition from the liquid to the gaseous state, so that free gas is generated within the reservoir. In this way, it is highlighted the importance of understanding phase transition in CO2 injection processes for effective carbon capture and storage strategies.

Dimensionality Analysis of Unsteady-State Core-Flooding Simulations for Homogeneous and Heterogeneous Rock Types

2024-12-06T13:55:05+00:00

Model quality and computational resources must be carefully balanced in numerical simulations due to the high computational cost that three-dimensional models pose. This is inherently true in the oil and energy industry, where reservoir modelling and complex real experiments are required, in which inaccuracies have a direct impact on financial outcomes. Properly used, one-dimensional simulations yield significant technological and financial benefits by reducing simulation runtime, allowing more efficient operations, and faster and more accurate decision-making. As a result, wherever possible, models with lower dimensionality are preferred. This work aims to analyze the feasibility and effectiveness of the dimensional reduction of three-dimensional to one-dimensional models for unsteady-state core-flooding experiments. For that, 1D and 3D multiphase flow on porous media simulations were performed using the Black Oil IMEX software to verify the variability of oil production volume, saturation profiles, and differential pressure numerical responses. According to the results, the oil production volume and pressure differential are not affected by the dimensionality of the problem in homogenous cases. On the other hand, it is found that when dimensionality is reduced, heterogeneities lead to different outcomes in terms of pressure differential and oil volume production, which, in that case, may compromise dimensional reduction.

Evaluation of the Impact of Mineralogy On Oil Recovery Using Digital Petrophysics

2024-12-06T13:58:50+00:00

Exploring pre-salt oil deposits poses a significant challenge for the oil and gas industry. Carbonate rock reservoirs, being more susceptible to diagenetic actions, exhibit considerable complexity due to the heterogeneity of the porous system, making exploration activities in this scenario challenging. Microscale analysis of fluid behavior in porous media from X-ray microtomography images and petrophysical system analyses has become increasingly essential for enhancing techniques applied in this sector. To investigate the impact of mineralogy on oil recovery using desulfated seawater (DSW), two samples of coquinas from the Morro do Chaves Formation, Sergipe-Alagoas Basin, considered analogs to the coquinas of the Itapema Formation in the Santos Basin, Brazilian pre-salt, were utilized. Due to the depositional context of this formation, the coquinas from the Morro do Chaves Formation contain terrigenous minerals, primarily quartz, in their composition. This study aims to understand how different percentages of these terrigenous minerals associated with carbonate minerals can influence reservoir oil recovery. For this purpose, 3D image analyses obtained by micro-CT at different saturation phases: dry, water-saturated formation, oil-aged, and at various contact times with DSW were employed. To confirm observations acquired through images, the contact angle of the system was measured, where samples aged in oil came into contact with recovery water. Image analyses were conducted using profiles of both porosity and fluid saturation present in the pores. As a result, indications were observed that terrigenous minerals influence rock wettability. The sample containing higher percentages of these minerals demonstrated an affinity with oil, while the other, lacking these minerals, exhibited water-wettability. Different interpretations, however, could be identified: desulfated seawater did not benefit oil recovery, as the sample with a high content of terrigenous material showed the highest efficiency in removing residual oil; another interesting aspect found in this sample was the tendency for gas entrapment, as the percentage of pores filled with air remained practically constant during the process.

Modeling and inversion of petrophysical properties using Monte Carlo method in coquinas of the Morro do Chaves Formation (Sergipe-Alagoas Basin)

2024-12-06T14:02:45+00:00

The discovery of large accumulations of hydrocarbons in the reservoir coquinas of the Pre-Salt section of the Santos Basin has created a demand for research focused on characterizing the petrophysical properties of these rocks. However, obtaining rock samples in the Pre-Salt involves considerable complexity and costly logistics. The coquinas of the Morro do Chaves Formation in the Sergipe-Alagoas Basin (SE-AL) are considered a potential analog to the reservoir coquinas of the Pre-Salt. Therefore, they are used to understand the depositional, diagenetic, and facies processes that affect the characteristics of these rocks. The data used in this research were geophysical well logs: sonic transit time (BHC) and compressional velocity (Vp), as well as laboratory rock data such as grain density (GrainDen), porosity (PhiLab) and permeability (PermLab). These data belong to LAGESED-UFRJ and come from well 2-SMC-AL drilled in the Atol Quarry, located in the city of São Miguel dos Campos (AL), SE-AL Basin. The lack of continuous well logs prevent the application of a flowchart to characterize carbonate rocks along the well. Therefore, modeling and inversion methods were employed using the total density of the samples to estimate density and porosity logs at depth. The main objective of this study was to estimate the coefficients - a, b, c - of Gardner's (1974) polynomial equation, which would result in an adequate fit between the density data obtained in the laboratory and the observed density data, achieved by employing the Markov chains Monte Carlo method (MCMC). This statistical technique is used to simulate complex systems and make numerical estimates in order to determine the probable distribution of the coefficients and the predicted densities with the associated uncertainties. After obtaining the coefficients, it was possible to estimate a density log (MonteCarlo) over the interval of the analyzed well, and subsequently, this log was used to estimate the porosity log (PhiDENmc). Additionally, the Wyllie et al. equation (1956) was used as an alternative method for estimating the porosity log (PhiWyllie) from the sonic log. Finally, these porosity logs estimated (PhiDENmc and PhiWyllie) were correlated with PhiLab. It was possible to observe that PhiDENmc showed the best fit with the porosity data measured in the laboratory (PhiLab).

Numerical modeling of fault damage zones and their impact on EOR applications

2024-12-06T14:08:02+00:00

Geological faults are present in several regions in subsurface. For conventional reservoir engineering in the oil and gas industry, such faults are considered as impermeable surfaces responsible for reservoir compartmentalization. However, seismic and field observations show that faults are not surfaces but volumes composed by two regions: the fault core and the damage zone. While the fault core accounts for the fault sealing, the damage zone can have different impacts for fluid flow depending on the geological structures present around the fault. Porous host rocks such as sandstones are prone to trigger deformation bands which can significantly reduce the permoporous properties of the rocks, acting as barriers for fluid flow. On the other hand, stiff rocks with reduced porosities are prone to develop fracture networks in the damage zone, creating preferential flow paths. Therefore, the consideration of fault damage zones and their corresponding properties are important for reservoir modeling in order to develop suitable production strategies, in particular for enhanced oil recovery. In this kind of applications, water is injected into the reservoir aiming at raising both the reduced reservoir pressure and the oil production. In this study, we consider a three-dimensional reservoir model that includes a water injection well, an oil production well and fault damage zones between the wells. Then, different scenarios are analyzed considering the fault damage zone composed either by deformation bands or fracture networks using equivalent continuum approaches. For such purpose, power-laws based on deformation band density and fracture intensities around the fault core are used to define the permeabilities corresponding to the damage zone. The numerical results show that the presence of the damage zone generated around a normal fault changes the water propagation speed, affecting the oil recovery efficiency. Furthermore, the obtained results also contribute for a better understanding the dynamic behavior of flow through these geological structures.

Permeability estimation from rock digital images segmented through deep learning

2024-12-06T14:11:11+00:00

An accurate estimation of permeability is very important for the development and management of petroleum reservoirs. Knowledge of petrophysical properties is essential to achieve profitability in production in the oil and gas (O&G) industry. Modeling of flow properties at pore scales has gained great prominence in oil industry projects with the advances achieved with digital transformation. From digital images of reservoir rocks, it is possible to extract information from the porous system, in order to obtain petrophysical properties such as porosity, permeability, and, make suitable the comprehension of the connectivity of this system. The feasibility of acquiring three-dimensional images of these rocks, the industry began to use machine learning tools to assist the rock characterizations, thus, the entire modeling process is more efficient. And with high-performance computers, both the optimization and expansion of porous network have led to increasingly real flow calculations, which contributes to the knowledge of these properties. The objective of this research is to estimate the absolute permeability of rocks using micro tomography (microCT) images segmented using deep learning. It was used 12 samples of coquinas from the Morro do Chaves formation (Sergipe-Alagoas Basin), these samples are similar to those from the Itapema formation (Santos Basin). The images, with 42-micron resolution and in gray scale. Data were separated into training, validation and testing. Each batch of training images has 32 sub-images with 64x64 pixels (patch) and the stride ratio equal to 1. It was used 100 learning epochs with an early stopping criterion. The model used for segmentation will be U-net convolutional neural network with cross entropy as cost function and Adadelta ([1]) optimization algorithm. Additionally, sensitivities were made regarding the use or not of the data augmentation technique and also regarding the use of input images with and without denoising filters. Deep learning models were generated in the Dragonfly program ([2]), and the modeling of the pore network, using the PNM algorithm (Pore Network Modeling).

[1] Zeiler, Matthew D.. Adadelta: an adaptive learning rate method [Online] Available: https://doi.org/10.48550/arXiv.1212.5701
[2] Dragonfly: commercial software [online] Available: https://dragonfly.comet.tech/

Sensitivity Analysis of Relative Permeability on Unsteady-State Core Flooding via Experimental Data

2024-12-06T14:16:24+00:00

The use of computational reservoir simulation plays a key role in understanding fluid flow in geological formations, enabling the development of advanced models and accurate predictions. These simulations rely heavily on parametric constitutive relations to represent essential properties such as relative permeability (Krel), which is required for modeling continuous-scale multiphase flow in porous media. However, the majority of models described in the existing literature contain numerous empirical parameters that must be determined. Regardless of how complex their parameterization is, these parameters have no direct relationship to the problem's underlying physics. As a result, there is a need to estimate these parameters and regularly assess the associated uncertainties. Nevertheless, achieving satisfactory uncertainty quantification requires a preliminary investigation into sensitivity and linear dependence, a step that is often overlooked, especially in the context of core flood experiments. Given this issue, this study aims to analyze the reduced sensitivity coefficient of relative permeability parameters, parameterized using the LET model, in unsteady-state core flooding experiments, considering both bump and no bump conditions, while also taking into account the capillary pressure parameterized via LET. In these experiments, a plug saturated with oil undergoes axial water injection at one end, resulting in oil (and water after breakthrough) being produced at the opposite end. Experimental data includes the pressure difference between the water inlet and the oil (and water) outlet, along with the accumulated volume of produced oil. Based on experimental data, computational simulations were conducted using the Cydar® software to optimize the relative permeability and capillary pressure. The dynamic behavior of the relative permeability parameters' local sensitivity is showcased, alongside their dimensional comparison.

The evaluation of heterogeneity variations on flow simulations applied to 3d scal models

2024-12-06T14:20:13+00:00

Heterogeneities within reservoir cores significantly influence fluid flow behavior, potentially causing premature rupture and distorting experimental outcomes. Neglecting to account for these heterogeneities when incorporating relative permeabilities into reservoir simulation models can render such models non-representative of real field conditions, thus impacting field performance predictions. Predicting behavior resulting from random heterogeneity distributions becomes challenging. Therefore, it is crucial to mitigate these effects by studying local heterogeneities to better understand their influence at larger scales. This study leverages CMG®, a well-established petroleum reservoir simulation software, to model lithology based on outcrop data. Synthetic heterogeneous plugs were simulated under various scenarios to assess their impact on flow parameters during SCAL experiments. Both single-rate and experiments with multiple flow rates were conducted on 3D plugs. The analysis focused on heterogeneity variability, examining net production and pressure differentials. Additionally, the study investigated how heterogeneity affected experiments with varying flow rates. The results highlight notable impacts observed through spot analysis of plugs representing smaller regions. Experiments with multiple flows demonstrated greater sensitivity to heterogeneity compared to prolonged experiments with a single flow. These findings suggest that such influences would be exponentially amplified in large oil fields, as supported by the presented data

A Multi-Objective Ant Colony Optimization for Routing in Printed Circuit Boards

2024-12-05T13:40:17+00:00

Automatic routing for Very Large-Scale Integration (VLSI) and Printed Circuit Board (PCB) design is an important tool to facilitate and optimize the work of engineers. Such a tool is typically provided by popular Computer-Aided Design (CAD) software and is a long-running research field. As electronics technology evolves and both discrete and integrated components get smaller and faster, the constraints to design circuits become more complex and new challenges arise. To deal with these difficulties, strategies using computational intelligence algorithms are employed to provide viable routing solutions in a timely manner. Within these strategies, multi-agent and swarm algorithms are highly relevant, being frequently applied alongside other approaches or by themselves. In this paper, we introduce a variation of the typical Ant Colony Optimization (ACO) algorithm modified to perform PCB routing, focusing on length matching between traces. The PCB area is divided into a grid that represents the search space for the algorithm. For each trace, the initial and final positions are known and contained within a cell of the grid. The routing of each trace is performed by an individual ant colony. The ants of a colony must travel from the initial to the final position of a trace to find the route that better fits the constraints of a multi-objective function. An ant in a cell can only move to neighboring cells. The number of movements it makes represents the length of the route. The algorithm consists of three steps. First, colonies and data structures are initialized. In the second step, one iteration is performed; the ants of each colony find a route to a trace. In the third step, the results found by the ants are evaluated, and the pheromone trails for the colonies are updated. The pheromone trails are updated based on a function that simultaneously minimizes three objectives: trace length, the number of times that traces cross with each other, and the length difference between traces. In other words, the ants try to find the shortest possible trace that has the same length as the other traces without crossing with them. Steps two and three are repeated until the maximum number of iterations is reached. We tested our algorithm in five fundamental scenarios and performed a statistical analysis on multiple executions of each scenario. The results obtained show that our algorithm is a viable approach to perform PCB trace routing with length matching.

Access Control with Facial Recognition: A Systematic Literature Review

2024-12-05T13:43:51+00:00

Counting people or even identifying individuals present in a given place is a fundamental task for public and private sectors and/or institutions that need to manage the access and permanence of individuals in certain places. This is not different at the Federal Institute of Education, Science and Technology of Mato Grosso do Sul - Campus Três Lagoas, which has a large physical space and only a few employees to control and supervise these facilities, which are shared by high school and college students, requiring more strict access control, especially in research laboratories. Several tools and methodologies have been proposed to meet this demand, including the use of DeepLearning, convolutional networks and a wide variety of facial recognition algorithms, which show great potential, as they are present in several solutions in the literature. The aim of this paper is to carry out a systematic review of the literature, broadly investigating best practices and success cases in using facial recognition to control people's access to environments. The review makes a significant contribution to those who intend to develop or research in this field, as it presents an overview and discusses what has already been tested and returned a good outcome and what did not generate a satisfactory result, as well as presenting the results of tests and proofs of concept carried out at the IFMS - Campus Três Lagoas.

Applications of the Circle-Inspired Optimization Algorithm: Comparison between MatLab and Python versions

2024-12-05T13:46:52+00:00

This paper presents applications of the Circle Inspired Optimization Algorithm (CIOA), a modern optimization algorithm developed by the authors, in optimization problems from different areas of study implemented in MatLab and Python, with the main objective of making a comparison between versions of each computer language. Different sets of optimization problems were selected, involving classical benchmark functions, traditional truss structural optimization problems, and real-world optimization problems obtained in the 'CEC2020 Real-World One-Objective Constrained Optimization Competition'. Each optimization problem was solved multiple times on the same computer in MatLab and Python, to make comparisons between the accuracy and robustness of each version of the algorithm, evaluating the best solution and the mean and standard deviation between several solutions. Furthermore, a comparison of computational time was also performed. The results obtained attest to the efficiency of CIOA in both computational languages. In terms of accuracy and robustness, it was not possible to clearly identify a better version (MatLab or Python) for CIOA, as the differences obtained in the results were, in most cases, very small, and may be caused by the random characteristics of the algorithm. In the comparison of computational time, the MatLab version performed better in most optimization problems. This fact may be due to the efficiency of the specific libraries used and the programming experience of the authors in each computer language.

Checking the coupling between overhead crane hook and steel ladle trunnion in Steelmaking Plant using convolutional neural networks

2024-12-05T13:51:33+00:00

Overhead cranes are equipment designed for the efficient and safe movement of large loads and are widely used in the industry. They play a very important role in logistics and production by allowing the flow of materials, machinery, and products from one location to another, whether within a factory, warehouse, shipyard, or any other industrial environment. These equipment have a simple mechanical structure, consisting of a main beam equipped with wheels that allow movement along tracks. A hoist is suspended under the main beam, which can also move along it, and is used to lift and lower loads. The element that couples the load to the lifting system varies according to the type of load.
In this article, we explore the coupling system commonly used in the steel industry for handling steel ladles through overhead cranes, called hooks and bails. This study proposes the use of artificial intelligence (AI) and machine learning techniques, through computer vision based on convolutional neural networks to detect the coupling, segmenting both the hook and the bail and thereby determining the precise alignment of the assembly before lifting. This contributes to validating the operator's visual information, reducing possible human errors, and promoting greater safety for both the process and the people involved.

Comparing Transformers and Linear models for precipitation forecast in Rio de Janeiro

2024-12-05T13:54:57+00:00

Precipitation represents a critical meteorological phenomenon that exerts a substantial influence on different geographic regions, as well as playing a fundamental role in various human activities. Notably, Rio de Janeiro experiences unstable weather conditions that lead to sudden and intense rainfall. Consequently, forecasting such precipitation patterns, particularly extreme events, is of fundamental importance in mitigating adverse impacts. Artificial Neural Networks (ANNs) present a promising path for predicting time series data, with transformer architectures emerging as an efficient option. Recognized for their versatility across diverse tasks, transformers have demonstrated effectiveness in time series forecasting, with the Autoformer model emerging as a standout performer, achieving state-of-the-art performance levels. However, the computational demands inherent in transformer-based models, including significant time and memory requirements, have led to the exploration of simpler alternatives. Linear models, such as DLinear, have been proposed as computationally efficient alternatives, capable of providing predictive performance comparable or superior to transformers. The objective of this study was to evaluate and contrast the predictive effectiveness of the linear model with the transformer-based approach in precipitation forecasting tasks for data from Rio de Janeiro. The dataset was obtained through the INMET meteorological system, covering historical records from 2002 to 2023, from four meteorological stations distributed in Rio de Janeiro, Brazil. When it comes to precipitation forecasting, the presence of data imbalance, particularly with regard to extreme events characterized by precipitation exceeding 25 mm, represents a significant challenge. In the scope of this work, the dataset was used in unbalanced form. To train the models, the dataset was partitioned into training (60%), validation (20%) and test (20%) subsets. Both models were instantiated with equal parameters, including sequence length and prediction length of 96, batch size of 32, 20 epochs, and utilizing EarlyStopping and ReduceLROnPlateau callbacks with a patience parameter of 3. The mean squared error (MSE) served as the primary metric for optimizing the loss function during training and evaluating predictive performance. Finally, the study seeks to evaluate the quality of models for predicting precipitation in the Rio de Janeiro region. By evaluating meteorological data, the study attempts to contribute to the understanding of models performance in precipitation forecasting tasks. Our analysis sought to demonstrate insights into which architecture to choose when it comes to precipitation with an unbalance dataset.

Data exploration: large language models in the construction of Knowledge Graphs

2024-12-05T13:57:34+00:00

Knowledge graphs (KGs) are graphical representations of structured information that illustrate the relationships between concepts, entities, or data. KGs play a crucial role in enhancing the performance of artificial intelligence systems and search tools. However, constructing knowledge graphs is a complex undertaking, requiring the assimilation of substantial amounts of data. One approach to building KGs involves utilizing Large Language Models (LLMs), which leverage artificial intelligence to comprehend and generate natural language. Hence, this study advocates for the utilization of an LLM model in KG construction. The proposed model utilizes artificial intelligence to identify the most pertinent subjects within a domain of knowledge (nodes of the KG) and establish the connections between these topics (edges of the KG). To achieve this, the Stable Beluga 2 model, fine-tuned on Llama2 70B, was employed. The execution of the model utilized the Petals architecture, a system designed for collaborative inference and fine-tuning of large-scale models by pooling resources from multiple entities. This facilitates the execution of large-scale models with reduced computational resources. The outcome of this endeavor was the development of an artificial intelligence model capable of generating knowledge graphs that serve various purposes, including summarizing concepts, identifying correlations between areas of study, and responding to inquiries.

Detecting Hate Speech on Brazilian Social Media: New Dataset and Analysis

2024-12-05T13:59:58+00:00

Social media plays a crucial role in human interaction, facilitating communication and self-expression. However, the proliferation of hate speech on these platforms poses significant risks to individuals and communities. Detecting and addressing hate speech is particularly challenging in languages like Portuguese due to its rich vocabulary, complex grammar, and regional variations. To address this challenge, we introduce TuPy-E, the largest annotated Portuguese corpus dedicated to hate speech detection. Through a comprehensive analysis utilizing advanced techniques such as BERT and GPT-2 models, our research contributes to both academic understanding and practical applications in this field.

Emergency callback prioritize

2024-12-05T14:03:10+00:00

The need for performance evaluation of Electric Power Distributors by the National Electric Energy Agency (ANEEL), focusing on service quality, measured through the percentage of emergency occurrences with Power Interruption (PNIE). In response to the challenges faced by distributors in efficiently managing emergency complaints, with attention to reducing services without power interruption. The main objective is to develop an advanced system that optimizes service, establishes precise performance metrics, and reduces operational costs. We have a system that enables analysis, identification, prioritization, and forwarding of occurrences to the teams. Done through the mobile dispatch system, which streamlines communication between operations center operators and field teams. Once the service is completed, it becomes available for the next processing stage, where the data is analyzed and transformed into continuity indicators, providing a detailed view of service performance. Performance evaluation was conducted through meticulously selected metrics, allowing comprehensive analysis of Fuzzy logic, considering the diffuse and uncertain nature of the data. Among these metrics, calculation of the average degree of relevance, analysis of degree of relevance variation, and identification of minimum and maximum relevance stand out, providing a complete and detailed evaluation of model performance. After the initial tool implementation, it was observed that the percentage of unproductive displacement remained on average 40.64% over 12 months. Additionally, a significant increase of 18% in the entry of emergency occurrences was noted, indicating satisfactory initial effectiveness of the tool. Although there is room for additional improvements, these results suggest that we are on the right track in our pursuit of service optimization and continuous process improvement. Finally, the first round of model testing and validation has already shown promising results, indicating significant potential to reduce the percentage of unproductive displacements in the company. Based on solid foundations and previous analyses, it is expected that the model will positively contribute to operational efficiency, being considered a strategy to optimize operations. We are committed to closely monitoring the results to make continuous adjustments and improvements to the system.

Evaluation of Tolerance Selection Strategies and Multifidelity Techniques in ABC Methods

2024-12-05T15:11:19+00:00

Approximate Bayesian Computation (ABC) methods provides a flexible and robust framework for solve model fitting problems, particularly pertinent to complex models with intractable likelihood functions. This methodology is based on approximating a simulated parameter values through auxiliary data and evaluating the distance of this data with the true dataset. Effective implementation of these methods require reasonable decisions to be made about the selection of ABC techniques and how to implement the algorithm to ensure computational efficiency. A comprehensive understanding of these factors facilitates a more accurate inference about the model. This study aims to explore the impact of the tolerance selection and the integration of Multifidelity techniques to the convergence and cost of the method. In the initial approach, three methods of choosing tolerances are employed: a predefined vector, a percentile calculation, and a percentage calculation based on the distance vector obtained from model simulations, in order to verify the most effective strategy for the improvement of the inference process. Subsequently, the optimal approach of tolerances selection is combined with Multifidelity techniques to reduce the computational cost. This methodology is applied in the examination of infectious disease models of differential equations. This study aims to highlight the importance of careful decision-making when using ABC methods, through the evaluation of some approaches for choosing tolerance in combination with techniques that aim to reduce the computational cost in constructing samples in ABC methods. Through this analysis, we focus our efforts on trying to demonstrate insights about gains in computational efficiency and accuracy in results.

Monitoring and diagnosis of cardiac anomalies in hospitalized patients using IoT and LSTM neural networks

2024-12-05T15:15:28+00:00

Continuous monitoring of patients in hospital settings is essential for preventing cardiac disease, representing a crucial measure to ensure the safety of hospitalized patients. However, current monitoring methods have significant limitations, such as patients only being monitored for short periods, which complicates the identification of changes in health status. This article presents a proof of concept for successfully implementing a continuous vital signs monitoring system using the Internet of Things (IoT), coupled with a Long Short-Term Memory (LSTM) neural network for detecting cardiac anomaly events.The development of the neural network hinged on a meticulously labeled database. This database, composed of 12-lead electrocardiogram (ECG) signals from 45,152 patients, was a labor of expertise. Collected at a sampling rate of 500 Hz, these data were labeled by experts, ensuring their high quality and reliability. This resource is fundamental for training machine learning models with high diagnostic precision, enabling accurate identification of cardiac rhythm patterns that indicate potential adverse conditions or those that deviate from a normal or stable electrocardiogram pattern. To make practical use of this extensive data, a robust system architecture was necessary to handle and analyze the data effectively.

Microcontrollers played a crucial role in our system, facilitating the transmission of data to a web server. This was achieved using the Message Queuing Telemetry Transport (MQTT) protocol, a highly efficient and fast method for message transmission. The MQTT server, acting as a central hub, received the information and distributed it to two destinations. First, it sent the data to the real-time monitoring site, ensuring immediate access to patient vital signs. Second, it forwarded the data to the system hosting the neural network model. In this environment, the model processed the information and promptly identified any irregularities detected in the data.The results demonstrate that the model achieved high precision in identifying these conditions, enabling the issuance of alerts and the implementation of preventive measures with a high efficacy rate. Such actions reduce patients' health risks, allowing real-time detection and remote communication of vital signs to healthcare professionals.

Multi-objective optimization of unconventional airfoils at low Reynolds numbers

2024-12-05T15:19:02+00:00

The widespread exploration of drones has generated increasing interest in Micro Aerial Vehicles (MAVs). Furthermore, an application that has gained notoriety is the use of aerial vehicles for exploration on Mars. Thus, the quest for efficient aerodynamic profiles for these applications has been intensified. These types of applications operate in a Reynolds number range from 10^4 to 10^5, which is significantly smaller than those commonly found in conventional low Reynolds regimes, such as when commercial drones are adopted. The main objective here is to identify more efficient shapes for airfoils, optimizing them through a multi-objective process aiming to maximize the lift coefficient and minimize the drag coefficient. To achieve this goal, two models of unconventional airfoils were optimized using the Generalized Differential Evolution 3 (GDE3) algorithm. The acquisition of aerodynamic coefficients, essential for evaluating the performance of the evolutionary algorithm, was carried out through simulations using Computational Fluid Dynamics (CFD). The method applied to describe the aerodynamic behavior of the structures proved to be consistent with experimental data. We used two base structures: a cubic Bézier-profile plate and a planar model with two inflections. Employing the aircraft's range or autonomy as decision criteria, it was observed that the cubic Bézier-profile plate presented superior results. Analyzing the graphs of the aerodynamic coefficients in relation to the angle of attack, the considerable increase in the stall point and lift provided by this model is notable. Such improvements, however, were accompanied by a slight disadvantage in the drag coefficient for small or negative angles of attack. It was also found that the evolutionary algorithm resulted in aerodynamic profiles with interesting characteristics for these applications when compared to existing models in the literature. In conclusion, the proposed cubic Bézier-profile plate model proved to be an interesting alternative for applications with a significantly small Reynolds number.

Neuro-Fuzzy: Multivariable Identification of a Pumping System with Variable Demand

2024-12-05T15:21:45+00:00

Water supply systems (WSS) comprise a set of equipment, works and services aimed at supplying water, covering domestic, industrial and public consumption. WSS face challenges arising from hourly variation in demand, influenced by society's consumption patterns. These variations cause fluctuations in system pressures and energy inefficiencies. As a way of analyzing this aspect, intelligent techniques were used to identify an automated WSS with variable demand for the development of computational models. Two multivariable and non-linear models were developed based on Artificial Neural Networks (ANN) and Neuro-Fuzzy system (NF). The objective is to enable simulations of operation scenarios, analysis, design and implementation of new intelligent control algorithms. To collect the data used in training and validation, experiments were carried out throughout the system's operating region. For cross validation, tests were carried out in operating regions different from those used for training. The models were evaluated using performance criteria, such as: Root Mean Square Error (RMSE), Normalized Root Mean Square Error (NRMSE), Final Prediction Error (FPE) and Adjustment percentage. The results were obtained using an experimental bench and showed adjustments greater than 99%. The cross-validation results evaluated with performance indicators show the superiority of intelligent models in comparison to parametric and mathematical models in the multivariable and non-linear identification of water pumping systems for simulation and dynamics prediction purposes.

On the Use of DELEqC-III in Bilevel Problems with Linear Equality Constraints

2024-12-05T15:25:50+00:00

The bilevel programming problem (BLP) is an optimization problem with another optimization problem in its constraints. This framework finds utility in modeling decentralized scenarios, which arise in real-world applications such as trafﬁc management, transportation, and economic policy. Differential Evolution (DE) techniques have emerged in literature for addressing such complex problems. However, handling linear equality constraints poses a significant challenge for DE and other metaheuristics. To address this issue, we previously introduced DELEqC, enhancing DE with a mechanism to manipulate the linear equality constraints. A specialized variant, BL-DELEqC, was further proposed specifically for tackling general BLPs. Another variant, DELEqC-III, transforms the original constrained optimization problem into a lower-dimensional unconstrained one, offering applicability to BLPs with linear equality constraints. Thus, we explore in this study the efficacy of DELEqC-III in handling BLPs with linear equality constraints. The proposed BL-DELEqC-III is compared to BL-DELEqC on a selection of benchmark BLPs, demonstrating superior results.

Predicting Blockchain Application Performance with Machine Learning Techniques

2024-12-05T15:28:36+00:00

Blockchain technology is a distributed ledger designed to record all transactions within its network, characterized by its decentralized nature, resistance to tampering, and attributes such as consistency, anonymity, and traceability. However, evaluating blockchain applications' performance can be complex due to their intricate and distributed infrastructure. This research employs machine learning model-based methods to predict blockchain systems' performance using predetermined configuration parameters.
The data used in this study is derived from a blockchain simulator, generating blockchain data to facilitate performance predictions. The simulation process involves using simulated data and configuration settings for each run, including parameters such as the number of nodes, the number of miners, consensus algorithm, maximum block size, and transaction quantities, among others. Output metrics such as the total number of blocks, transaction rate, block propagation time, and latency are utilized to assess network performance. The simulator was run 184 times with various configurations. Our findings indicate that the Random Forest model outperformed other models used in the experiments, achieving the highest R² scores for multiple metrics, such as 0.987 for total number of transactions and 0.765 for average block propagation time, while also demonstrating lower RMSE values, indicating more accurate predictions.

Simulation of working memory using neural field equations

2024-12-05T15:31:26+00:00

Neural field equations are intended to model the synaptic interactions between neurons in a continuous neural network, called a neural field .This kind of integro-differential equations proved to be a useful tool for the spatiotemporal modeling of the neuronal activity from a macroscopic point of view, allowing the study of a wide variety of neurobiological phenomena, such as the processing of sensory stimuli. In particular, they are a perfect tool for the simulation of working memory, which makes them very useful in Robotics.
The aim of the present talk is to study the effects of additive noise in one- and two-dimensional neural fields, while taking into account finite signal transmission speed.
A Galerkin-type method to approximate such models is presented, which applies the Fast Fourier Transformation to optimise the computational effort required to solve this type of equations. Numerical simulations obtained by this algorithm are presented and discussed.

Structural Damage Detection using the Circle-Inspired Optimization Algorithm

2024-12-05T15:34:01+00:00

This paper presents a novelty approach to vibration-based damage detection using matrix updating with the Circle-Inspired Optimization Algorithm (CIOA). The methodology is evaluated through numerical simulations of three structures: a 10-bar truss, a cantilever beam, and a Warren truss. In all cases, the systems are subject to ambient vibrations with varying noise levels to replicate inaccuracies in the acceleration signals. Furthermore, different analysis scenarios were considered, including single and multiple damages. The Data-driven Stochastic Subspace Identification (SSI-DATA) technique is employed to determine the modal parameters of these signals. Natural frequencies and mode shapes are compared under healthy and damaged conditions to identify the damage state through the methodology. The parameters of the optimization algorithm, CIOA, were set to θ = 97º and GlobIt = 0.90. In addition, a factor specific to the algorithm, the radius reduction factor, was reduced from 0.99 to 0.98 to accelerate convergence. The number of search agents and iterations varied according to the complexity of each structure. Considering all analyses for each scenario and noise level, the highest percentage errors in damage detection obtained were 0.163% in a multiple damage scenario with noise of 3% for the 10-bar truss, 1.453% in a multiple damage scenario with 5% noise for the cantilever beam, 3.600% in a multi damage scenario with 5% noise for the Warren truss. Therefore, results demonstrate the proposed approachs promise in identifying, locating, and quantifying single and multiple damages.

Tomato Detection and Classification by Color, Size, and Imperfections using Computer Vision

2024-12-05T15:36:52+00:00

Tomatoes stand out in agribusiness, as they are one of the most consumed vegetables in the world. There is a growing search for healthier foods and tomatoes are an important source of vitamins A, C and B1. Its production, handling and transportation are complex due to its sensitivity to the environment, pest attack, road conditions, among others. Consumer markets are increasingly demanding, with its quality as a decisive factor for purchases. The price is also one of the primary factors for the purchase by the customer, both the prices and the quality of the tomato take into account the size, color and quantity of imperfections that the fruit presents. The classification by size nowadays is done using a mat with holes of small, medium and large sizes and as the tomato fits in the mouth whose size best adapts it will fall into boxes with tomatoes of its respective size, however, on these mats it is not possible to check neither the color nor the imperfections. Another form of classification is by electronic equipment that is capable of verifying the size and color, but they are imported machines and extremely expensive, in addition to not detecting imperfections. The most common form nowadays is the manual one, where a trained person separates the tomato according to its size, color and imperfections, however, this form of analysis makes the classification process slow and subject to subjectivity. In view of this scenario and taking into account the numerous applications of Computer Vision in agribusiness, this work proposes to create a tomato classifier by color, size and imperfection, using computer vision.

Application of Q4 Strain Gradient Notation Finite Element Method (SGN-FEM) in Level Set Optimization Using Radial Basis Functions

2024-12-17T12:47:08+00:00

The Strain Gradient Notation Finite Element Method (SGN-FEM) employs physically interpretable polynomials in the development of finite elements, allowing for the precise identification and subsequent elimination of parasitic shear sources, which cause shear locking. The element is corrected a priori, during development, by simply removing the spurious terms from the shear strain polynomials.
The Level Set Method (LVM) is an optimization technique widely employed in topology optimization to minimize the compliance of structures. This method consistently provides clear boundary and geometry information during the optimization process, giving it inherent advantages in solving boundary and geometry-related problems.
While numerous studies investigate different approaches to calculate level set optimization, there are fewer studies evaluating how the finite element technique contributes to the analysis. Considering this, this paper presents the application of Q4 SGN-FEM in optimization studies using LVM to minimize the compliance of a two-dimensional linear elastic structure. The differences obtained when using the SGN-FEM model are investigated. The parametrized level set method, as defined in Wei et al. (2018), is utilized alongside SGN-FEM to conduct the study. The model is validated through comparison with other studies, demonstrating that SGN-FEM proves to be a viable alternative for conducting optimization studies using the level set method.

Dimensionality Reduction and Visualization for Structural Reliability Analysis using Artificial Neural Networks

2024-12-17T12:52:52+00:00

Structural reliability analyses may become very computationally demanding, especially when numerical simulations are employed to represent the structural behavior, and/or these analyses are used within structural optimization procedures. To overcome this problem, surrogate models have been largely used in the last decades, helping to avoid evaluations of the demanding parts of the computational code and to reduce the overall computational demand. However, the efficiency of the surrogates is usually compromised when dealing with high dimensional problems. In fact, high dimensionality imposes some difficulties not only to surrogate models but also for some structural reliability methods available in the literature. For these reasons, the present paper proposes to investigate the application of Artificial Neural Networks to reduce the dimensionality of structural reliability problems. A proper dimensionality reduction may help visualizing and understanding the problem and may assist surrogate models and reliability methods which would otherwise lose accuracy, precision and/or efficiency when applied to high dimensional problems.

Methodology for Reliability Analysis of Reinforced Concrete Structures over time Considering Combined Corrosion

2024-12-17T12:59:19+00:00

One of the main causes of deterioration in reinforced concrete structures (RC) is the corrosion of steel bars. Many factors, including materials, environments, and loading conditions, which often have uncertain characteristics, affect the performance of RC structures. Some uncertainties may depend on time and location, and associated reliability issues become more difficult to address. This study presents a comprehensive method for assessing the temporal reliability of reinforced concrete structures, taking into account combined effects of carbonation (general corrosion) and chloride penetration (pitting corrosion). Probabilistic models are used to capture uncertainties related to the beginning, propagation, and combined effects of corrosion on structural performance over time. The time-dependent reliability of bridge structures is evaluated using sophisticated numerical simulations in conjunction with the FORM method for reliability analysis. Both time and space variables are treated as uniformly distributed random variables within specific intervals when generating sample points. Engineers and decision-makers can assess the reliability of reinforced concrete bridges using a systematic framework that considers the complex interactions of corrosion mechanisms. This aids an informed maintenance planning and effective resource allocation to ensure long-term structural safety and durability. Finally, the suggested method is tested on a reinforced concrete bridge with corroded steel reinforcement bars. The original work is validated, and the results are compared with the crude Monte Carlo simulation (MCS) method.

Optimal Adaptive Importance Sampling for Reliability Analysis

2024-12-17T13:02:43+00:00

Reliability Analysis play a central role in Structural Safety. For this reason, several methods have been proposed and adapted to solve this problem over the years. In this work we focus on a family of sampling-based schemes called Adaptive Importance Sampling (AIS). The idea of AIS is to take an initial sampling distribution, draw a sample, evaluate the required statistical moments and then update the sampling distribution using some rule in order to make it closer to the target distribution. The procedure is then repeated iteratively until a good representation of the target distribution is obtained. In the context of Reliability Analysis, this idea can be employed to represent the optimal sampling distribution of IS and thus allow an accurate estimate of the probability of failure. There exist several variants of AIS, but all of them provide a sequence of samples obtained with a sequence of sampling distributions. If employed to evaluated statistical moments, as is the case of Reliability Analysis, it is then necessary to combine the estimates obtained at each iteration to get a final result. Generally, this is done by taking the average value among all iterations. However, in this work we reflect on better ways to combine these estimates in order to obtain the final result.

Performance-based design optimization of steel structures subjected to seismic actions

2024-12-17T13:05:10+00:00

Finding an optimal design for a structural system subject to seismic actions to minimize failure probability, repair costs, and injuries to occupants, significantly contributes to the resilience of buildings in earthquake regions. This research presents a comprehensive framework for the performance-based design optimization of steel structures, incorporating the Performance-Based Earthquake Engineering (PBEE) methodology delineated in FEMA P-58 [1]. A selected set of ground motions, consistent with the seismic hazard intensity of interest, and a nonlinear finite element model, established using OpenSees, enable the assessment of the system's dynamic response. To address the computational complexity related to evaluating the probability of failure of the system during an optimization iteration when using the PBEE methodology for assessing performance, this study introduces metamodeling techniques as a substitute for the original high-fidelity nonlinear finite element model. In particular, Kriging is employed to approximate both the median and standard deviation of the Engineering Demand Parameters (EDPs) in the design domain. The parameters of the Kriging metamodels are derived from nonlinear dynamic analyses performed using the original high-fidelity model and an optimal sampling plan obtained through Latin Hypercube sampling. Under the assumption of a lognormal distribution, the metamodel is then used to generate a large number of simulated demand sets necessary for the Monte Carlo procedure adopted by FEMA P-58 to calculate the distribution of probable losses for any given value of the design variable vector. Additionally, the median and standard deviation of the fragility function modeling collapse are also approximated by a Kriging metamodel, in which the parameters are derived from an Incremental Dynamic Analysis (IDA) for any given value of the design variable vector. The scheme is illustrated in a full-scale case study consisting of the performance-based optimization of the buckling-restrained braces of a steel seismic force-resisting system in terms of expected losses and construction costs. The study demonstrates that the proposed risk-based optimization scheme effectively balances construction costs with expected financial losses from earthquakes, thus enhancing the seismic performance of the system.

[1] Applied Technology Council, & National Earthquake Hazards Reduction Program (US). (2012). Seismic performance assessment of buildings. Federal Emergency Management Agency.

Protection of Columns in Buildings: against accidental impact, fire and progressive collapse

2024-12-17T13:08:03+00:00

Civil structures must be designed to withstand demands throughout their lifespan, ensuring adequate safety levels. However, accidental events, such as fires and vehicular impacts, present high uncertainty regarding intensity, location and occurrence probability, potentially exposing the structure's lack of robustness and representing significant risk. A column loss, for example, can trigger progressive collapse. To prevent disproportionate damage, reinforcements or safety devices can be used. However, traditional reinforcements can be expensive and impractical, especially in existing buildings. In this context, an optimized structural protection device is proposed for reinforced concrete columns, capable of inhibiting or reducing damage caused by impacts and fires and reducing the likelihood of collapse due to falling slabs. The device consists of cellular structures, known for their energy absorption and thermal insulation properties. Using multi-objective optimization techniques, compromise points that composes Pareto fronts are explored. Through case studies, these points are evaluated and promoted to optimal solutions in scenarios that require specific mechanical and thermal capabilities to ensure the columns integrity against the mentioned hazards, coupled with optimized material consumption. A cost-benefit analysis based on risk minimization is also presented, aiming to reduce expected failure costs and failure probabilities in adverse scenarios. Supported by positive results, it is concluded that of the cellular protection device emerges as a good alternative to traditional structural reinforcement techniques, standing out for its versatility, effectiveness, and potential for application with reduced costs.

Reliability analysis in the design of cold-formed steel built-up I sections by modified Direct Strength Method

2024-12-17T13:10:16+00:00

Cold-formed steel (CFS) framing is an economical and efficient structural solution, as it provides high strength and low self-weight. Built-up sections, formed by combining two or more CFS members, can reduce instabilities and obtain more versatility. An approach adopted in standards from several countries for the design of CFS bars is the direct strength method (DSM), which allows calculation of axial force from elastic buckling loads, considering global, local and distortional buckling modes. Currently, there are proposals to modify the DSM for the design of built-up sections, aiming to better fit experimental and numerical data. This study aimed to investigate these modifications of original DSM formulae by applying them to a database of experimental compression tests on built-up I, or back-to-back, sections. Using the database results, it was possible to calculate the professional factor (P), obtained from the ratio between experimental and theoretical results. To obtain reliability indices (β) related to theoretical methods, the professional factor was evaluated as a continuous random variable, according to data grouping by section type, failure type, and all one. The reliability index (β) was obtained using FOSM, FORM and Monte Carlo Simulation (MCS) reliability methods for load combinations from AISI S100 (LRFD and LSD) and NBR 14762.

Reliability Analysis of Serviceability Limit States of Beams in a Benchmark Reinforced Concrete Building

2024-12-17T13:12:50+00:00

The construction system of reinforced concrete entails inherent uncertainties concerning its execution method, as well as physical, chemical, and biological phenomena, along with the loads acting on buildings. Hence, understanding and characterizing random variables in designing reinforced concrete structures is pivotal for devising effective solutions that meet safety and performance requirements. In this context, limit state equations are employed for structural analysis and design, addressing different failure modes, while concepts of probability and statistics are utilized alongside reliability methods to ascertain the probability of failure and assess the structural integrity of the elements. Within this framework, this study endeavors to implement models for evaluating the reliability levels of reinforced concrete beams in a 2-storey building, considering the limit states of excessive deflection and crack width, and incorporating the effects of shrinkage and creep, according to NBR 6118:2023. The probabilistic assessment of the designed beams is performed by using the First-Order Reliability Method (FORM), whose results are validated and compared with those obtained through the Monte Carlo simulation method. The findings indicate a conservative design of the beams for the failure modes addressed, as the reliability indices are in line with values stipulated by international standards in most cases analyzed. Although this, some critical beams subject to higher loads approached the allowable limits more closely, presenting a narrow safety margin. This study aims to contribute to the advancement of integrating reliability analyses into reinforced concrete structural projects.

Reliability Analysis of the Simplified Punching Shear Resistance Model of Eurocode 2:2004 in Different Column Positions on Flat Slabs

2024-12-17T13:15:10+00:00

The use of coefficients in structural design is a strategy aimed at providing adequate levels of safety for buildings, avoiding excessive conservatism. The effectiveness of these coefficients depends on mathematical models that approximately capture the real behavior of the structure, considering the random nature of resistance and load variables. In this context, the proper definition of coefficients is even more crucial in resistance models that do not have an analytical formulation, such as empirical models. An example of an ultimate limit state whose model is empirical is the punching shear phenomenon, which occurs in flat reinforced concrete slabs. Despite the notable accuracy among normative models to assist in the development of these phenomena, some are based on simplifications that can result in high levels of conservatism or even insecurity when compared to more refined models. In EUROCODE 2:2004, there is the possibility of omitting the analysis of moments in the slab-to-column connection in punching shear design, considering only the axial force. For this purpose, a coefficient is applied to the applied stress to compensate for this simplification, depending on the position of the column in plan: corner, center, or edge. Therefore, this research aims to evaluate the reliability, through the First Order Reliability Method, of slab-to-column connections subjected to punching shear, using the EUROCODE 2:2004 simplification for design and employing an error model in the reliability analysis based on stress estimates derived from Fourier series. The research aims to assess whether the reliability indices of these connections demonstrate adequate levels of safety, using as reference the target reliability indices of other recognized standards, such as ACI 318 (2019) and CEB-FIP/MC (2010).

Reliability and sensitivity analysis of pultruded GFRP I-sections resistance to flexural and lateral-torsional buckling

2024-12-17T13:17:41+00:00

Civil industry demands increasingly for materials with outstanding properties and economic viability. In this sense, Pultruded Fiber-Reinforced Polymers (FRP) profiles are experiencing great acceptability and usage in civil construction as innovative structural elements. This is due to its lightness, excellent mechanical properties-to-weight ratios, cost-effective manufacturing process, improved durability and so many other advantages. However, despite the growing application of these materials, there are scarce efforts towards development of recommendations or design standards for FRP structures based on reliability concepts. Frequently in the design of FRP frames buckling phenomena governs the structural ultimate limit state design research, because of the high strength to stiffness ratio of this material compared to conventional ones. The present work evaluates a reliability and sensitivity analysis of global buckling ultimate limit state of I-section pultruded beams, aiming to capture the effect of uncertainties related to initial imperfections, material properties and loading in the structure reliability index, and its sensitivity to modeled uncertainties.

Reliability of built-up cold-formed steel beams designed by the direct strength method

2024-12-17T13:19:52+00:00

Built-up cold-formed steel (CFS) beams are composed of two or more sections that are joined together with welds, bolts or screws. Although PFF composite bars are commonly used in bending applications, the structural design of these sections requires further investigation. This study proposed a critical review of research related to the structural behavior and designing methodology of these elements. A review of published articles, encompassing experimental studies and numerical simulations of these elements, was conducted. The safety of built-up beams subjected to bending, designed according to the Direct Strength Method (AISI S100, 2016; NBR 14762, 2010), was evaluated and for the statistical study of the model error variable, beam test results obtained from literature were compared to the resistant capacities obtained by the direct strength method (DSM). The structural safety verification of built-up beams was performed using first-order reliability methods to assess the safety level for different load combinations. A calibration procedure for NBR 14762 (2010) was also presented, obtaining the resistance factor for a target reliability index.

Structural reliability analysis of a laminated plate using the Reissner-Mindlin model and the finite element method

2024-12-17T13:22:16+00:00

The use of anisotropic laminated plates as structural elements has become increasingly common due to their ability to emphasize desired mechanical characteristics and reduce undesired ones, based on the laminate stacking sequence.
Although the application of structural optimization methods to define the optimum laminate stacking angle is common in the literature, an analysis of the influence of this angle on the behavior of the plate and the approximate identification of its failure mode is relevant when seeking to increase laminate efficiency. In addition, taking into account the uncertainties that affect the structural response of these elements is still under development and open to discussion. Structural reliability is a suitable tool for dealing with these uncertainties.
This article aims to analyze the influence of the stacking angle on the probability of plate failure, taking into account the probability distributions of the variables involved. In order to make a comparative analysis, different Structural Reliability methods are adopted, such as FORM and the Monte Carlo method, and several failure criteria - Tsai-Hill, Tsai-Wu, Hoffman and Maximum Stress. The analysis is based on a case study of a laminated plate subjected to transversal static loading. The plate is considered to be made up of orthotropic laminae in oblique directions. The structure is modelled using the Finite Element Method, using the Reissner-Mindlin kinematic theory in the linear elastic regime. The aim is to verify and discuss the influence of the stacking angle on the level of structural safety of laminated plates.

System reliability analysis of cold-formed steel structures for serviceability limit states

2024-12-17T13:24:30+00:00

The adoption of numerical analyses in structural design practice has ensured greater control over the actual behavior of structures. Design-by-analysis approaches deviate from traditional methods by directly considering the load-bearing capacity of the entire system rather than individual element checks. These approaches can even incorporate inherent nonlinearities into the analysis, such as second-order effects, material inelasticity, geometric imperfections, and semi-rigid connections. These advanced analysis models may produce results closer to the actual behavior of the structure in service, enabling the safe utilization of lighter structural systems. In this context, the evaluation of serviceability limit states becomes relevant, particularly for cold-formed steel structures, which are typically assembled using slender elements. This paper presents the application of a reliability-based procedure to assess the compliance of cold-formed steel frames with serviceability limit state criteria for excessive lateral displacement. Considering two groups of cold-formed steel structures based on their functions: single-story building frames and industrial storage rack frames, the lateral drift limits are extracted from the AISI S100, ASCE/SEI 7, ANSI MH 16.1, and Brazilian NBR 14762 and NBR 15524-2 standards, along with the target reliability indices for the corresponding limit state. The subsequent step involves evaluating system reliability, considering typical load cases for these structures (dead and wind loads for single-story frames and dead and product loads for racks) selected from the mentioned specifications, accounting for the uncertainties in loads and in the material and geometric parameters of the steel members. For this purpose, a MATLAB reliability framework is presented, coupling the First Order Reliability Method (FORM) to the MASTAN2 finite-element package, in order to apply the structural analysis results in each evaluation of the limit state functions. Conclusions regarding reliability indices and the potential adequacy of resistance factors are presented.

A defect correction technique for the MPFA-H scheme in single-phase heterogeneous and anisotropic flow problems media

2024-12-03T11:46:36+00:00

The numerical simulation of fluid flow in porous media is a technical tool of fundamental importance in the oil industry and a significant challenge for numerical algorithms. Standard reservoir simulators use the classical Two-Point Flow Approximation (TPFA) technique to discretize diffusive fluxes. However, it fails to give proper results for complex reservoirs with highly anisotropic and heterogeneous media and does not allow the use of unstructured meshes. It is essential to adopt efficient numerical methods and computational strategies to overcome such limitations and optimize the numerical simulations of these flows. In this context, the cell-centered Multipoint Flux Approximation with Harmonic Points (MPFA-H) method is a robust and accurate alternative. Furthermore, enforcing the discrete maximum principle (DMP) is essential to avoid non-physical extremes, such as negative pressures or saturations. In our work, we investigated and implemented a slope limiting coupled with MPFA-H to impose these conditions. Finally, we evaluate benchmark problems extracted from the literature to verify our implementation.

A double-hybrid finite element formulation for Stokes flows using a divergence-free approximation space

2024-12-03T12:00:34+00:00

This paper presents a study of Stokes flows using a fully-hybrid finite element formulation. Incompressibility appears in Stokes differential equations as an additional constraint that enforces the velocity field to be divergence-free. A straightforward option to discretise those kind of problems would be to use a space of vector functions that includes the divergence-free constraint. When using standard De Rham compatible $H(/text{div},\Omega) - L^2(\Omega)$ spaces a scalar $H^1(\Omega)$ space is used as a Lagrange multiplier to enforce the divergence-free condition weakly. In recent developments, the research group at LabMeC developed $H(\text{div})$ approximation spaces derived from $H(\text{Curl})$ spaces whose divergence is constant. This work demonstrates that this pair, that also satisfies the De Rham sequence, can be used to approximate the velocity and pressure fields, respectively. This approach greatly reduces the number of global degrees of freedom. In previous work, $H(\text{div})$ spaces, which automatically guarantee continuity of the normal components, were combined with a Lagrange multiplier space to enforce the tangent velocity weakly. The Lagrange multiplier is associated with a shear stress applied between elements. In this contribution, a second hybridization is applied to the shear stress approximation, leading to a Lagrange multiplier associated with the tangent velocity. Condensing internal degrees of freedom leads to an element stiffness matrix that is positive definite with a single pressure Lagrange multiplier enforcing the incompressibility. Examples are presented to test and verify the developed numerical methodology.

A Treatment for Overlapping Fractures in the Context of Mixed Finite Elements for Flow in Fractured Porous Media

2024-12-03T12:05:09+00:00

Accurately modeling flow in discrete fracture networks (DFNs) can be important for several fields of engineering such as groundwater management, petroleum engineering, and geotechnical engineering where these DFNs can play a key role in the flow patterns in a formation. These fracture networks are often complex and can have fractures in very close proximity, which, in turn, can lead to challenges in creating fitting meshes for finite element analyses. This work proposes a methodology to handle overlapping fractures in the context of simulating flow in fractured porous media using a Mixed Finite Element Method formulation. With this capability, fractures in close proximity can simply occupy the same geometric location in the mesh, which avoids the creation of elements with poor aspect ratio. In this work, the porous media flow is modeled with traditional Darcy's equations and the fractures and their interaction with the porous media are modeled using the Discrete-Fracture-Matrix (DFM) representation. A mixed finite element formulation is adopted to solve the flow problem in both porous media and fractures, which has key features such as local mass conservation and improved velocity approximation. The mesh generation is done using the DFNMesh algorithm, which is a mesh generator for DFNs that can handle overlapping fractures by using pre-defined user settings. The proposed methodology is analyzed using a set of numerical examples, which show the importance of the treatment even for very simple cases and that it can handle overlapping fractures and provide accurate results for the flow in complex fractured porous media problems.

Finite Element Method applied to the Fractional Partial Derivative Equation of Anomalous Diffusion

2024-12-03T12:09:50+00:00

Diffusion, a fundamental phenomenon in nature, operates on both microscopic and macroscopic scales. At the microscopic level, it manifests itself as a stochastic process, while at the macroscopic level it represents a uniform drift toward equilibrium. The Fokker-Planck equation is widely used to model diffusion phenomena in various disciplines, including physics, chemistry, biology, and others. The classical Ficks law cannot correctly represent the movement of species through inhomogeneous materials, such as porous media. This phenomenon is known as non-Fickian or anomalous diffusion and presents behavior that is difficult to analyze and require computationally intensive simulations. To address this, recent studies have explored modeling anomalous diffusion using fractional derivatives in time or space. Fractional calculus, a branch of classical calculus, provides a framework for handling integrals and derivatives of arbitrary order. Its application has proven to be particularly effective in systems that exhibit hysteresis, allowing the computation of associated memory effects. One example is the modeling of anomalous diffusion in polymeric coatings used to protect flexible pipelines in subsea oil exploration. Under such adverse conditions, extreme depths and temperatures, the properties of the polymer change over time, affecting the ingress of corrosive ions into the metal structure. It left unchecked, this threatens operational safety and environmental integrity. In this work, the Finite Element Method (FEM) is applied to anomalous diffusion described by Fractional Partial Derivative Equations (FPDEs), seeking to predict these intricate transport dynamics.

Global Sensitivity Analysis of Relative Permeability and Capillary Pressure in Unsteady-State Core-Flooding Experiment

2024-12-03T12:13:07+00:00

Numerical simulation stands as a pivotal method within the petroleum industry, enabling the prediction of fluid flow in porous media. Its primary goal lies in analyzing behavior and forecasting oil production through fluid injection. However, the necessity for numerous simulations, each encompassing diverse multidimensional and compositional characteristics, presents a challenge. This leads to a significant accumulation of physical information, exacerbating the computational demands on the numerical model, particularly in terms of computational cost. To address this challenge, one potential solution is to determine the essential input parameters required for accurate oil production prediction. Global sensitivity analysis emerges as a powerful tool for this purpose, aiming to identify which input parameters exert the most significant influence on the numerical model's response, thus optimizing computation time. Unlike traditional approaches that focus on sensitivity around a single operating point, this study adopts a holistic perspective, assessing sensitivity across the entire sample space of the inputs. Specifically, this research investigates the impact of changes in parameters related to relative permeability and capillary pressure curves within a plug during unsteady-state core-flooding experiments. The key metrics under scrutiny include water saturation profiles, pressure differentials, and cumulative oil production. Sobol indices, a method for quantifying global sensitivity, are employed to assess the contribution of each input parameter's variance to the outputs' variance. The mathematical framework employed here is based on the multiphase (water/oil) Darcy equation, incorporating capillarity effects in one-dimensional longitudinal flow, incompressible flow assumptions, and constant injection flow, commonly known as the Black Oil model. The model is solved utilizing an implicit finite difference methodology with time step control, with relative permeability and capillary pressure parameterized by the LET model. The outcomes of this analysis provide valuable insights, notably in reducing the number of estimable parameters in inverse problems on a global scale. This reduction significantly diminishes computing costs, offering greater flexibility in constructing surrogate models for future simulations.

Modeling the propagation of hydraulic fractures in reservoirs with natural fracture networks using high aspect ratio interface elements

2024-12-03T12:18:43+00:00

The application of hydraulic fracturing in unconventional reservoirs is a technique widely used to overcome the problem of low permeability in porous media. However, there are complex factors involved in understanding this technique, since the propagation of hydraulic fractures can be impacted by factors such as the state of stress in situ and the distribution of natural fractures, which may have different lengths, inclination angles and aperture values. Thus, based on the continuum mechanics and using the finite element method, this paper seeks to simulate the effect of hydraulic fracturing in porous media with a complex natural fractures network under the influence of different stress states. The modeling of the problem considers a fully coupled approach for solving the hydro-mechanical problem, with the Darcys law governing the fluid flow in the porous media and by the classical cubic law inside the fractures. For the representation of natural and hydraulic fractures, High Aspect Ratio Interface Finite Elements (HAR-IEs) associated with a suitable tensile damage model are used and inserted into the regular mesh via the Mesh Fragmentation Technique (MFT). The results obtained are validated with the literature and show that the model is capable of reproducing the complex scenarios of propagation and interaction between multiple fractures.

On the numerical simulation of two-phase flow in shale gas reservoirs

2024-12-03T12:29:55+00:00

In the past two decades, the scientific and technological community dedicated to oil and gas production has demonstrated a growing interest in unconventional reservoirs containing natural gas, such as shale reservoirs. These deposits typically contain significant volumes of gas, but their low intrinsic permeability is a drawback. For example, technological advances using horizontal well drilling have led to economically viable production from such reservoirs, and in this context, numerical simulations are relevant in planning natural gas recovery. In this paper, we carry out numerical simulations of isothermal two-phase gas-water flow in shale gas reservoirs. We considered the effects of slippage and adsorption employing the Klinkenberg model and the Langmuir isotherm for the gas phase. It also incorporates a pressure-dependent correction in determining effective permeability for both phases and horizontal wells for production. The Control Volume-Finite Difference method is applied to discretize the governing flow equations, employing centered block grids and fully implicit numerical formulations. We linearize the discretized equation for gas phase pressure using the Picard method, while we use the Newton method for the discretized equation for water phase saturation. The results are analyzed in terms of the pressure at the production well, leading to an evaluation of how the effects considered for the effective permeabilities of the phases influence pressure variation and the times of occurrence of the flow regimes for the considered well-reservoir system.

Optimizing Mesh and CFD Simulation Performance: A Multivariate Analysis Approach

2024-12-03T12:34:27+00:00

The objective of the study is to analyze mesh parameterization through the weighting of results that can define an increase in precision and a reduction in simulation time. To optimize the performance of a mesh and CFD simulation, we will adopt a systematic approach. Initially, we will employ experimental design, with five factors varied in three replications. These factors directly influence three responses. After collecting the experimental data, an evaluation of the significance between the independent variables was carried out, proposing a regression function capable of explaining the behavior of the factors and their relationship with the defined responses. Next, we will identify the individual optimal points using the Ordinary Least Squares method, representing ideal configurations of factors that maximize or minimize the responses of interest. Based on the results obtained, the Payoff matrix will be assembled, containing the individual optimal points and the reactions of the other variables. Thus, the scaling of functions will be performed to formulate and employ the minimization of the Mahalanobis multivariate distance, considering an adequate weighting between the optimal responses. This approach will guarantee the attainment of balanced and efficient solutions. Finally, we will integrate the results of the Payoff matrix into the mixture arrangement methodology, allowing for the conclusion of the analysis of optimal points for each function weight, providing efficient responses for the continuous improvement of the process. This systematic approach, which combines techniques of experimental design, regression, optimization, and multivariate analysis, will be fundamental to maximize the efficiency of mesh and CFD simulation, ensuring precise and reliable results.

A boundary element solution for free vibration of FGM beams

2024-12-04T14:38:09+00:00

The main purpose in this article is to derive a new solution based on Boundary Element Method (BEM) for dynamic analysis of Euler-Bernoulli beams made of composites such as Functionally Graded Materials (FGM) that have properties that vary continuously through the thickness direction according to the volume fraction of constituents. In contrast, laminated composite materials are oriented plies bonded together, where each ply may be made of a different material. A boundary element solution for any problem is obtained using integral equations and fundamental solutions defined on continuum, and algebraic equations for the discretized problem. In this paper, original discussions on deriving both integral equations and fundamental solutions for dynamic composite beam problems are properly made. Algebraic representation is also obtained, incorporating rigid and elastic end supports into the BEM solution. Numerical results of different cases of mechanical properties and boundary conditions are considered and compared to other published works.

A formulation of the fast multipole boundary element method applied to the analysis of anisotropic materials under body forces

2024-12-04T14:42:21+00:00

This work presents a formulation of the boundary element method with fast multipole expansion (MECMP) applied to the analysis of anisotropic elastic materials subject to body forces. Integral equations are obtained using the Somigliana identity. Integrals are divided into near field and far field. Near field, when the source points and integration elements are close, are treated as in the standard boundary element method, that is, integrating along the element and considering the interaction between source points (nodes) and the elements. On the other hand, in the far field, when the source points and integration elements are far away, the fast multipole method is applied. In this case, the fundamental solution is expanded in a Laurent series and the node-to-node interaction is replaced by a cell-to-cell interaction. Cells are generated by a hierarchical decomposition of the domain using the quad-tree algorithm. Different fast multipole operations are used to take advantage of the hierarchical domain decomposition and expansions of the fundamental solutions. Influence matrices are never explicitly obtained and the matrix-vector product are carried out with linear complexity. The linear system is solved by an iterative method. A preconditioning matrix is used to reduce the number of iterations to obtain a result with an specified accuracy. Effectiveness and efficiency in solving large-scale problems are discussed. The treatment of problems involving body forces are taken into account by the utilization of the modified boundary condition method. This approach entails augmenting the boundary condition with a specific solution tailored to the problem. Following the solution of the linear system, the particular solution is subsequently subtracted from both displacements and tractions. Importantly, this procedural step obviates the need for generating additional vectors or matrices within the matrix equation. The formulation presented in this article is based on a representation of complex variables of the integrands, similar to the formulation previously developed for potential (scalar) problems. Validation is carried out by comparing the results obtained by the two formulations: the standard boundary element method and the boundary element method with fast multipole expansion. The influence of the number of terms of the series expansion in the calculation of fundamental solutions and influence matrices is analyzed. Numerical examples are presented to demonstrate the efficiency, accuracy, and potential of the boundary element method with fast multipole expansion to solve large-scale problems, i.e., with tens of thousands of degrees of freedom.

Boundary element method for buckling analysis of elastically connected double-beam system

2024-12-04T14:45:54+00:00

Studies of Double-beam systems have received significant attention from researchers due to their wide applications in civil and mechanical engineering. Commonly, finite element method or exact solutions have been employed to solve double-beam systems, with few others considering buckling of axially loaded double-beam systems with classical boundary conditions. This paper presents a novel formulation of the Boundary Element Method (BEM) to determine the critical buckling load of the double-beam system elastically connected by a Winkler elastic layer with generalized boundary conditions. Based on the Euler-Bernoulli beam theory, the double-beam system is composed of two identical beams. This paper provides a detailed discussion of each step involved in the BEM, including the fundamental solution, boundary integral equations, and algebraic system. Examples considering different boundary conditions, material properties, and load cases are done and compared to corresponding analytical solution. The results show excellent agreement between the BEM approach and the analytical solution, confirming the accuracy and effectiveness of the technique.

Dynamic amplification analysis in acoustic wave propagation problems subject to time-variable loads

2024-12-04T14:52:07+00:00

In this work, the formulation of the direct interpolation boundary element method is applied to evaluate the dynamic behavior of continuous acoustic systems subject to the excitation of time variable loads. In such a condition, the temporal variation of the load may be close to some of the system's natural frequencies, and the evaluation of dynamic amplification and damping effects is very important. Physically, the analysis undertaken in this work provides an excellent indication of the dynamic behavior of a continuous system subject to pressure waves, which can be an aqueous medium or any seismic medium. In numerical terms, the simulations carried out show the robustness of the chosen technique in solving acoustic wave propagation problems compared to other methods.

Efficient evaluation of near-singular integrals of the eXtended Isogeometric Boundary Element Method for three-dimensional fracture mechanics

2024-12-04T14:54:53+00:00

The Boundary Element Method (BEM) has proven to be a suitable method for the numerical assessment of numerous engineering problems in both two-dimensional and three-dimensional forms. In particular, BEM robustly handles discontinuities in the mechanical response present in fracture mechanics applications. Additionally, its boundary-only nature simplifies the re-meshing process during crack growth modelling. Furthermore, coupling BEM with isogeometric analysis (IgA) is straightforward, as both strategies rely on boundary representation, enabling the direct use of Computer-Aided Design (CAD) geometry as the mesh for the method. IgA basis functions can accurately represent complex surfaces such as spheres and toroids. In this context, the Isogeometric Boundary Element Method (IGABEM) emerges as a reliable tool for solving engineering problems, combining the advantages of BEM with the improved geometric accuracy provided by IgA. In addition, a relevant approach in fracture mechanics is using enrichment functions that incorporate known solution fields, addressing response aspects that standard isogeometric basis functions cannot capture. Combining the enrichment strategy with IGABEM leads to the eXtended IGABEM (XIGABEM) method. Specifically, enriching functions that account for the square-root inverse behaviour on crack surfaces promotes several improvements, such as improved convergence rate and removal of a non-physical jump displacement in the crack front. Another advantage is the direct extraction of Stress Intensity Factors (SIF) as system variables, eliminating the need for costly extraction techniques in three-dimensional problems. However, near-singular integrals appear after the Singularity Subtraction Technique (SST) of the enriching terms in 3D XIGABEM. This study proposes using the hyperbolic sine transformation for the near singular surface integrals that arise from the SST to evaluate them efficiently. Numerical applications demonstrate a reduction in the required integration points for these integrals compared to traditional methods. Therefore, this advancement in the XIGABEM framework reduces the computational cost of this strategy while maintaining accuracy.

Fracture failure representation of quasi-brittle materials using a three-dimensional dipole BEM formulation including loading rate effects

2024-12-04T14:57:43+00:00

This study presents an alternative boundary element method (BEM) formulation for the cohesive crack propagation modelling in three-dimensional structures, including loading rates problems. Therefore, these developments enable the modelling of viscous-cohesive fracture processes. An initial stress field for representing the mechanical behaviour along the fracture process zone is proposed, which leads to a set of self equilibrated forces named as dipole. The proposed dipole-based formulation demonstrates some advantages in comparison to classical BEM approaches in this field. Among them, it is worth citing the discretisation of only one crack surface and the requirement of solely three integral equations per source point at the crack surface. Then, in addition to the accuracy, the proposed formulation is efficient in terms of computational effort, which is a bottle neck in three-dimensional problems. Cohesive laws govern the material nonlinear behaviour along the fracture process zone. The mechanical effects of loading rate over the material resistance at the FPZ are properly handled by a time dependent function, which modifies the tensile material strength and the material fracture energy as a function of the loading velocity rate. Some applications are introduced to demonstrate the adequate performance of the proposed formulation, in which the results obtained have been compared against experimental responses available in the literature.

Implementation of a Fatigue Analysis Program Based on the Dual Formulation of the Boundary Element Method

2024-12-05T11:29:34+00:00

The study and analysis of fatigue are extremely important, given the countless financial and social losses caused by this damage process. For this reason, a complete computational program is implemented for two-dimensional fatigue analysis in cracked components, coded in Fortran 95 language. The Dual Boundary Element Method (DBEM) is used to evaluate the elastic fields of displacement and traction, through the placement of Boundary Integral Equations (BIE) of different natures on each of the crack faces. Stresses and strains at boundary points are evaluated through the hypersingular BIE. Once the variables of interest are obtained in the boundary, the fatigue subcritical propagation of cracks is evaluated based on the concepts of Linear Elastic Fracture Mechanics (LEFM). J-Integral is used to measure the stress intensity factors at the crack tip, due to its effectiveness, precision and excellent coupling with the dual formulation of the Boundary Element Method (BEM). The direction of crack propagation is defined by the Maximum Circumferential Stress criterion. Finally, the lifespan of the cracked component is determined using an adapted Paris Equation, in order to correctly evaluate mixed mode fracture and non-zero mean stresses. Furthermore, using the Rainflow Cycle Counting algorithm, the program is capable of evaluating components under the action of cyclic loads of variable amplitude. In order to evaluate the implemented computational program, two examples are presented. The first considers a Compact Mixed Mode (CMM) specimen under mixed mode fracture. The second example evaluates the driven wheel of an iron ore pelletizing furnace under cyclic loading of variable amplitude. According to the results presented, it is proved the effectiveness and reliability of the developed computational program, which allows to accurately analyze real situations of components under mode I, II or mixed mode fatigue.

Isometric Boundary Element Method for 2D analysis of elastostatic structural issues

2024-12-05T11:39:23+00:00

In structural engineering, there is a growing trend towards using elements that better conform to geometric characteristics. This is particularly true when leveraging surface (or line, in 2D cases) generation in CAD environments, directly benefiting from more precise geometry. In this context, the need for Isogeometric elements arises. Through their utilization, the analysis of more complex stress and strain distributions is conducted with greater accuracy. This paper presents an alternative for analyzing the structural behavior of elastostatic structural cases through 2D modeling, employing an approximate method with Isogeometric elements. A computational implementation of the Boundary Element Method (BEM) was developed using the Python programming language. The "2D BEM" code was adapted, employing Kelvin's fundamental solution with the use of continuous and discontinuous linear elements, as well as higher-order elements, for more accurate boundary discretization. The formulation of BEM thus enables the modeling of the domain, in this case, the analysis of 2D bodies in the presence of mechanical damage, with iterative monitoring. The behavior is assessed through the displacements obtained for the boundary and internal points, as well as the stresses, conveniently evaluated in graphical representations. Applications are presented to test the implemented modeling and to provide an alternative for analyzing an important area within structural systems in civil construction projects, among others.

Multiscale Modelling of the Two-Dimensional Problem Using the Boundary Element Method

2024-12-05T11:45:36+00:00

A full coupled multi-scale modelling using the Boundary Element Method for analysing the 2D problem of stretched plates composed of heterogeneous materials, where dissipative phenomena can be considered, is presented. Both the macro-scale and the micro-scale are modelled by BEM formulations where the consistent tangent operator (CTO) is used to achieve the equilibrium of the iterative procedures (see [1]). The equilibrium equation of the plate (macro-continuum) is written in terms of in-plane strains while the equilibrium problem of the microstructure, which is defined by the RVE (Representative Volume Element), is solved in terms of displacements fluctuations (see [2]-[5]). In this kind of modelling, the mechanical behaviour of the material is governed by the homogenized response of the RVE, obtained after solving its equilibrium problem. As this kind of modelling is expensive computationally, it is important to investigate other numerical methods to have faster formulations, but which are still accurate. To validate the presented model, the numerical results are compared to the ones where the material microstructure (RVE) is modelled by the FEM.
REFERENCES
[1] G. R. Fernandes and E. A. de Souza Neto, Self-consistent linearization of non-linear BEM formulations with quadratic convergence, Computational Mechanics, vol. 52, pp. 1125-1139, 2013.
[2] G. R. Fernandes, L. H. R. Crozariol, A. S. Furtado and M. C. Santos, A 2D boundary element method to model the constitutive behavior of heterogeneous microstructures considering dissipative phenomena Engineering Analysis with Boundary Elements, vol. 99, pp. 1-22, 2019.
[3] G. R. Fernandes, J. J. C. Pituba and E. A. de Souza Neto, FEM/BEM formulation for multi-scale analysis of stretched plates, Engineering Analysis with Boundary Elements, vol. 54, pp. 47-59, 2015.
[4] D. Peric, E. A. de Souza Neto, R. A. Feijóo, M. Partovi and A. J. C. Molina, On micro to macro transitions for multi scale analysis of non linear heterogeneous materials: unified variational basis and finite element implementation, Numerical Methods in Engineering, vol. 87, pp. 149-170, 2011.
[5] Somer D.D., de Souza Neto E.A., Dettmer W.G., Peric D., A sub-stepping scheme for multi-scale analysis of solids, Comput. Methods Appl. Mech. Engrg., v. 198, p. 10061016, 2009.

Possibilities of node location optimization and the quest isoparametric versus isogeometric in the collocation boundary element method

2024-12-05T11:49:50+00:00

We have recently laid down the theoretical basis for the consistent formulation of the collocation boundary element method, as it should have been conceived from the beginning. We proved a convergence theorem for two- and three-dimensional problems of elasticity and potential, which applies to arbitrarily curved elements in the frame of an isoparametric analysis. We also showed that arbitrarily high precision and accuracy may be achieved limited only by the machines capacity to represent numbers. On the other hand, there still is the cost-benefit question considering that the physical phenomenon is mathematically adequately idealized of how to improve a real problems simulation without refining too much a discretization mesh. The first possibility of doing this is optimizing the geometric location of the primary parameters (as for displacements and tractions, in elasticity) for the problem's mechanical description. This primarily consists in locally refining a mesh. We may also attach the problems parameters to optimal locations inside the boundary element. A second issue is that an isoparametric formulation (generally in terms of polynomial interpolations along the boundary segment) may fail to reproduce the exact geometry of the idealized physical problem as the isogeometric approach does. Since, for two-dimensional problems, we have the boundary element formulation under control regarding all numerical evaluations, we assess how an isoparametric analysis with the introduced elegancy of a convergence theorem compares to a formulation that preserves the problems idealized geometry, but to which the theorem no longer applies. We present the conceptual formulation, code implementation, and numerical illustrations.

Stress Recovery Techniques for the Modified Local Greens Function Method

2024-12-05T11:51:51+00:00

The Modified Local Greens Function Method (MLGFM) is an integral method hybrid of the Finite Element Method (FEM) and the Boundary Element Method (BEM). The method uses the FEM to create discrete projections of the Greens functions that will be used as fundamental solutions in BEM formulation. The MLGFM has the advantage of presenting high convergence for the displacements in the domain, inherited from the FEM, and for the normal stress on the boundary, inherited from the BEM. Despite these advantages, the accuracy of the recovered stresses in the domain has not been studied in previous works. As the MLGFM is a hybrid of the FEM and BEM, techniques used in both methods will be explored in this paper to study the advantages and disadvantages of each one. The techniques that will be used here are the Least Squares procedure, the Zienkiewicz and Zhu (ZZ) recovery, both widely used in FEM, and the integral form derived from the fundamental solution used in the BEM. The techniques will be analyzed in terms of errors and computational cost of each one.

A Surrogate-Based Approach for Bend-Twist Coupling Optimization of a Horizontal Axis Wind Turbine Composite Blade

2024-12-11T12:53:24+00:00

A design study on the effect of bend-twist coupling in a composite blade of horizontal axis wind turbine (HAWT) is conducted. Using specific lamination sequences with unidirectional plies, a laminated composite is obtained whose mechanical stresses are coupled in its bending and twisting. Given the aerodynamic forces on the blade during its operation, mechanical stresses emerge in the material, which, due to its bend-twist coupled behavior, conforms elastically, adapting its geometry to the wind flow. The tailoring of aeroelastic effects can be applied to wind turbine blades to improve the performance of wind turbines. Furthermore, the manufacturing costs, either from material or process perspectives, are potentially reduced with well-designed layup sequences. A blade is first designed according to specific parameters using the Blade Element Momentum Theory (BEMT) under the assumption of total rigidity. These include operational and constructive parameters (e.g., desired output power, airfoil profile characteristics, nominal wind velocity, number of blades, etc.). The effect of bend-twist coupling in the laminated composite is analyzed by fluid-structure interaction (FSI). The layup sequence is parametrized within ANSYS Composites PrepPost (ACP) with different laminations for upper and lower face of the blade, given both geometry and stress distributions differ for each face. The CFD and the structural behavior are coupled in a two-way FSI system, along with material properties evaluated from ACP. Thus, deformations are computed using the pressure distribution from CFD and material properties from ACP. The power coefficient is calculated once the FSI simulation has converged, yielding the resultant torque and rotation, which are then used to evaluate the extracted power.. An optimization routine is implemented to maximize the power extraction as a function of the lamination sequence for the upper and lower faces of the blade. The computational cost of the optimization procedure is reduced by employing radial basis function neural network, acting as a surrogate model. It is predicted an increase of up to 10% in the power coefficient for the generator. The final proposed laminated composite for upper and lower faces of the blade extends the power curve of the generator, allowing it to sustain operation even in overload conditions, delaying stall of the blades and avoiding tower collapse by excessive blade tip axial deflection.

Advancing Offshore Wind Turbine modeling: developing an integrated tool for structural control

2024-12-11T13:08:54+00:00

This paper presents the modeling of a 22 MW OWT (IEA Wind 22-Megawatt Offshore Reference Wind Turbine), intended for integration into a new MATLAB-based user-friendly interface. Users can select from turbines ranging from 5 to 22 MW, inputting relevant data on wind and maritime conditions, and other relevant data. Significantly advancing prior research utilizing a 5 MW NREL OWT, this study encompasses hydrodynamic and aerodynamic modeling of a flexible tower to assess response peaks at the OWT hub, evaluated via Power Spectral Density analysis. The routine models the tower, incorporating a rotational spectrum to account for blade rotation effects. The developed tool may include the incorporation of vibration absorbers for structural control, such as pendulum, inertial, or liquid column absorbers, among others.

Analysis of the fluid-structure interaction of a 2D model of the savonius rotor, using immersed boundary and fourier pseudospectral methods

2024-12-11T13:12:28+00:00

Savonius rotors are a unique type of vertical axis wind turbine (VAWT) characterized by its S shape, with low rotational speed, low noise and good automatic start-up capability. This turbine has a great profile for
small businesses and residences. The present work presents a simplified modeling of the fluid-structure interaction problem of a Savonius rotor, using the Fourier pseudospectral method (FPSM) coupled to the immersed bound-ary method (IBM), considering the Newtonian fluid, incompressible flow, without heat transfer and gravitational effects, with constant and two-dimensional (2D) properties. The results presented address the flow over a freely rotating vertical turbine, which allows the analysis of the evolution of the moment coefficient (Cm ) in relation to temporal evolution, azimuthal position (θ) and the blade tip speed ratio (λ).

Comparative Study of Intelligent and Classical MPPT Techniques Applied to Solar Battery Charger

2024-12-11T13:15:48+00:00

Renewable solar energy is an excellent alternative to conventional energy sources and, recently, it has shown remarkable growth on electrical power grid in various countries around the world. Maximum power point tracking (MPPT) has critical importance in solar energy generation since it increases the system's efficiency in many scenarios. Photovoltaic modules (PV) are influenced by environmental factors such as temperature and solar irradiation density, changing the amount of energy generated throughout the day. In order to extract the maximum available power from a PV, its necessary to use the MPPT technique, which considers the systems nonlinearities. Maximum power tracking (MPP) is done by tuning the duty cycle of the DC-DC converter, so that the PV's terminal voltage is modulated to match the environmental conditions. This tuning, generally, is dependent on sensor readings. Normally, only the modules voltage and current sensors are used, due to the low cost and ease of acquisition of these signals. However, intelligent techniques demand the usage of temperature and irradiation sensors, increasing the complexity of the systems implementation. The use of intelligent control techniques applied to the energy generation system has had a notable presence in recent publications. The high efficiency obtained from its application demonstrates that the use of intelligent systems in the decision-making process is a useful tool in obtaining maximum generation power. The objective of the present study is the development and simulation via MATLAB/SIMULINK of a battery charging system with solar energy, which consists of a PV, a Buck converter, a 12V battery, and the MPPT controller. The intelligent fuzzy logic MPPT technique (FLS) and the classical incremental conductance technique (INC) will be compared, both techniques using only voltage and current measurements.

Computational Simulation of a Plane Channel with Spalart-Allmaras Turbulence Model and Fourier Pseudo-Spectral Method

2024-12-11T13:20:07+00:00

The majority of fluid flows encountered in nature and practical applications are turbulent, characterized primarily by a broad range of scales, from large structures influenced by flow geometry to small structures determined by fluid viscosity. Turbulence is a topic of significant relevance in engineering across various sectors. For instance, airflow over terrestrial surfaces, where roughness varies considerably, is critical for predicting the potential and sizing of wind turbines and wind farms.
In this context, this study proposes extending the IMERSPEC methodology to conduct simulations of turbulent flows based on Reynolds-averaged Navier-Stokes equations, utilizing the Spalart-Allmaras turbulence model. The IMERSPEC methodology integrates the Fourier Pseudo-Spectral Method with the Immersed Boundary Method, offering excellent numerical accuracy and computational efficiency compared to other high-order techniques, attributed to the efficient use of Fast Fourier Transform (FFT) and the pressure term projection method in Fourier space.
The numerical results obtained through this approach are validated against experimental data and Direct Numerical Simulations (DNS) for flow in a flat channel at a Reynolds number of 40,000. This comparative analysis will facilitate assessing the effectiveness and precision of the proposed method in capturing turbulent flow characteristics, with potential applications in aerodynamic and fluid dynamic engineering studies.

Discussion on bending-torsion behavior of long wind turbine blades

2024-12-11T13:22:43+00:00

In recent years there has been a tendency to increase the size of wind turbine rotors, particularly when considering offshore applications, leading to more capacity for energy extraction from wind. However, there are many engineering challenges to that. Blades become very long, surpassing lengths of 100 meters, and are usually very flexible, which claims a geometrically nonlinear model for evaluation of their structural behavior. In this context, the present work employs an enhanced structural solver to evaluate the behavior of very flexible wind turbine blades. The blades are modeled as beams. Large displacements and finite rotations are assumed to model the kinematics by employing the geometrically-exact theory. To establish a relationship between generalized internal loads and generalized strains we adopt a linear constitutive model such that one can take results from BECAS, directly. This can handle torsion-bending constitutive coupling for a general position of the beam axis, conveniently. The developed solver was used to study general operational conditions, assuming distinct pitch angles for the blade considering the scenario of the wind turbine. The present work brings discussions on the structural behavior, such as internal loads distributions along the blade spam in numerical simulations. The focus is given to the analysis of bending and torsion moments, discussing their aspects when considering such a long and flexible blade in operational conditions.

Estimation of wind energy potential through experimental investigation of boundary layer in small wind tunnel

2024-12-11T13:25:58+00:00

In Brazil, the persistent increase in electricity consumption, primarily propelled by economic and technological advancements, can exceed the capacity of generation and distribution, underscoring the imperative for alternative energy sources. Given the compromised state of hydroelectric power and the environmental ramifications of thermoelectric plants, wind energy emerges as a promising and sustainable solution. Research in this domain encompasses turbine efficiency and analysis of local wind potential. Precise determination of this potential is pivotal to ensure project viability and efficacy, directly impacting decisions of electrical generation companies. Tests for assessing wind potential can be conducted in situ or employing techniques such as Fluid Dynamics, crucial for large-scale projects. Experimental investigations, particularly those conducted in wind tunnels, assume a foundational role in research and development in this field. The distribution of wind velocity across the test section stands as a critical parameter, with accurate simulation of the atmospheric boundary layer being indispensable for dependable outcomes. The boundary layer, an area adjacent to the surface influenced by friction between solid and fluid, holds a crucial role in drag and heat transfer. Various techniques have been devised to simulate and control the boundary layer in wind tunnels, representing a burgeoning area of inquiry. The present study advocates for the utilization of the 'boundary layer plate with flap device' to examine how different flap angles and Reynolds numbers impact boundary layer height, employing experimental design with factorial planning for result analysis. Subsequently, the obtained results indicate that flap angle significantly alters the boundary layer height within a given range of Reynolds numbers, thereby enabling the simulation of diverse boundary layer heights within a small wind tunnel, facilitating experiments related to wind flow and atmospheric boundary layer. Consequently, this research contributes to the estimation of wind potential and propels the efficient utilization of wind energy as a clean and renewable source.

Improving the energy efficiency of residential buildings in Brazil by changing the geometry of ceramic bricks

2024-12-11T13:30:16+00:00

The performance of a building's thermal and energy systems is greatly affected by its building envelope. In Brazil, residential buildings typically utilize masonry walls with coatings, and the materials used, such as the block models, have a significant impact on their energy efficiency. However, cost is a limiting factor when it comes to improving performance. One way to modify thermal properties without significantly increasing manufacturing inputs is to explore new geometries of ceramic blocks. This study introduces a new ceramic block geometry for structural masonry, adapted from a commonly used 14cm thick commercial model in Brazil. The thermal properties of this new model are evaluated numerically using Abaqus software. Additionally, the study presents the findings of an energy simulation conducted on housing models in cities like Fortaleza, Brasília, and Curitiba using Energyplus software. The results show potential for reducing energy consumption in colder months while having a minimal impact on energy consumption in hotter climates, while still maintaining a comfortable temperature.

Soil-structure interaction effects on modal analysis of a 3D reticulated structure supporting plane rectangular shells

2024-12-11T13:35:04+00:00

This paper aims to verify the interference of soil-structure interaction (SSI) on the natural frequencies and on the respective vibration modes of a 3D reticulated structure supporting plane rectangular shells. This is done through a computational linear elastic 3D finite element model using EulerBernoulli frame elements, biquadratic Lagrangian thin shell elements and elastic translation springs for the soil at columns bases (representing pile embedded length). A convergence analysis is performed to determine the maximum mesh size and mass participation factors are measured to establish the number of considered vibration modes. Chosen elastic spring coefficients are extracted using polynomial linear regression applied to the results of experimental compressive and horizontal load tests of steel piles embedded in a silty clay soil. Using these parameters, nine models are processed via an eigen solver and obtained frequencies and some mode shapes are presented. It is found that, for the adopted approach and for the evaluated structure, there are not significant changes in modal response induced by SSI, being the mass distribution more important than soil stiffness in this case. Despite the results, this study indicates the need of further investigation to provide better measures about the interference of SSI on modal response of structures as the one analyzed in this research.

Structured Model for Hydrothermal System Operation and Optimization

2024-12-11T13:39:15+00:00

This paper presents an analysis for optimizing hydrothermal system operation within the Brazilian energy sector.
In the last years, researchers at the Laboratory of Bio-Inspired Technologies and Solutions from Federal University of ABC (LabBITS - UFABC) have been implementing a platform for accessing the information of this Brazilian electric power generation system from a SQL (Structured Query Language) database, regularly updated from the ONSs provided package of files. The database is accessed by the laboratory researchers via a REST (Representational State Transfer) API (Application Programming Interface) which is used to supply the parameters of the energy system models used in the energy operation planning calculations.
In 2024, utilizing Java object models for hydroelectric power plants, a structured approach was developed, organizing plants into power plant systems to capture the interdependencies between flow data and storage of water in reservoirs throughout a cascade and across time.The simulation technique of genetic algorithms was then applied to test the structure for optimal operating schedules. Different populations of solutions were tested, considering the maximization of energy generation.

Study of the Influence of Buildings on the Performance of Micro Wind Turbines in Urban Environments through Computational Simulations

2024-12-11T13:42:21+00:00

In urban areas, where space is limited, micro wind turbines can be installed on rooftops or structures near buildings. Studying the flow around cylinders near a flat wall is important for understanding how the presence of buildings affects the performance of these micro wind turbines and how they can be optimized to operate in urban environments. This study employs the Pseudospectral Fourier method coupled with the Immersed Boundary method in simulations involving flow around a circular-based cylinder near a wall. This work presents simulations that demonstrate the influence of local Reynolds number with the introduction of a wall, as well as the influence of varying the distance between the cylinder and the wall, referred to as "GAP," on the formation of the vortex wake. The results are compared with other works: experimental and numerical.

Using Computational Fluid Dynamics to investigate heat exchanges between the environment and photovoltaic panels

2024-12-11T13:44:34+00:00

Given the increasing demand for energy sources with lower environmental impact, solar panels play an important role in diversifying energy sources and in the process of decarbonizing the electrical grid. Their electricity production is based on the photovoltaic effect; however, only a portion of the energy from solar radiation is utilized, with the rest being reflected or transferred to the environment in the form of heat, increasing the temperature of the panel and causing an energy efficiency loss, since the performance of the panels is influenced by the operating temperature.
Therefore, our study aims to investigate the heat exchanges by natural convection that occur between solar panels and the surroundings, disregarding radiation. The analysis was conducted using Computational Fluid Dynamics with the OpenFOAM software, which employs the Finite Volume Method to discretize the governing equations. We sought to evaluate the effects of varying the inclination of the panel on the surrounding temperature.
The CFD modeling consists of three stages: pre-processing, processing, and post-processing. In the pre-processing stage, the Gmsh software was used to create the computational domain, a simplified 2D model of 4 m x 4 m around the panel with a length of 2 m, a temperature of 80 °C, and presenting different inclinations. Then, the domain was discretized through the division into an unstructured mesh of finite volumes with progressive refinement near the panel.
Wall conditions were assigned for the ground and the panel, and free flow conditions for the surroundings. The fluid was defined as air, with dynamic viscosity of 1.849 × 10^-5 kg/m∙s, specific heat at constant pressure of 1000 J/kg∙K, Prandtl number of 0.7296, and temperature of 25°C. In the processing stage, the transient state solver, buoyantPimpleFoam, was used for transient and turbulent flows of compressible fluids for heat transfer, including the K-epsilon turbulence model.
In the post-processing stage, the Paraview software was used to map temperature and velocity fields. The results show the formation of air flows and the gradual propagation of temperature to the environment from the panel through thermal plumes. The increase in the panel's inclination contributed to raising the average temperature of the surroundings. The natural convection from the panel caused the formation of air flows due to the buoyancy effects that occur with the variation of the fluid's density.

Application of Convolutional Neural Networks for Advanced Classification of Power Quality Signals

2024-12-13T14:27:42+00:00

In this work, we explore the classification of power quality signals using a simulated database incorporating both unique and combined disturbances in accordance with IEEE 1159 standards. The primary focus is on employing convolutional neural networks (CNNs) for the detection and classification of these anomalies. To assess the effectiveness of our approach, we conducted a comprehensive comparison between the outcomes from CNNs and traditional machine learning techniques, as well as with recent literature findings. Preliminary results indicate that CNNs exhibit a remarkable ability to capture distinctive features of power quality signals, surpassing traditional methodologies in terms of accuracy and robustness. This study not only reaffirms the potential of convolutional neural networks in the field of power quality monitoring but also paves the way for future investigations that might explore more complex deep learning approaches to further enhance the accuracy of anomaly classification in electrical systems.

Cardiac Pacemaker: Fractional Equations and Frequency Analysis

2024-12-13T14:31:02+00:00

Understanding and researching the human body has been fundamental due to its importance for living beings. As one of the vital organs of the human body, the heart has always been of great academic relevance. One of the areas of study of the heart is the study of the electrical stimuli that provide blood pumping. These electrical stimuli come from the Sinoatrial Node (SA), known as the natural pacemaker, which transmits the stimuli to the other parts of the heart, thus allowing blood to be pumped. A model to represent the signals of a pacemaker has been developed using a relaxation oscillator, the Van der Pol oscillator, given by a second-order differential equation. In this particular study, a more comprehensive investigation is proposed by introducing fractional order differential equations. Varying the order of the system allows for a more refined analysis of the dynamic properties of the Van der Pol oscillator and, by extension, of the cardiac pacemaker modeled by it. This approach is especially relevant considering the complex and nonlinear nature of the cardiovascular system. The practical implementation of this model is carried out by means of numerical simulation, using algorithms developed in the Python programming language. This choice of platform allows for efficient and flexible analysis of the resulting signals under different conditions and system parameters. Signal analysis in the time domain is complemented by advanced signal processing techniques in the frequency domain. The Discrete Fourier Transform (DFT) and Continuous Wavelet Transform (CWT) are employed to investigate the system's response at different frequencies, providing an in-depth understanding of its stability and dynamic behavior. In addition, the graphical representation of the results using phase spaces and bifurcation diagrams provides a visual understanding of the complex interactions between the system components and their dependencies on the model parameters.

Control allocation of an arbitrary fully actuated multirotor aerial vehicle equipped with 1-DOF vectoring rotors

2024-12-13T14:35:23+00:00

The present paper deals with the control allocation of fully actuated multirotor aerial vehicles (MAVs) equipped with an arbitrary number of only radially vectoring rotors. To tackle the problem, we first consider a control architecture in which the control allocator is cascaded with the control laws. Therefore, the latter provides the resultant force-torque commands for the former to distribute them among the available actuators, which include the spinning and the vectoring motors. We formulate the control allocator through an optimization problem in which the rotor thrust vectors represented in body-fixed frames are the design variables. In this way, the control allocation equation becomes linear since it does not explicitly include the commands for the vectoring angles, which can be immediately computed afterwards using the computed optimal thrust vectors. In the optimization problem, the thrust vectors are constrained in such a way to respect given bounds on their magnitude and vectoring angle. It is noteworthy that, considering a minimal thrust magnitude, in general, greater than zero, the thrust vectors span non-convex sets, thus making the original problem a non-convex optimization. However, instead of dealing with such convex sets, we have replaced them by convex ones, thus given rise to a convex program that approximates the original problem. The method is widely evaluated by computer simulations on a hexa-rotor with all the six rotors equipped with a one-degree-of-freedom vectoring mechanism.

Exploring the Dynamics of Wind Energy Harvesters: VIV Turbines and Piezoelectrics

2024-12-13T14:38:12+00:00

Wind energy is recognized not only for its high generating capacity among renewable sources, but also for its growing popularity in recent years. However, conventional wind turbines, which rely on blades to capture wind energy, present significant challenges, including noise pollution, interference with bird migration and the frequent need for maintenance due to the complexity of their mechanical components. In an attempt to minimize these problems, current innovations include bladeless wind turbines (VBWT). These operate from wind-induced vibrations, mostly vortex-induced vibrations (VIV). Among the various designs that have been documented, those that exploit energy generation through electromagnetic induction and piezoelectric systems deserve to be highlighted, as they have gained increasing recognition in the academic sphere. In this context, this work focuses on carrying out a dynamic analysis of a vortex-induced vibration energy harvester (VIVEH), which will have its energy generated from a piezoelectric patch connected to a beam with non-linear stiffness due to a magnetic coupling. The system will have its equations of motion simulated using a Runge-Kutta integrator implemented in the Python programming language, where its responses will be analyzed in the time domain by studying the system's sensitivity to different wind speeds, and in the frequency domain using tools such as Fast Fourier Transforms (FFT) and Continuous Wavelet Transforms (CWT). The results focus on analyzing the influence of the beam's non-linearity and its response in the frequency and time domain for different wind speeds.

Remarks On the Use of Variational mode decomposition for Chaos and Nonlinear Dynamics Analysis in Fractional-Order Systems applications

2024-12-13T14:41:48+00:00

This study investigates the dynamics of an electromechanical device for energy generation. The device utilizes a motor with an unbalanced mass coupled to a piezoelectric substrate. The central focus of the analysis is measuring the average power generated by the piezoelectric material, which is stimulated by the motor's vibrations. We explore the fractional dynamics of the system, examining variables such as the parameter of the fractional derivative operator and the control parameter. Using techniques like bifurcation diagrams and recurrence analysis, we investigate the routes to chaos and their implications on the stability and behavior of the system. The study is enhanced by the implementation of Variational Mode Decomposition, a technique that allows us to decipher the complexities of the system's dynamics.

Vibration of extremely flexible beam axially tensioned by incremental force

2024-12-13T14:44:51+00:00

Cables can be associated with extremely flexible beams. Particularly, electrical system cables supported on transmission towers are subject to climatic conditions whose effects are capable of mobilizing their vibration modes. The first mode is considered to be of special importance due to the shape assumed by the cable when subjected to the Earth's gravitational field. Under these conditions, cable deformation is influenced by its geometric and material properties, including viscoelastic behavior, when considered, making these systems intrinsically nonlinear in terms of geometry and material. The balance of these structural parts can only be found in the deformed configuration of the system. As a rule, cables need to be pulled for proper and correct use in transmission lines. The use of a traction force modifies the rigidity of the system, causing an increase in the natural frequencies of vibration. This occurs because the force that pulls the cable mobilizes the geometric stiffness portion of the total system stiffness. In solving the vibration problem, numerical methods can be employed. To this end, the model adopted is analogous to a double-supported beam, for which the successive integration of the bending moment differential equation leads to displacements of the axis, or the elastic line, for each stage of the iterative process. These iterations are repeated until the sum of the portions equals the total axial force to be applied. The smaller the force portion in each iteration, the better the result obtained. However, the number of iterations required will be greater, making processing potentially costly from a computational point of view. To solve the proposed problem, a programming routine was developed in the Python Jupyter Notebook language that allows calculating the deformation of the structural system and the natural frequency of vibration in each iteration. The process begins with the analytical solution of the approximate elastic line under the effect of gravity and the subsequent tension in the cable, with the definition of the natural frequency of vibration following the Rayleigh method. In the end, the first natural vibration frequency of the cable was raised non-linearly from 0.358 Hz to 5.944 Hz.

A Comparison of Mesh Simplification Strategies for Realistic Grains

2024-12-16T14:01:39+00:00

In recent years, the Discrete Element Method (DEM) has emerged as a powerful tool for studying granular materials. In a DEM simulation, the objective is to reproduce the grain-to-grain interactions, and by working at this scale, the method can provide new insights into granular behavior. In the early stages of DEM, the particles were represented by disks and spheres. Currently, many codes have been developed to incorporate new ways to represent the grain shape more accurately. However, this process is not simple, taking into account that more realistic shapes bring the necessity of more complex algorithms for contact detection. Furthermore, to represent realistic grains through some ways like polyhedrons, a large number of entities (i.e., points, faces, and edges) are necessary, which increases the computational costs, making the simulation infeasible in some situations. To circumvent this problem, an alternative commonly used with polyhedrons is to reduce the number of entities in the mesh, decreasing the computational costs of simulation and the level of fidelity to the real grain shape. Due to the importance of this pre-processing stage, this paper compares three strategies for mesh simplification, analyzing the impact in shape descriptors, and the computational costs involved entities in DEM simulations, when varying their level of representation of 30 realistic grains.

A mixed total Lagrangian-updated Lagrangian Smoothed Particles Hydrodynamics method for geomechanics simulations with discontinuities

2024-12-16T14:07:17+00:00

This study presents a novel approach for simulating geotechnical problems including the initiation and post-failure behavior of discontinuities. The developed method is constituted by a mixed total Lagrangian--updated Lagrangian Smoothed Particle Hydrodynamics (SPH) method, which the main characteristic is to distinguish between internal forces within a body and contact forces from interactions with other bodies as internal stress and collision stress, respectively. Internal stress effects are calculated using total Lagrangian SPH interpolations, while collision stress effects are computed with updated Lagrangian. Fractures are simulated by employing plastic deformation as a damage measure, with fully damaged particles detached from their original body and treated as a separate particulate material, interacting via collision stress. Numerical tests confirm the method's capability in accurately modeling elastic collisions, friction forces and tension and shear fractures, validated against experimental data. Finally, we show the applicability of the proposed by simulating a real-scale landslide scenario, the Selborne experiment. This final numerical test demonstrates the capability of the method to simulate a landslide detached from the main soil mass as observed in the experiment.

A position-based PFEM formulation for free-surface non-Newtonian flows with application to fresh concrete

2024-12-16T16:22:10+00:00

This work presents a methodology for free surface non-Newtonian incompressible flows using a particle position-based formulation of the Particle Finite Element Method (PFEM) [1], motivated by the simulation of fresh concrete flow. This method is based on the Lagrangian description of the flow and represents the fluid domain by cloud of particles, with a finite element mesh being built, taking the particles as nodes, to solve the motion equations and update the particle positions. To deal with large distortions of fluid flows, such mesh is constantly rebuilt, leading to a method very robust to deal with topological changes within the fluid domain. This approach requires updating the reference configuration, enabling the use of partially or fully updated Lagrangian descriptions. The weak solution is based on the stationary energy principle considering current nodal positions and pressures as variational parameters, deviating from the common practice of employing velocity and pressure as unknowns. Furthermore, smoothed versions of the Bingham and Herschel-Bulkley viscoplastic models are chosen to represent the fresh concrete behavior, keeping stresses independent of strain history and making updating the reference for the fluid simple, without the need for considering the stress distribution in the past reference. The implicit α-generalized strategy is chosen for time integration, enabling second order convergence and ensuring good stability due to the control over numerical dissipation at high frequencies. Finally, selected 2D and 3D examples are simulated to test and verify the proposed methodology.

[1] IDELSOHN, S. R.; ONATE, E.; Del Pin, F. The particle finite element method: a powerful tool to solve incompressible flows with free-surfaces and breaking waves. International Journal for Numerical Methods in Engineering, John Wiley and Sons, Ltd, v. 61, n. 7, p. 964989, oct 2004. ISSN 1097-0207.

Analysis of two-phase flows using position-based PFEM formulation

2024-12-16T16:42:13+00:00

The numerical simulation of flows with topological changes is quite challenging, being approached in the literature by different techniques, highlighting fixed mesh methods, generally based on immersed boundary techniques, and particle-based methods, generally based on a Lagrangian description of the flow. One approach that has proven to be efficient is the particle and finite element method (PFEM), which combines the concepts of particle methods with the finite element method. In this context, this work deals with the development and implementation of techniques for simulating two-phase flows with free surface and topological changes in an alternative formulation of PFEM, where instead of velocities as nodal parameters, particle positions are used. Initially, the domains of the two fluids are represented by a cloud of particles to which the physical characteristics of the fluid they represent are attributed, as well as the initial conditions. A mesh of finite elements is built on this particle cloud to solve the equation of motion in Lagrangian description, with the physical characteristics, as well as the velocity and pressure fields, being interpolated by the shape functions of the finite elements. To avoid large distortions, and also mesh entanglement, at each step this mesh is destroyed and a new mesh is built. Delaunay triangulation is used to construct the mesh, together with the alpha-shape method to define the contours, together with a particle relocation technique that must guarantee the quality of the mesh (avoid extremely small elements or elements with a very small volume ), as well as ensuring the conservation of the number of particles of each fluid. This formulation is tested for cases of free surface flows, such as sloshing in reservoirs, taking into account the water-air interaction, and the results are compared with results from the literature.

Assessing 3D-printed concrete process parameters through Discrete Element Modeling

2024-12-16T16:44:50+00:00

Three-dimensional concrete printing (3DCP) has emerged as a promising manufacturing technique in the civil engineering sector, offering myriad advantages over traditional construction methods. Despite its potential, challenges persist in optimizing the manufacturing stage of 3DCP, including determining optimal fresh concrete rheology, layer thickness, print path, and nozzle characteristics. In this study, we incorporate the Discrete Fresh Concrete model (DFC) into our Discrete Element Method (DEM) code to simulate the rheological behavior of fresh printable concrete during printing, aiming to explore a comprehensive range of process parameters and their combinations to enhance understanding and optimization 3DCP process. Through a series of simulations, we systematically vary some of the process variables such as concrete mix design, nozzle specifications, and printing speed to investigate their influence on the printed output quality. By the obtained results, we aim to identify the key parameters that significantly affect the process, offering insights for refining 3DCP technologies and helping guide their development. We believe methodologies of the type as shown here may be an efficient tool for advancing 3DCP technologies.

Contact enforcement methods comparison in DEM context: application for railway ballast shear test

2024-12-16T16:48:31+00:00

In the Discrete Element Method (DEM) analysis one has to represent the mechanical contact between particles, which is a need in a model representation in a certain geometric scale. This can be done by numerous methods and assuming distinct interface laws. In this work, two distinct contact enforcement methods are compared: the classical penalty-based and the barrier method. The former is available in Rocky DEM commercial software and the latter is implemented in the academic code GIRAFFE. Both methods are compared with respect to their capabilities, advantages and limitations. A classical shear box test is used as a comparison basis. The granular material tested is a sample of railway ballast. Discussions on aspects of convexity or concavity of particles are also made, such as their influences in overall mechanical results.

On an immersed boundary technique for modeling 3D incompressible fluids laden with particles

2024-12-16T16:50:44+00:00

This work presents results from a recently developed three-dimensional immersed boundary technique for modeling 3D particle-laden fluid problems. A classical Eulerian approach is followed to describe the fluid (assumed here as incompressible through Navier-Stokes equations). A discrete element formulation, in turn, is used to describe the particles´ dynamics. The fluid-particle interfaces are treated through Nitsches method, which is an immersed boundary technique whereby we impose the particles´ surface velocities and spins as boundary conditions to the fluid in a weak form. Here, particle-to-wall (i.e., fluid´s exterior solid boundaries) contacts are fully permitted and resolved. In order to assess the accuracy and efficiency of the developed scheme, numerical simulations of 3D unsteady flow of an incompressible fluid loaded with particles are performed and compared against benchmark solutions. This work refers to an intermediate stage of a scientific research that aims to model problems of fluid-particle interaction (FPI) with full particle-to-particle contacts in particle-laden fluids.

Quasi-conformal versus Hertz superposition: a comparison for two-dimensional contact

2024-12-16T16:54:27+00:00

Hertz contact theory results in a relation between the normal contact force and the rigid indentation of the contact surfaces, the force is proportional to the indentation to the power of 3/2, and a semi-ellipsoidal traction distribution. It is a valid theory for non-conformal contact between smooth surfaces (curves in 2D) of elastic bodies. This force model can be derived by considering the Taylor polynomials of degree 2 at the contact point as approximations for the surfaces/curves. In the 2D case, it depends only on the curvature radii of the curves and is undefined when they are equal, the equality of radii violates the non-conformality.
The Hertzian force is usually applied to the contact of solid particles as a model compensating for the small local deformations that occur in the contact region. We consider the 2D contact of a rigid convex particle with a rigid concavity enforcing the contact constraint with a barrier method, an approach that prevents overlapping of the bodies, resulting in a force that acts on the contact point. The geometries and the motion are specially designed to show the coalescence of two contact points into one. It illustrates two possible issues with convex-concave contact, the non-uniqueness of contact points and the conformality. We compare the results with a deformable finite element model for equivalent bodies and motion showing that there is a transition between a Hertzian and a non-Hertzian behavior. We conclude that a criterion for the conformality of curves must include the ever-present gap when a barrier method is used to enforce the constraint and the Hertzian force is not suitable for the coalescence of contact points.

Shear strength reduction in triaxial compression of confined granular materials due to vibrations using the discrete element method

2024-12-16T16:57:32+00:00

When subjected to external forces, the mechanical behavior of granular materials may range from static to dynamic. Unconfined granular beds, for example, are easily fluidized by vibratory loading. Under confinement, this type of material may also exhibit observable effects due to vibrations regarding their volumetric and strength behaviors. In this paper, the shear strength and dilatancy of dry confined granular materials subjected to vibrations are investigated using discrete element simulations of a triaxial cell. The material is first subjected to isotropic compression. Then, with controlled lateral stresses and imposed vertical motion, shear and compressive stresses are applied to a cubic sample. Additional harmonic displacements of the walls induce vertical and horizontal vibrations in the system during the shear tests. Finally, the impact of the amplitude, frequency, and direction of the vibrations on the angles of internal friction and dilatancy of the material is analyzed and compared to observations from the literature.

Simulation of 3D concrete printing using an implicit formulation of the moving particle semi-implicit method

2024-12-16T17:00:40+00:00

Additive construction techniques, such as 3D Concrete Printing (3DCP), offer significant advantages, as reduced material waste, optimized construction times, and the possibility to create complex shapes that would be difficult to achieve through conventional methods. Despite the advances in 3DCP, some challenges persist due to the still incipient development to predict the printing results. The fresh properties of the material play a crucial role. Therefore, in addition to experimental studies, numerical modeling emerges as a valuable tool to investigate the dynamic aspects of the extrusion process in 3DCP. However, the numerical modeling of 3DCP is challenging due to the complex rheological behavior of the self-supporting concrete, which typically exhibits high values of apparent viscosity at low deformation rates. To address these challenges, we adopted the moving particle semi-implicit (MPS) method, which is a particle-based simulation technique suitable for modeling free surface flows and materials undergoing large deformations. As a Lagrangian approach, MPS discretizes the computational domain into particles that move according to the governing equations of fluid motion. The conventional formulation of the MPS presents numerical restrictions when dealing with highly viscous fluids. To assure numerical stability, the semi-implicit approach requires very low time steps, resulting in high processing costs. In this way, this study adopts an implicit algorithm that allows for significantly larger time steps, resulting in reduced processing time compared to the conventional semi-implicit formulation. To validate the implicit algorithm, simulations of non-Newtonian flow between parallel plates were validated using analytical solutions, demonstrating better accuracy at lower Bingham numbers. The 3DCP simulations were conducted to describe the flow of fresh mortar using the Bingham-Papanastasiou constitutive model. The geometry of the 3D model includes the extrusion nozzle and a planar surface where concrete is printed. The numerical investigation involved simulations with different nozzle heights (Hn), printing speeds (V), and extrusion volumetric fluxes (U). The cross-sectional shapes of the extruded layers were compared with experimental data, showing qualitative agreement. The results demonstrate the potential of the implicit MPS method for modeling 3DCP processes.

A fully-hybrid finite element formulation for general compressible-incompressible elasticity problems using de Rham compatible spaces

2024-12-03T14:15:30+00:00

This work proposes a novel fully-hybrid finite element formulation for general elasticity problems, combining $H(\text{div},\Omega)$ conforming vector functions for displacement and $L^2(\Omega)$ discontinuous scalar functions for pressure. This pair is De Rham compatible, which means that within the incompressible regime, the divergence-free constrain will hold strongly at element level. As the $H(\text{div})$ spaces only present continuity of the normal displacements across elements boundaries, the tangential displacement continuity can be weakly imposed performing a hybridization of the shear stresses using $H^1(\partial\Omega_e)$ functions. From past researches conducted at LabMeC, this approach has demonstrated to pose some numerical difficulties as it leads to a saddle point problem with two constraint variables - the pressure and the shear-stresses. In this work, a second hybridization is done by approximating the tangential component of the primal displacement variable using $H^1(\partial\Omega_e)$ space. Two benchmarks are used to verify the developed numerical scheme - the classical Cook's membrane and a tridimensional cantilever beam subjected to an end shear load. Optimum convergence rate is achieved under compressible, quasi-incompressible and full incompressible scenarios.

A Simple Geometrically Exact Displacement Based Shell Finite Element

2024-12-03T14:20:00+00:00

This paper presents a modification of the T6-3iKL element based solely on displacements. It is a nonconforming triangular element with 6 nodes and a quadratic displacement field enhanced by a bubble function. Its coefficients are eliminated with three scalar rotation parameters at the mid-side nodes. The element approximates the Kirchhoff-Love shell model in the large displacement domain with only 21 DoFs . The rotation-continuity between adjacent elements is enforced at mid-side nodes, allowing for multiple branch connections in the mesh. The element allows the adoption of different material constitutive equations. The model is numerically implemented, and the results are compared to varying references in multiple examples, showing the capabilities of the formulation. The original desirable properties of the T6-i3KL element are preserved, which are the lack of penalties or Lagrange multipliers, a simple exact nonlinear kinematics, a relatively small number of DoFs, the possibility of using 3D material models, and is easily connected with multiple branched shells and beams.

A study on Physics-Informed Neural Networks parameters influences in solid mechanics problems.

2024-12-03T14:28:24+00:00

In recent years, Physics-Informed Neural Networks (PINNs) have introduced a novel approach to solving partial differential equations (PDEs) using deep learning techniques. Despite the promising results and rapid advancements in the field, there is a lack of more accurate studies concerning properties related to modeling choices within the deep learning framework, especially, but not exclusively, in solid mechanics problems. In this study, we aim to explore whether the neural network architecture, activation function, optimizer, and sampling method can influence the accuracy of results and training speed for solid mechanics problems. We will focus on elasticity and hyperelasticity problems in 1D, 2D, and 3D dimensions to lay the groundwork for more complex investigations.

A study on the representation of local effects in low order models for thin-walled rod members

2024-12-03T14:31:55+00:00

This work aims to explore alternatives to represent local effects, such as local buckling and plasticity, in low order models for thin-walled rod members. The discussion is carried out on a theoretical-numerical level, and illustrative examples are provided. The techniques that are explored stem from two different approaches: (i) direct enrichment of the rod kinematics and (ii) multiscale methods. Direct enrichment of low order kinematics usually leads to models with optimal computational cost, while still at the downside of having lower-order (still limited) kinematics. Models derived from the Generalized Beam Theory (GBT) are an example of such an approach. Multiscale methods, in turn, rely on results of higher-order theories (e.g., shells and 3D solids) to improve the performance of the lower-order model. The associated computational cost and accuracy vary widely with the imposed coupling level between the different scales. It is possible to have models ranging from full coupling at run-time the so-called strong coupling multiscale method to no coupling at all the higher-order models are used only to compute meaningful mechanical quantities that are passed on to the low order model at some point. The work is an on-going development of a PhD research by the first author, and the results provided so far are only partial.

Analysis of the Creep Curve Reinforced Concrete Beams in Eurocode 2 via the Three-Parameter Model

2024-12-03T14:35:27+00:00

Creep is characterized by progressive deformation that occurs in concrete structures when exposed to constant loads during their operation. Factors such as air humidity, temperature, the initial consistency of the concrete, and the strength of the concrete after curing are decisive for the advancement of this phenomenon and the resulting deformation over time. In reinforced concrete beams, these deformations can increase the final deflection corresponding to the serviceability limit state, as well as cause the failure of the system at the ultimate limit state. The three-parameter model is suitable for describing the viscoelastic nature of many solids and is frequently used to study the phenomenon in various scientific fields. In this work, the creep model could be considered in two ways: first, the mathematical model for creep predicted by Eurocode 2 (European Standard EN 1992-1-1), and second, a three-parameter viscoelastic model whose parameters are adjusted to match the results obtained with the use of Eurocode. A three-parameter mathematical model was developed to accurately represent the creep curve of Eurocode 2 using computational modeling. In this context, this study seeks to understand the effects of creep in reinforced concrete structures through numerical modeling using a three-parameter model of a simply supported beam designed for usual building loads. A basic literature review on creep in concrete structures was conducted, followed by a structural analysis at different times during the commonly accepted life expectancy of these structural systems. In the simulation, the three-parameter model was used as an alternative to the creep calculation prescribed in Annex B of EUROCODE 2. During the analysis process, curves representing the investigated phenomenon were generated, considering different ambient temperature values, with the results presented in the form of graphs and tables. The adopted structural element was a rectangular reinforced concrete beam, simply supported at the ends. The adopted load was uniformly distributed. With this, it was possible to assess the displacements over time, enabling the evaluation of creep deformations at different stages of time under the influence of temperature and ambient humidity.

Finite Element Analysis of a Steel Catenary Riser Transporting Gas-Liquid Slug Flow

2024-12-03T14:38:21+00:00

Steel catenary risers (SCRs) are main offshore structures that transport produced oil and gas from the seabed to floating units such as floating production storage and offloading (FPSO) units. This work analyzes the dynamic behavior of a steel catenary riser transporting internally a gas-liquid slug flow. A finite element formulation for computing elastic large displacement in planar and spatial frames, with consistent numerical implementation, is presented using Updated and Total Lagrangian approaches. To account for geometric changes as external forces are applied, the nonlinear solution is linearized in steps, each representing a load or time step. However, nonlinear terms are included to calculate the stiffness matrix due to the presence of large deformations. The Newmark numerical integrator was used, coupled with the Newton-Raphson method. The two-phase slug flow is model as a homogeneous mixture with timewise and spatially varying density. Numerical results are in good agreement with available experimental data in literature. The effects of the slug flow parameters on the dynamic behavior of the steel catenary riser are investigated.

Finite element analysis of double nanobeams having Pasternak foundation in between

2024-12-03T14:43:07+00:00

Single/double nanobeams (nanowires) have attractive features including reduced sizes and high flexibility and conductivity. As a result, many engineering applications such nanoelectromechanical systems (NEMS) and biomedical devices have been developed in technology industries. Due to the extremely high surface area-to-volume ratio, the properties of nanobeams have size-dependent behavior. In this paper, elastically connected double nanobeams are represented on Eringens nonlocal elasticity theory. Each nanobeam of double beam is modeled as Euler-Bernoulli beam and the interconnecting layer is represented by a Pasternaks elastic foundation model. A four-node double-beam finite element with eight degrees of freedom using approximate functions to interpolate transverse displacements and rotations is derived where both stiffness matrix and load vector are explicitly shown. The present FEM solution is validated by numerical examples where the influence of effects of dimensionless small-scale parameters, boundary conditions, and shear parameter of Pasternak foundation on displacements and stress resultants of double nanobeams are investigated.

Numerical investigation of an orthotropic finite elasticity problem using a constrained minimization theory to prevent material overlapping

2024-12-03T14:48:07+00:00

We consider the problem of an elastic annular disk with uniform thickness in equilibrium in the absence of body force. The disk is fixed on its inner surface and compressed by a uniform pressure on its outer surface. The disk is made of a cylindrically orthotropic material that has a constitutive response that is stiffer in the radial direction than in the tangential direction. Material properties of this type are found in carbon fibers with radial microstructure and some kinds of wood.
In the context of the classical linear elasticity theory, the solution of this problem predicts material overlapping for a large enough pressure, which is not physically acceptable. An approach to prevent this anomalous behavior consists of minimizing the total potential energy functional subject to the constraint that the determinant of the deformation gradient, J, be positive. We have used this approach to eliminate material overlapping, yielding solutions with J not close to one, which contradicts the basic assumption of infinitesimal strains upon which the classical linear theory is founded.
In this work, we extend our investigation to the nonlinear elasticity theory. Necessary conditions for a deformation field to be a minimizer were found elsewhere. It includes a nonzero Lagrange multiplier that represents a reaction pressure to prevent material overlapping. We use a finite element formulation to find that, differently from its linearly elastic counterpart, the Lagrange multiplier field associated with the local injectivity constraint remains bounded. In addition, we obtain convergent sequences of approximate solutions of the disk problem formulated with both this constrained minimization theory and a compressible and orthotropic Mooney-Rivlin material. This material has certain growth conditions on the deformation field that prevents material overlapping in classical problems of mechanics. Both sequences yield convergent solutions that are in very good agreement with each other.

Strategies for the development of finite elements for non-prismatic frames

2024-12-03T14:50:50+00:00

Non-prismatic structural elements, often referred to as beams with variable cross-sections, constitute a special class of slender structures. These types of structures capture the interest of engineers and architects due to their ability to optimize geometry to meet specific needs, such as weight reduction, material consumption, environmental impact, and costs. Despite the advantages that engineers can gain from using non-prismatic structural elements, modeling these structures poses non-trivial challenges, resulting in inaccuracies that may compromise the benefits offered by such structures. Taking this into consideration, this work presents an innovative approach to obtain the displacement solution for non-prismatic beams, obtaining the elastic stiffness matrix through the virtual work principle, using the kinematics of Timoshenko's theory. This proposed formulation is independent of bar discretization to achieve an analytical result. This is due to the absence of considering any additional approximations beyond those already contained in the analytical idealization of bar behavior, resulting in a nearly natural discretization of the structure.

Structural analysis of beams on masonry: comparison between analytical and computational modeling

2024-12-03T14:53:56+00:00

Structural masonry stands out in building projects as an efficient and versatile solution due to its function not only in sealing environments, but also in supporting and resisting different types of loads, in addition to presenting fast construction. The stiffness of masonry plays a crucial role in the global behavior of the structure, as it contributes to the safety and resistance of the set, thus obtaining a more robust and resilient system. Thus, this work aims to study analytically and computationally beams on masonry using elastic supports in the calculation of bond beams used in structural masonry. In the end, the analysis highlighted the influence of masonry stiffness on the elastic line and the distribution of sectional forces in the beam. Comparison with the numerical model in the Ftool software validated the analytical results and provided a detailed visualization of the beams behavior and the masonry that supports it. In this context, the study in question constitutes an excellent application of concepts with an interesting use to the technical community and the computational modeling proved essential to deepen the structural analysis in question.

Three-dimensional finite-volume theory for elastic stress analysis in solid mechanics

2024-12-04T10:50:12+00:00

The finite-volume theory is a powerful numerical technique for structural analysis in solid mechanics and has emerged as an alternative to the finite-element method. The finite-volume theory is an equilibrium-based approach that employs surface-averaged tractions and displacements acting on the faces of a subvolume. In addition, this theory employs the equilibrium equations at the subvolume level and continuity conditions between adjacent subvolumes along subvolume faces. The finite-volume theory has been successfully used for two-dimensional structural analyses. However, in the context of three-dimensional solid mechanics analysis, this numerical technique has encountered instability problems related to the interpretation between adjacent subvolumes' faces. These problems result in the singularity of the global stiffness matrix, which has delayed the publication of a three-dimensional version of the finite-volume theory for continuum elastic structures. These numerical instability problems can be solved by employing a modified stiffness matrix, where the Tikhonov regularization method is used to artificially add minimal stiffness in the main diagonal of the global stiffness matrix. This contribution proposes the stress analysis of three-dimensional continuum elastic structures by the finite-volume theory, where problems with analytical solutions are employed for verification.

Young's modulus identification via finite element model updating using full-field data from a 3-point bending test

2024-12-04T11:05:27+00:00

High-temperature applications usually require refractory materials because of their thermal and physical properties. The mechanical design of structures with these materials demands their elastic properties to be well known. However, evaluating these data at high temperatures through common experimental methods such as strain gauges, not only generally furnishes single-point measurements but may also become impossible at higher temperatures due to the required contact with the specimen. Non-intrusive image-based techniques are thus welcome to overcome these limitations, allowing full-field displacement and strain measurements, calculated from images gathered with cameras placed far from the sample. In this context, the article aims to assess the Young's modulus of a refractory material by combining Digital Image Correlation (DIC) and a Finite Element Model Updating (FEMU) approach. DIC allows the computation of the displacement field over a region of interest for each loading level (i.e., acquired picture), enabling different parameter evaluations from a single test. Pictures are gathered through a camera setup in a three-point bending test, and the DIC analysis is performed in MATLAB with the Correli framework. The identification problem is modeled using the finite element software Abaqus and its Scripting Interface in Python. A sensitivity analysis is performed to ensure the successful identification of parameters. Then, the elastic parameters are iteratively updated until computational results match the experimental displacement field and the resultant reaction forces (FEMU-UF). Both displacement and force residue involving the comparison of the computational model and experimental results are discussed. It is shown that the richness of full-field measurements is helpful to identify different parameters from a single experiment.

A co-rotational finite element for nonlinear analysis of hollow section steel frames accounting for local buckling via lumped damage mechanics

2024-12-09T12:23:00+00:00

To reduce engineering costs, the search for more efficient materials and design concepts leads to slender structures. Consequently, the need for geometrically nonlinear analysis is becoming increasingly important. Besides, the phenomenon of local instability becomes more evident when dealing with structural components with hollow cross-sections composed of slender plates and shells. It is usual to employ elastoplastic shell finite element models for dealing with such problems, which leads to analyses with high computational costs. Therefore, this paper proposes a geometrical nonlinear beam finite element, developed for the nonlinear analysis of hollow section steel frames, accounting for local buckling. The finite element is locally formulated as the traditional linear Euler-Bernoulli beam element. A co-rotational description of motion is then employed to account for large displacements and rotations. The local buckling phenomenon is taken into account by a lumped damage model, which concentrates the effects at inelastic hinges. The inelastic hinge´s yield functions are defined in terms of the co-rotational nodal axial forces and bending moments, as well as in terms of damage variables. The local buckling of the hollow sections is accounted by the adopted damage evolution law. The inelastic rotations are governed by the normality rule and the evolution laws of the internal variables. A predictor-corrector algorithm is employed at element level, whereas the Newton-Raphson method solves the global nonlinear equilibrium equations. To assess the accuracy of the proposed model, the numerical results obtained in this study are compared against available numerical and experimental responses. The numerical results show good accuracy, which corroborates that the proposed model might be used in practical applications.

Analysis of local buckling in steel Rectangular Hollow Section via Lumped Damage Mechanics

2024-12-09T12:28:51+00:00

This paper presents a lumped damage model to analyse local buckling in steel Rectangular Hollow Section (RHS). In this model, the nonlinear and damage effects of the planar frame element are concentrated in plastic hinges located at the ends of the element, significantly reducing the computational cost of the analysis. Thus, plasticization is represented by the formation of plastic hinges, while local buckling is described by the addition of a damage variable to these hinges. The analysis adopts a step-by-step procedure to consider geometric nonlinearity, solving the problem sequentially and considering the change in the geometry of structural elements. To evaluate the accuracy of the model, the numerical results were compared with experimental results, in which steel RHS were subjected to compressive axial force with monotonic bending moment loading. The results indicate that the numerical model presents satisfactory behaviour in relation to the experimental results.

Homogenised damage model for concrete

2024-12-09T12:33:17+00:00

This work deals with numerical simulation of the mechanical behaviour of concrete using a homogenised damage model based on the concept of Representative Volume Element (RVE). The RVE is composed of phases with different mechanical behaviours leading to heterogeneous characteristics on the microstructure level. We adopt a simple damage model capable to simulate the behaviour of the cement paste and transition zone while the aggregates are modelled as linear elastic material. To perform the numerical analysis, a based homogenisation technique is used to obtain a damage model that represents the macromechanical behaviour of the material. Results show the capabilities of the model to capture complex phenomena including a comparison with experiments tests performed in concrete specimens.

Numerical modeling of localization bands with mesh-independence using lumped damage mechanics

2024-12-09T12:36:49+00:00

The Lumped Damage Mechanics for continuous media has been successful in describing the nonlinear physical behavior of engineering problems. The approach utilizes basic concepts from fracture and classic damage mechanics. In this regard, material degradation in two-dimensional media is computed from the evolution of localization bands concentrated on the finite elements faces. The growth of these bands occurs based on the Griffith criterion. In this work, a nonlinear evolution law with exponential softening is adopted in order to accurately describe quasi-brittle failure behavior. Numerical solutions show mesh-independence of the proposed approach as well as the reproduction of the size-effect phenomenon. Finally, it was possible to reproduce experimental behavior in terms of equilibrium trajectory and cracking pattern of the failure region.

Reinforced concrete plates: cracking and ultimate load through Lumped Damage Mechanics

2024-12-09T12:43:06+00:00

In structural analysis, it is crucial to accurately characterize the nonlinear behavior of structures. This behavior may result on strain localization phenomena, that may lead to collapse processes. Lumped Damage Mechanics (LDM), one of the more recent nonlinear theories, has shown promise for a variety of applications. It is applied to frame elements, for static and dynamic analysis, in reinforced concrete, plain concrete or steel structures, or in continuous media, with plate elements for plain concrete or bending plate elements, for reinforced concrete slabs. This paper presents the study of reinforced concrete slabs using LDM. Damage and plastic rotations are the internal variables of the problem that characterize concrete cracking and reinforcement yielding, respectively. The results numerically obtained were confronted with experimental ones. It was observed that the model is highly accurate in describing the initiation and propagation of cracks, as well as identifying the collapse mechanism, in addition to precise Load vs. Deflection results, close to the experimental values.

Seismic vulnerability of steel tubular structures based on local Buckling driving variables

2024-12-09T12:51:48+00:00

Performance-Based Earthquake Engineering (PBEE) is computationally demanding, due to the multiple high-fidelity non-linear dynamic structural response analyses required to compute fragility curves. In this manuscript we propose an efficient procedure to obtain fragility curves of complex tubular structures prone to fail due to local buckling using a model based on the Lumped Damage Mechanics. A state variable characterizing local buckling is employed as engineering demand parameter in PBEE. This state variable is a scalar, derived from lumped damage mechanics and taking values between 0 and 1, which characterizes the degree of local buckling (LB). A procedure to identify and define global collapse mechanisms using the local buckling state variable at the nodes is proposed, which serves as the EDP for computing the structure's fragility curves. To evaluate the seismic vulnerability, incremental dynamic analyses are conducted. The main results demonstrate efficiency of the mechanical model in a PBEE framework, and that the internal variables indicating local buckling can be considered objective indicators of collapse for Tubular complex steel frames. Results show how to identify the global failure mechanisms that are more likely to appear for each frame.

UHPFRC structural analysis from a geometrically exact Extended Lumped Damage Mechanics approach

2024-12-09T12:56:20+00:00

The use of ultra-high-performance fibre-reinforced concrete (UHPFRC) has significantly increased in the recent years. However, the accurate mechanical behaviour modelling of this complex material is still a challenge in the present. Because the materials high load-bearing capacity and the presence of fibbers, this type of problem experiments large displacements before the failure. In this study, the material damage description has been performed by the Extended Lumped Damage Mechanics. Additionally, an approach based on the nodal positions of the Finite Element Method has been utilised, which makes the formulation geometrically exact. Thus, this study evaluates the failure of structures composed of UHPFRC, accounting for the effects of material and geometric nonlinearities computed by the Extended Lumped Damage Mechanics and the Finite Element Method based on positions, respectively.

A Case Study of Artificial Neural Networks Usage for Rate of Penetration Prediction with Offset Wells Data

2024-12-09T13:01:31+00:00

The oil and gas industry is constantly motivated to implement strategies focusing on cost management and operational optimization to maximize productivity. Rate of Penetration (ROP) serves as a key performance metric, reflecting the speed at which a drilling bit penetrates subsurface formations. Increasing ROP can minimize costs by reducing drilling time. ROP prediction models aid drilling optimization plans since accurate models are required to find ideal controllable parameters to increase ROP using optimization algorithms. Drilling characteristics that significantly influence ROP include bit type, formation properties, and operation parameters, such as Weight on Bit (WOB) and Rotations per Minute (RPM). The number of significant parameters makes it difficult to develop analytical expressions for predicting ROP. The present work investigates the applicability of Artificial Neural Networks (ANN) for ROP prediction using public data from three wells extracted from the Volve oil field in the North Sea. The adopted strategy is to learn from offset wells, which means using data from two wells to predict the ROP for the third. This approach helps to address a practical scenario where historical data are used to make predictions for a new well in a close region. This study uses MLP (Multilayer Perceptron) networks with WOB, RPM, Torque, Fluid Flow rate, and Delta-T Compressional as features, and the training process is conducted using the GridSearchCV method for hyperparameter tuning, comparing different model architectures to improve results. To assess the final performance of the model, metrics such as Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) are applied to the tested well. The results show that the developed model can capture ROP patterns without requiring any data stratification of the two wells regarding lithology information.

A deep learning approach for detection and location small portions of water in aerial images acquired by drones

2024-12-09T13:10:33+00:00

Drones have been used to automatically identify objects and scenarios (normally water tanks, buckets, plant pots, and other containers contained in open-air trash) that characterize potential breeding sites of mosquito, such as Aedes aegypt, from the acquired images. However, despite knowing that water stagnation is an essential condition for mosquito breeding sites, computer vision systems proposed in the literature for automatic image analysis do not include the detection of water in suspicious objects and scenarios, which constitutes a technical limitation for the effective use of drones in vector monitoring and control actions. In this work, a method based on deep learning is proposed to detect and locate small portions of water in multispectral images acquired by drones. To carry out the experiments, we composed a database of multispectral images acquired from simulated scenarios containing small containers with and without water in a controlled environment. The high rates obtained in terms of the mAP50 metric (above 90%) in computational experiments using a convolutional neural network YOLOv8 to segment the images confirm the potential of proposed approach to increase the technical viability of existing computer vision systems, making them more effective in combating mosquito breeding sites, bringing important contributions to the public health area.

A Stacked Generalization Ensemble Method for Rate of Penetration Prediction

2024-12-09T13:15:01+00:00

Efforts to reduce drilling costs and duration have made accurate predictive models for rate of penetration (ROP) essential in the drilling industry. These models assist decision-making concerning parameters that affect drill efficiency. Utilizing advanced machine learning algorithms, such as ensemble methods and artificial neural networks, has become a clear trend aimed at enhancing predictive precision. In this study, a stacked generalization ensemble model is introduced to improve ROP prediction performance. The adopted approach combines four base learners, namely random forest, gradient boosting, linear regression, and artificial neural networks, into a meta-model architecture. The resulting meta-data from these models are used to make the final ROP prediction using a linear regression algorithm. Drilling data from two wells in the Volve oil field are used for training, including various operational and formation-related parameters, such as average surface torque, weight on bit, average rotary speed, mud flow rate, and delta-T compressional. The performance of the model is evaluated on an unseen well, using error metrics such as mean absolute error (MAE) and mean absolute percentage error (MAPE). The proposed approach has demonstrated superior performance compared to the base learners, as indicated by the comparative analysis. This suggests its potential to enable more accurate predictions, consequently improving the efficiency of the drilling process.

Analysis of the Citation Network in Scientific Journals

2024-12-09T13:18:47+00:00

This article presents an analysis of the citation network in scientific journals, with the aim of understanding citation patterns between journals and identifying trends in authorship and citation. To achieve this goal, an extensive set of citations of scientific articles published in journals by Brazilian researchers was compiled. Using network analysis techniques, the citations were modeled as a graph, allowing a systematic visualization and analysis of the citation relationships between journals. The results revealed significant findings on the dynamics of citation in the Brazilian scientific community.

Application of Nonlinear Optimization in Flight Path Reconstruction of a Sub-scale Aircraft

2024-12-09T13:22:28+00:00

One key challenge in working with free-flight test data is ensuring its compatibility with the dynamic systems of sub-scale unmanned aircraft. This is crucial to avoid errors in measurements, bias, or scaling issues that could compromise the integrity of the estimated results. We refer to this initial processing step as data compatibility checking, a rigorous process that forms the foundation of our research.
Typically, this verification process involves flight path data reconstruction (FPR) predicated on estimating the aircrafts flight kinematics. The predominant methodologies encompass the stochastic approach, the Extended Kalman Filter (EKF), and the deterministic approach, employing the Output Error Method (OEM). In this research, we propose to approach the problem from the perspective of a nonlinear optimizer to estimate the reconstruction of data derived from free-flight tests of a sub-scale aircraft.
The nonlinear optimizer we employ in this research was designed to verify the authenticity of the data representing the aircraft's actual flight. It does this by comparing the measurements of attitude angles, accelerations, and velocities with the expected kinematic behavior of the aircraft. This rigorous evaluation process ensures that the reconstructed data is as close to the actual flight as possible, enhancing the reliability of our results.
The sub-scale model deployed in these tests was engineered to emulate the dynamic characteristics of a full-scale aircraft, utilizing the Froude number criterion for appropriate scaling. The chosen aircraft for this project was a Cessna 177B, and the sub-scale aircraft was developed by the Aeronautical Systems Laboratory (LSA) at the Aeronautics Institute of Technology (ITA).
This study will delineate the outcomes achieved through FPA employing OEM techniques and compare these results with the studies derived from the proposed nonlinear estimation method.

Automating Rock Classification: A Vision Transformer Approach in Brazil's Ornamental Stone

2024-12-10T12:18:31+00:00

The ornamental stone sector in Brazil is renowned for its diverse array of rock types. However, the classification of these rocks largely relies on subjective assessments and the specialized expertise of professionals. This dependence has spurred interest in employing artificial intelligence (AI) to enhance the image classification process in this field. This study establishes a comprehensive labeled database of ornamental rock images, containing 1,798 images divided into 12 distinct classes, and makes this database publicly available. Additionally, it proposes the use of a Vision Transformer network, specifically the SI-ViT (Shuffle Instance-based Vision Transformer), which was originally developed for the automated classification of pancreatic cancer images, for this task. In comparative evaluations, the SI-ViT network demonstrated superior performance, outperforming established models such as Vgg16, Vgg19, Resnet50, Resnet101, Xception, and Inception v3, with an impressive accuracy rate of 99.68%.

Brazilian academic mobility: exploring the journey towards training

2024-12-10T12:26:37+00:00

The exodus of individuals for various reasons or circumstances has increased significantly in recent years in Brazil and the world. One of the reasons identified for this migratory flow is the academic training of these individuals, who seek to train in better quality educational institutions. In this context, this work aims to analyze how the scientific exodus occurs in Brazil, in which individuals from different locations in the country migrate in search of better academic training. Therefore, in this study, we analyzed how the Brazilian scientific exodus occurs. To do this, it was necessary to extract academic training data from the CVs of individuals registered on the Lattes Platform. Therefore, all individuals with completed doctorates were selected, aggregating 381,463 CVs. The choice of this group is justified because it is the group with the highest level of completed academic training, and which has the characteristic of having recently updated data in their CVs. Initially, the data was filtered, selecting the attributes relevant to the research, and finally, the data was processed with the aim of finding the geographic location of the institutions in which the individuals trained. As initial results, it was possible to characterize the data collected on the Lattes Platform, measuring distances traveled by individuals throughout their academic training, as well as flows followed by doctors at state level and an analysis of the internationalization process of doctors Brazilians. Link networks were created demonstrating the main locations occupied by doctors during their academic training, as well as the connections between these locations. Possible indicators were subsequently extracted and analyzed, seeking justifications for the choice of individuals to migrate to locations during training, such as a correlation between the results found and some indicators extracted from open access data repositories, such as population and undergraduate and postgraduate courses. -graduation. Therefore, it was possible to present an unprecedented portrait of how the Brazilian scientific exodus occurs.

Checking the Status of High Voltage Disconnection Switches Using Siamese Convolutional Neural Networks

2024-12-10T12:30:10+00:00

A high voltage power substation is an electrical installation made up of equipment responsible for transmission and distribution of energy for voltages above 69kV and below 230kV. Necessary to keeping our homes and industries running, a substation has various power equipment such as circuits breakers, power transformers and disconnection switches that guarantee its operation. These devices can be controlled locally or remotely way, either through control systems or manually by a human operator.
One of the fundamental pieces of equipment to guarantee the operation of a substation is a disconnection switch. Disconnection switches are electromechanical equipment composed by moving parts, in a conventional substation. This equipment is subject to mechanical efforts, vibration and temperature. The wrong functioning of a disconnection switch can cause major losses for the company, from equipment downtime to a complete lack of power to the plant.
With the aim of contributing to avoiding failures in the operation of an industrial substation, this work proposes the use of artificial intelligence (AI) and machine learning techniques, through computer vision based on the Siamese convolutional neural network to verify the disconnection switches opened and closed status of a power substation in a steel industry.

Collection and Processing of Data from Articles in Scientific Events

2024-12-10T12:35:45+00:00

Several studies focus on exploring the behavior of scientific evolution. For this reason, one of the main means of scientific communication today is events, in which diverse and valuable works are generated, also enabling fast communication and possibilities for argumentation. However, most works that evaluate scientific production in scientific events generally have specific repositories as a data source, often restricted to some areas of knowledge. Although such works present interesting results, no studies were found that encompass events in general, with a large number of publications or that address different areas. In this context, this work aims to analyze the scientific production published in the annals of events of the group of physicians who have CVs registered on the Lattes Platform. The data used were extracted from the Lattes Platform in January 2021, so that all the selection and processing of the data of interest could be carried out. Therefore, this work has the general objective of analyzing the scientific production published in events, understanding how Brazilian scientific production occurs in this means of dissemination, using bibliometric metrics in the data extracted from the curricula registered in the Lattes Platform.

Contributions of the Analysis of Academic Trajectories to Educational Management

2024-12-10T12:40:58+00:00

Educational management is present and necessary in contemporary times, given the ability of the techniques and dynamics proposed to guide education systems and maximize the investments made. Given this fact, conclusions about social phenomena that can be guaranteed by analyzing academic trajectories are of significant relevance, since they reveal information regarding the effectiveness of education centers, the means of re-establishing training paths that have been broken and the variables in the context of individuals that influence the teaching-learning route. In view of this, this work aims to carry out a case study with an educational institution, so that results can be extracted from the investigation of educational histories that collaborate with the institution's strategies. Based on CVs from the CNPq's Lattes Platform, the research was structured around the stages of Data Selection, Filtering, Summarization and Stylization, with interpretations of educational profiles, geographical mobility for academic and professional purposes, migration between institutions and other related data, from an understanding that ranges from high school to doctoral level. In this way, conclusions were reached, in the first phase of the work, regarding the scope of the institution's pedagogical projects and the spatial retention of qualified individuals by the campuses.

Data-Driven Modeling of Cold-Formed Steel Bolted Angle Connections under Axial Tension using Artificial Neural Networks

2024-12-10T12:45:37+00:00

Given that steel is one of the main structural materials in civil engineering, it is important to understand its mechanical properties and failure mechanisms. L-shaped laminated steel elements, known as angles, are commonly bolted to other metal elements to make connections in steel structures. When these elements are connected by only one of its legs and are subjected to axial tension, the failure of the angle can be caused by rupture of the section where the holes are located. In this case, there is influence of complex phenomena such as shear lag, therefore a reduction factor is applied to the resistance of the section. The general theme of this work is the use of Artificial Neural Networks (ANN) as an approach to the study of the load capacity of cold-formed steel bolted angles connected by one leg and under axial tension. Although this class of techniques do not provide a simple regression equation, they are powerful tools in Machine Learning (ML), having the ability to model any arbitrarily complex nonlinear problem. In this work, a dataset is built with samples from different numerical and experimental works, collecting steel angles geometric parameters, tensile strength of the material and ultimate capacity regarding net section failure. The data-driven models are trained with 80% of the data, tested with 20%, validated with 5-fold cross-validation and their hyperparameters are tuned with Bayesian Optimization. Feature generation, selection, and importance algorithms are implemented, hoping to achieve more accurate, less complex and more interpretable models. ML models predictions are compared with the ones given by the equations of Eurocode-3, Brazilian NBR 14762, American Iron and Steel Institute (AISI) and Australasian AS/NZS Standards. The comparison shows mostly superior results in the ANN models, proving the competitiveness and effectiveness of Machine Learning techniques and data-driven modeling.

Deepfake detection using Eulerian video magnification and Deep Learning

2024-12-10T12:50:35+00:00

The Internet witnesses millions of video views every minute in the contemporary landscape of extensive data proliferation and ubiquitous social media use. In this context, the burgeoning advancements in deepfake technologies introduce security and privacy concerns. These technologies facilitate manipulating video and audio content to an extent where someone can seamlessly replace one persons visage with anothers, or entirely synthetic videos can be crafted using real individuals voices and appearances, potentially deceiving viewers. Consequently, the malicious exploitation of deepfakes has caused apprehension due to its potential adverse societal repercussions, including, but not limited to, harm infliction, extortion, and reputational jeopardy. This study seeks, within the realm of deepfake detection, to evaluate the efficacy of Eulerian video magnification (EVM), a technique that accentuates subtle cues and motions, typically imperceptible to the naked eye. To this end, we propose the use of hybrid architectures comprising Convolutional Neural Networks (CNN) and Vision Transformers (ViT) with magnification techniques. Subsets of the FakeAVCeleb dataset, including authentic and manipulated videos, will train, validate, and test the model. The evaluation of the model will employ metrics such as accuracy, precision, recall, and the F1 score, with results compared to the existing literature.

DETERMINATION OF CRITICAL PLANES IN MULTIAXIAL FATIGUE WITH ESTIMATION OF SHEAR STRESS AMPLITUDE IN MECHANICAL COMPONENTS THROUGH DIFFERENT FAILURE CRITERIA

2024-12-10T12:54:03+00:00

Fatigue strength analysis in mechanical components is fundamental in the development across various industrial and economic sectors worldwide. Different materials are used in the construction of structural and mechanical elements subject to intermittent and intense usage under various loading conditions. The evaluation of fatigue strength of materials is widespread in diverse computational research, which presents various characteristic parameters according to fatigue strength and material failure criteria. The presence of shear stresses in materials, mean stresses, their amplitudes, and critical planes of rupture seek to identify the assessment of the structural reliability of these elements. The Susmel and Lazzarin Method and the Findley Method, together with the evaluation of the shear stress in a loading history in materials, are capable of indicating, according to stipulated criteria and parameters, error indices, and affirming the accuracy of the fatigue strength capacity of materials. Thus, the determination of fatigue strength can indicate better design, construction, and maintenance parameters for studied elements.

Early detection of university dropout with cluster analysis and machine learning classification techniques

2024-12-10T12:56:34+00:00

This study addresses the challenge of student dropout in the Faculty of Sciences and Technologies of the National University of Caaguazú in Paraguay by constructing an early warning model based on academic factors. Employing a data science methodology, academic records were characterized and analyzed, using techniques such as cluster analysis and the elbow method to optimize student segmentation. Several predictive machine learning models were adjusted, including logistic regression, decision trees, and k-nearest neighbors, which were evaluated using precision, recall, and F1 Score metrics to determine their effectiveness in classifying academic statuses.
With the cluster analysis, four well-defined clusters were identified. These were characterized through cluster analysis into: early dropout, late dropout, thesis stage and graduate.
The models had an average performance of 88% accuracy. These models were trained only with academic data (grades obtained in the courses). The data used covers four careers from 2012 to 2021: Computer Engineering, Civil Engineering, Electronics Engineering and Electrical Engineering.
An early warning model for student dropout in the Faculty of Sciences and Technologies was built, using estimates based on relevant academic factors extracted from the faculty's academic database.
In the study carried out, an effective characterization of the academic database was achieved using advanced data science techniques. Initially, the elbow method was used to determine the optimal number of clusters, identifying four different groups. The student population was segmented into: graduates, early dropouts (students who dropped out before five years of their degree), late dropouts (those who left their degree after five years) and students who completed the curriculum but have yet to present their Project. End of Degree. This detailed analysis allowed us to better understand the academic distribution.
Predictive machine learning models were tuned and evaluated using four different data configurations in a series of training and prediction experiments. The most effective method was the third experiment, which combined data from students in states 2 and 5 through the third year. This combination created a more homogeneous and representative data set of academic success, allowing the models to more accurately identify the patterns and key factors that predetermine successful academic outcomes.
With the selection of the third experiment, for the different majors, the optimal models varied: for Computer Science, the best model turned out to be K-Nearest Neighbors (KNN) with an accuracy, precision and recall of 0.896 and F1 of 0.895 in contrast to the one that had The lowest performance was Decision Tree (DT) with an accuracy and recall of 0.793, a precision of 0.853 and F1 of 0.814; for Electricity and Civil, the Decision Tree (DT) model was the most effective, in electricity with an accuracy and recall of 0.980, a precision of 0.981, and F1 of 0.979, in the civil career with an accuracy and recall of 0.968 , a precision of 0.976 and F1 of 0.970, however, the one that had the lowest performance in the two races was KNN, respectively for the Electricity race with an accuracy and recall of 0.823, a precision of 0.805 and F1 of 0.814 and in the Civil race with accuracy, recall and F1 of 0.843 and a precision of 0.850; and for Electronics, Logistic Regression (RL) and K-Nearest Neighbors (KNN) demonstrated better performance with accuracy and recall of 0.888, with a precision of 0.898 and F1 of 0.882, unlike the Decision Tree Model (DT) demonstrated lower accuracy and recall of 0.777, improving a little in precision with 0.809 compared to the RF and SVM models that demonstrated a lower precision of 0.740. The conclusions highlight the performance of different models in early identification of at-risk students, further proposing the integration of socioeconomic and psychological factors for future research in the field.

Early Warning Panel

2024-12-10T13:04:24+00:00

Artificial intelligence methods are normally used to make predictions, classify objectives, group and optimize human work and minimize uncertainty for decision making, but despite the advantages they offer, they are not entirely friendly or accessible to the majority of people. That is why we use an artificial intelligence model, the LSTM model, it is used to predict time series and can be extended to any endemic disease for which there is enough data for deep learning of an artificial intelligence model, which which will allow us to draw up plans to combat and confront this disease in our country.
Paraguay is a country that epidemiologically is considered endemic for some arboviruses, we can mention: Dengue with cases since 2009, Chikungunya since 2013 and Zika since 2015.
The epidemiological indicators provide us with information on the epidemiological situation of Dengue in Paragua, the indicators that we collect through a bibliographic review and that found in our Early Warning Panel were identified through a bibliographic review, the search engine used was Google Scholar, the inclusion criteria were: articles that mention epidemiological indicators and the way in which they are calculated. Finally, the epidemiological indicators used were: Incidence, bitting rate, probability of infection from mosquito to human, probability of infection from human to mosquito.
For the implementation of the prediction in our Early Warning Panel, the LSTM model was defined, pre-training. It is one of the most advanced and successful deep learning architectures for time series prediction.
For the evaluation of our Panel, a survey was developed for potential users in order to evaluate the usability, relevance and performance of the system. Experts in epidemiology and control of infectious diseases, with experience in managing dengue cases, were selected. A representative sample was sought that included epidemiologists, doctors specializing in tropical diseases, data analysts, and public health officials. With the potenticial users was evaluated: Usability, Relevance and Performance.
The results of this evaluation revealed good acceptance by the experts, who highlighted the clarity and usefulness of the information presented. These findings confirm the effectiveness and relevance of the epidemiological panel as a useful tool for the surveillance and control of dengue.
The panel is available at: https://alertatemprana.vercel.app

Efficient Market Hypothesis in Brazilian and American Markets: A Study Using Time Windows

2024-12-10T13:09:09+00:00

Financial markets play a fundamental role in contemporary societies, directly influencing social well-being. Traditionally, economists have sought to understand the underlying processes driving the dynamics of these markets. However, in recent decades, there has been a significant increase in the contribution of researchers from various disciplines, including physics, mathematics, and computer science. In this context, econophysics has emerged, employing typical physics methods to study systems commonly investigated in economics and finance.
Financial markets are recognized as complex systems, whose behavior can be observed through indicators such as prices and trading volumes. However, the statistical characterization of these time series remains an ongoing challenge, as does understanding their emergence from microeconomic relationships.
The Efficient Market Hypothesis (EMH) suggests that future price time series in financial markets contain little useful information for prediction, making it extremely difficult. In this study, we conduct analyses of financial time series to investigate this expectation. We use a return trend prediction model based on differential equations with a focus on time segmenting. The accuracy of this model can provide insights into the presence of the information suggested by the EMH in financial time series.

Identifying the Main Research Topics in Open Access Journals: An Analysis with Bibliometric Metrics

2024-12-10T13:12:16+00:00

The traditional printed format of science communication is gradually giving way to new electronic formats, due to the rise of information and communication technology. In the context of research and scientific studies, scientific communication appears today as a central element at different levels of discussion, with emphasis on the dissemination of scientific articles in journals, currently one of the main means of communication for this purpose. In the context of this work, in order to better understand the main research topics investigated by Brazilian researchers in open access journals, the curriculum data repository of the Lattes Platform was used. Currently, the Lattes Platform has a set of more than 7 million registered CVs.

Intelligent analysis system and automatic conference of train formations at EFVM using computation vision

2024-12-10T13:15:00+00:00

Every wagon and locomotive has an alphanumeric code on each of its longitudinal faces that identifies and distinguishes it from any other railway vehicle on the Brazilian network. The train formation process consists of joining one or more sets of wagons and locomotives, which will be used to transport ore, and is an inherent step in the railway logistics process, where resources (wagons and locomotives) are joined or separated due to physical limitations of ore loading terminals. At the end of a formation we have a sequence of vehicles ordered and sequenced by their codes, and from this we are able to identify the characteristics of the ore being transported. The activity of forming trains is very important in railway operations, and requires attention and care, as they involve operational, fiscal and commercial risks, which, if not mitigated, can bring irreparable negative results. Such results range from fines imposed by government agencies and even potentially catastrophic accidents, thus putting the lives of employees, communities, partners and the environment at risk. As an example, we have the possibility of an ore composition being delivered with the wrong wagon sequence to a customer, and it entering the production line of a steel mill, which could cause an explosion due to the use of a type of ore wrongly added to a mixture in the blast furnace. Faced with such high risks, the activity of checking the trains after the maneuvers to separate and join the wagons becomes even more important. Making a cut in the Iron Ore circuit on the Vitória a Minas Railway, around 7,800 wagons are allocated daily per train, making checking all formations/compositions a very laborious task. The present work consists of the development of an intelligent system, based on Computer Vision, which automatically checks the alphanumeric codes of train compositions, aiming to guarantee the correct sequence of wagons in each formation of ore trains in the Tubarão yard in Vitória a Minas Railway.

Invisible Colleges and Technical Production: A Study of Patents in Brazil

2024-12-10T13:18:00+00:00

Analyzes of scientific collaboration networks have been extensively explored in research from different areas of knowledge, in view of their ability to identify how groups of researchers have carried out their work collectively. Such studies make it possible to identify how collaboration between individuals occurs through analyzes based on social network metrics. In this context, new studies have been proposed in order to analyze collaboration in the development of technical products, with data on patents being studied in most studies. This type of analysis is relevant because it makes it possible to understand the collaboration process in the proposal of new inventions. In this work, initially a general characterization of the group of individuals analyzed is presented, and afterwards, a global and temporal analysis of the collaboration network is performed in the proposal of patents of Brazilian individuals with curricula registered in the Lattes Platform. For that, all the patents registered in the curricula of these individuals were used for the identification and characterization of the collaboration networks. As a result, it is possible to see how collaboration in the proposed inventions of the analyzed set has been intensified over the years, with an emphasis on the institutions and areas of expertise of each inventor.

Long short-term memory neural networks applied in demand forecast in the retail market

2024-12-10T13:21:00+00:00

Sales forecasting is an indispensable component of the retail industry, underpinning strategic decision-making and operational planning, and is crucial for maintaining financial stability and facilitating business growth. While traditional statistical methods have been widely utilized to address issues in time series analysis, they often fall short when confronted with high-dimensional, complex, or dynamic non-linear relationships between variables.

In this context, Long Short-Term Memory (LSTM) networks offer significant advantages due to their capability to retain information over prolonged periods. These qualities make LSTMs particularly suited for handling scenarios characterized by complexity and dynamic interactions within the data.

This study evaluates the efficacy of three distinct LSTM architecturesVanilla LSTM, ConvLSTM, and CNN-LSTM Multiscalein forecasting future sales. For a comprehensive analysis, an Average model is also employed as a baseline for comparison. The performance of these models is assessed using several metrics, including Mean Average Error (MAE), Root Mean Squared Error (RMSE), and Mean Absolute Scaled Error (MASE). This comparative analysis aims to elucidate the relative strengths of each LSTM model in the realm of time series forecasting.

The findings suggest that the ConvLSTM architecture generally surpasses the other models across most evaluation metrics. Furthermore, this study concludes that LSTM-based models are adept at navigating the complexities inherent in time series data, identifying intricate patterns over extended durations. This capability is important for effective forecasting in various practical, real-world scenarios, reinforcing the utility of LSTM networks in advanced analytical applications in the retail sector.

Machine Learning Techniques for Egg Production Prediction

2024-12-10T13:23:39+00:00

Predicting egg production in poultry farming is a complex task due to the multitude of influencing factors such as temperature, nutrition, and environmental conditions. This study aims to evaluate the performance of various machine learning models in forecasting egg production using multivariate time series data. The dataset comprises records of the Hy-Line breed, divided into four batches, with attributes including age, maximum and minimum temperature, feed and water consumption, and daily production percentage. The study employs a sliding window technique to capture temporal patterns and evaluates models including Ridge Regression, Random Forest, XGBoost, and MLP. The models were trained on three batches and tested on the fourth, with performance measured using Mean Squared Error (MSE) and Mean Absolute Percentage Error (MAPE). The results indicate that Ridge Regression, with a window size of 7 days, provided the most accurate predictions, achieving an MSE of 19.74 and a MAPE of 3.81%. This study demonstrates the effectiveness of machine learning techniques and the sliding window approach in improving the accuracy of egg production forecasts, offering valuable insights for poultry farm management and optimization.

Moisture Detector in Concrete using Convolutional Neural Networks

2024-12-10T13:26:26+00:00

Concrete undergoes various indicators of the deterioration processes, such as pH changes, compressive strength reduction, and microbe growth, all associated with moisture. As a result, wet concrete can lose its adhesive properties and compressive strengths, leading to failure. To address this issue, this study presents a classifier that uses convolutional neural networks (CNNs) with a custom and low-complexity architecture to detect surficial signs of wet concrete visible to the human naked eye. The sample used in the study was built upon scraped data from the open database, as well as authorial photographs. The images of concrete surfaces were divided into two classes: with and without moisture. The results indicate that the classifier can effectively classify images with visible moisture that the human eye can detect, with good performance.

Social4Science: Mapping Trends and Patterns in Discussions of Scientific Publications on Social Media

2024-12-10T13:29:34+00:00

With the growing use of social media, it has become increasingly important to understand how scientific publications are disseminated and discussed on these online platforms. Analyzing this data on the interaction and circulation of scientific research has been investigated in altmetrics studies and can provide valuable information on how science is perceived and shared by the general public. This work aims to propose a platform for collecting and analyzing social data related to scientific publications, with a focus on the video-sharing platform YouTube. By collecting data from YouTube, the platform seeks to understand how scientific publications are disseminated and discussed on social media. In the solution developed, called Social4Science, it is possible to obtain social data from YouTube and correlate it with scientific data from publications. This approach makes it possible to identify trends and patterns in discussions about scientific publications on social media. The results obtained show that the proposed platform is very promising in providing a deeper understanding of the interaction between science and the public, and also opens up possibilities for future studies on this subject.

Socioeconomic Analysis of students who took the Enem between 2019 and 2022 using Machine Learning

2024-12-11T11:40:52+00:00

The National Secondary Education Examination (Enem) is the exam that allows students, through the results obtained, to enter higher education institutions. Socioeconomic analysis is the means that evaluates the economic relationship with a portion of society. Through this analysis, which is carried out through socioeconomic questionnaires carried out in Enem, it is possible to analyze the factors that impact student performance. In this context, the objective of this work is to carry out a socioeconomic analysis of Enem from 2019 to 2022, aiming to identify possible social inequalities and factors that may influence students' performance in Enem. With socioeconomic analysis, it is possible to define a target audience in which public measures are needed to avoid social inequalities, seeking to promote more opportunities and equal access to education and higher education. Due to the size of the Enem databases from 2019 to 2022, the Knowledge Discovery in Databases(KDD) steps were adopted to carry out the analyses, which consist of: selection, pre-processing, transformation, data mining and interpretation of data through discovered knowledge. Furthermore, in the development of the KDD stages, the programming language Python. As a result, between 2019 and 2022, two groups were divided for each year, a group of students with good performance and one of students who did not perform as expected. The group of students with good performance, the vast majority are from private schools, white color/race, with a computer at home, southeast and northeast region, monthly family income in class C where the minimum wage is 4 to 10, class D in that the minimum wage is 2 to 4, and class E of up to 2 minimum wages. Furthermore, of the students who did not perform as expected, the vast majority are from public schools, brown color/race, do not have a computer at home, are from the southeast and northeast regions, have a monthly family income of class E, which is up to 2 salaries minimums.

Study of the Temporal Propagation of Arboviruses in the Region of Recife-PE: Analysis of Climatic Influence using the SIR Model and Recurrent Neural Networks

2024-12-11T11:53:21+00:00

The occurrence of disease outbreaks, especially Dengue, Zika and Chikungunya, is on the increase throughout Brazil, and is currently a significant concern for the Recife-PE region due to the high temperatures. This directly affects public health and the population's quality of life, as well as the city's economy and education. To deal with this challenge, public policies are being implemented, such as awareness campaigns, inspections, and case reports. However, underreporting is a common problem due to the lack of demand for health services and difficulties in accessing medical care, which is reflected in official municipal data. In addition, there are gaps in the treatment of the specificity and cause of the problem and its mitigation. To overcome this inaccuracy, dynamic models such as the SIR model have been widely used in epidemiology. This model, which is based on differential equations, describes the temporal evolution of the susceptible, infected, and recovered classes. In Recife, the ambient temperature shows a strong positive correlation with the infection rates of cases of the diseases, which leads to the intensification of prevention campaigns during the summer. A study carried out in 2022 used data from the National Institute of Meteorology (INMET) to adjust a trigonometric function and analyse the seasonal influence of climate on infection rates, applying the SIR model. In addition, monthly iterations were carried out using the Runge Kutta numerical method in Simulink software. To improve the prediction and qualification of endemic disease cases, long-term memory modelling was used with a Recurrent Neural Network (RNN), validated based on available epidemiological data, obtaining an RMSE error metric of around 0.8 for the three diseases assessed.

Technical Decisions Influences on Dynamics and Results in Football: An Analytical Approach Based-On Graph Theory

2024-12-11T11:59:51+00:00

Soccer players are meticulously and continuously observed and evaluated during games based on their roles, positions, and characteristics. In a scenario of great tactical complexity, it becomes essential to identify variations in athletes' performance, a dynamic that directly impacts the quality of the team during each competition. In this context, relevant challenges emerge and require meticulous analysis of the teams and their behavior during the game. Among these challenges, evaluating the player's performance is an important aspect that is deeply influenced by the strategic approach adopted by the coach. In this paper, we explore the issue of individual player performance, given the different philosophies and strategies that coaches use during each match. In this context, we introduced an analysis approach based on graph theory, aiming to evaluate the relationships between players, the quality of assistance in the match, and the coaches' strategies to develop a model capable of identifying the different impacts of strategic composition in individual gameplay. The results show that training strategies adopted can considerably influence gameplay quality and, consequently, the player's performance during a match.

The Prediction of Bond Strength Between Thin Steel Bars and Concrete Using an Adaptative Neuro-Fuzzy Inference System

2024-12-11T12:11:29+00:00

In reinforced concrete, the solidary behaviour between steel and concrete means that tensile, compressive, bending, or torsional stresses are transferred from one material to another due to adhesion. Tests such as pull-out and beam tests, proposed by the EN:10080 standard, can be used to verify this behaviour; however, the difficulties inherent in destructive tests, as well as the non-linearity and number of variables involved in this issue, make it pertinent to use alternative methods. Using a database with experimental results from pull-out tests, the aim is to create an alternative technique to these tests. Hence, this work proposes the use of an Adaptive Neuro-Fuzzy Inference System (ANFIS) to predict the maximum adhesion load in pull-out tests. An ANFIS is a hybrid model made up of two techniques: Artificial Neural Networks (ANN) and Fuzzy Logic. The central idea in a Fuzzy Inference System is that the techniques work in parallel, with the neural network used to adjust fuzzy logic parameters. The combination of ANN and Fuzzy Logic is a useful approach to obtain the benefits of these systems in a single model, namely Neuro-Fuzzy. The Neuro-Fuzzy Inference System implemented in this work consists of four input variables: the surface of the bar, the diameter of the bar (ϕ), the compressive strength of the concrete (fc), and the length of the anchor (Ld). The output is the maximum adhesion force at the steel-concrete interface. The performance metrics obtained in this work will be evaluated against those obtained by other computational methods carried out earlier by our research group. The study indicates an alternative to the destructive tests that are widely carried out, overcoming their limitations considering the safety coefficients used in engineering.

The Relationship between Occupation, Sleep Disorders, and Health Impacts: an Analysis Based on Maximum Spanning Tree

2024-12-11T12:23:14+00:00

The health challenges of sleep quality disorders are notable, especially in certain occupational groups and their interactions with the professional job environment. The adversities in such a professional atmosphere can compromise the excellence of activities, the quality of life, and, consequently, physical and mental health. The present study proposes an analysis model to investigate the relationship between health and job occupation in developing sleep disorders. The objective is to identify the professional groups most susceptible to these problems, thus highlighting the predominant characteristics in the manifestation of such disorders. In this context, based on Kruskal's algorithm, we adopt the maximum spanning tree strategy to investigate the sleep quality datasets available on the Kaggle platform. The results show a broad relationship between hereditary conditions, such as high blood pressure, with the professional occupation and several sleep quality disorders, such as insomnia and apnea. With these results, we hope to amplify the discussions and evidence that certain occupational groups, due to high levels of occupational stress, tend to suffer considerable influence on indicators such as increased blood pressure and sleep quality disorders, having relevant impacts on the lives of these individuals.

Aerodynamic and structural optimization of wind turbine blade considering natural of frequencies of vibration

2024-12-11T13:46:50+00:00

In recent years, wind energy has garnered significant global attention due to its immense energy and environmental potential, leading to a substantial increase in both capacity and size of wind turbines, evolving from a nominal power of 75kW to 7.5MW and a rotor diameter of 17m to over 125m. However, this scaling-up has introduced new challenges related to instability caused by the aeroelastic effect, which stems from the interplay between wind loads and the structural deformation of wind turbine blades. Consequently, an effective model necessitates well-defined aerodynamic and structural components. Yet, the complex geometric shapes of turbines demand extensive computational resources for analysis, particularly given their composite materials and intricate configurations.
Various research institutions, including NREL, DTU, and ECN, have developed aeroelastic tools for wind turbine studies, integrating structural and aerodynamic modules. The prevalent approach employs the BEMT (Blade Element Moment Theory) model for aerodynamic simulation and FEM models for structural dynamic analysis. The BEMT model partitions the blade into elements to evaluate aerodynamic loads based on local characteristics. This amalgamation offers an efficient solution for predicting element performance parameters. Additionally, the BEM model provides a computationally economical alternative to more intricate models, making it a cost-effective choice for wind turbine analysis and a cheaper tool compared to robust methods, like CFD.
This work proposes an aerodynamic optimization method constrained by the structural model, focusing on the natural vibration frequencies of wind turbine blades. The methodology comprises three phases: defining the aerodynamic model using the CCBlade code in Julia Language, implementing the structural analysis method via FEM for rotating Timoshenko beams in MATLAB, and integrating the aerodynamic and structural models on a multi-objective optimization platform. Evolutionary algorithms were employed to enhance wind turbine energetic efficiency and avoid structural instabilities within this study. By leveraging advancements in modeling and optimization techniques, the aim is to contribute to the development of more efficient and reliable wind turbines, further promoting the transition to clean and sustainable energy sources.

Analysis of optimization algorithm models for the design of prestressed steel beams

2024-12-11T16:21:20+00:00

Prestressing in steel beams offers significant benefits in terms of structural efficiency and material savings. The aim of this study is to present a comparative analysis of the design results of prestressed steel beams obtained through three optimization algorithms: Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and its variant, including a craziness operator for performance enhancement (CRPSO). These algorithms were used to minimize CO2 emissions and cost in the structural design process, while adhering to the constraints imposed by ABNT NBR 8800:2008. The implementation was carried out using MATLAB (2016). The validation of the methodology was conducted using examples from the literature, comparing the CO2 emissions and cost values obtained from experimental work and those derived from GA, PSO, and CRPSO. The results indicate that, although the Genetic Algorithm is widely used in optimization, more optimized results are achieved using PSO. Furthermore, the improvement obtained by CRPSO showed no significant deviation from those obtained by PSO, nor did it affect the convergence speeds of the results. It was also observed that all three implemented models yielded more optimized values of emissions and costs compared to those reported in the literature.

Backcalculation of asphalt pavement materials moduli considering absolute and relative errors

2024-12-11T16:26:48+00:00

Backcalculation is a procedure used to estimate the material properties of pavement layers from the results of non-destructive tests, such as the Falling Weight Deflectometer (FWD). This procedure is important to assess the quality of a pavement structure during its construction and/or to monitor its condition during its lifespan. The Finite Element Method (FEM) can be used to evaluate the pavement deflections, provided that the loading, geometry, and material properties of each pavement layer are known. Thus, assuming a linear elastic behavior and known Poissons ratios and layer thicknesses, the backcalculation procedure consists of the determination of the set of elastic moduli that minimize the differences between the simulated (FEM) and measured (FWD) deflections. Different error measures can be adopted to assess the quality of the model fitting. The resulting Nonlinear Least Squares (NLS) problem can be solved using classical algorithms, such as Gauss-Newton and LevenbergMarquardt methods. However, these algorithms present convergence problems for NLS with large errors. In this case, it can be necessary to use of hybrid algorithms based on a combination of Gauss-Newton and BFGS methods. The robustness, accuracy, and computational efficiency of classical and hybrid algorithms are compared in the backcalculation of asphalt pavements.

Comparative Analysis of Evolutionary Methods in Topological Optimization of Truss Structures: Progressive Directional Selection versus Evolutionary Structural Optimization

2024-12-11T16:33:58+00:00

The main difference between evolutionary methods and traditional structural topological optimization methods is that the former may not always converge to an optimized solution and can be challenging to implement. This work presents two heuristic and evolutionary methods, which aim to analyze truss structures obtained by the topological optimization process using the PDS and ESO methods, employing a ground structure type structure as the initial design domain. The Progressive Directional Selection (PDS) method is based on selecting a certain number of elements, established by the user, that most contribute to supporting the loads applied in an initial design domain. The selection stages involve a progressive number of selection steps, each eliminating a certain number of less efficient elements. Convergence occurs when the selected elements are the same in a certain number of consecutive selection stages, also pre-established by the user. The Evolutionary Structural Optimization (ESO) method is a technique where elements that contribute less to supporting loads in an initial domain are removed through a rejection rate. If removing elements with the same rejection rate value is no longer possible, an evolution rate value can be added to remove more inefficient elements. ESO convergence is achieved when the rejection rate evolves to a user-established value. The optimized structures obtained by both methods efficiently support the applied loads. The PDS method stands out for reaching optimized truss structures with a specific number of elements that ESO cannot obtain, but the former stands out for its shorter processing time.

Comparative Analysis of Solutions in the Optimal Design of Composite Flooring Systems for Different Beam Topologies

2024-12-11T16:38:01+00:00

With the advancement of civil construction, there has been an increase in the utilization of composite steel and concrete systems, often employing full-web profiles for the beams. However, other solutions such as cellular beams and truss beams remain relatively unexplored. The objective of this study is to conduct a comparative analysis of the optimal design of composite floors using different beam topologies, namely: full-core beams, cellular beams, and beams composed of tubular trusses. The objective function will be to minimize CO2 emissions resulting from the materials used in the floors. To solve this optimization problem, the Ant Colony Algorithm (ACO) will be employed. A comparative analysis will be conducted between the solutions proposed in the literature for floors utilizing full-core beams and those obtained with cellular beams and beams composed of tubular trusses, to determine the most environmentally efficient solution.

Cost and CO2 emission optimization of steel-concrete composite floor systems with composite tubular trusses

2024-12-11T16:43:07+00:00

The objective of this study is to propose a formulation for the topological and dimensional optimization of composite floor systems, which comprise composite trusses, while considering both the costs and environmental impacts generated due to the consumption of materials from this structural system. To address this optimization problem, the Bonobo algorithm (BO) will be employed. For the structural analysis, the bar element was implemented with 2 nodes and 3 degrees of freedom per node to obtain displacements and efforts arising from the application of the vertical actions considered (dead and live load). Structural verification will adhere to the guidelines outlined in Brazilian standards for tubular structures, steel structures and composite steel and concrete structures. The models studied address examples from the literature in order to verify and compare solutions from an economic and environmental perspectives, identifying which factors impact the final solutions found.

Cost Optimization of RC Beams Considering Steel Rebar Losses

2024-12-11T16:47:12+00:00

Optimization techniques are an efficient tool for developing structural projects. By seeking the rational use of available resources, they can not only reduce costs but also the impact on the environment. In this sense, it is interesting that these techniques are effectively incorporated throughout the process, including at the construction stage. For example, in the design of reinforced concrete structures, an additional 10 percent of steel consumption is usually foreseen due to losses from cutting rebar, which is supplied in standard lengths on the market. These losses can be significantly reduced if the bars are cut according to an optimized plan. This study aims to combine the optimization of the cost of reinforced concrete beams with the minimization of losses due to the cutting of steel bars. Initially, the two optimization problems were implemented separately and used sequentially, using the Harmony Search Optimization Method. Several simulations were then carried out to assess the influence of factors such as the number of beams and the number of gauges on losses and final costs. In a second stage, the aim is to integrate the two problems so that the reduction of losses can be optimized even during the design and detailing phase of the structure.

Design optimization via genetic algorithms of acessible Ferris Wheels

2024-12-11T16:50:43+00:00

In Brazil, systematic studies related to the design of amusement park equipment are still incipient. Essential normative references for these projects, such as NBR 15926-2 and ISO 17842-1 which deals with design and installation safety requirements, are often not effectively applied, increasing the risk of structural failures and neglecting stability and operational safety evaluation. Consequently, most of these equipment are imported, lacking national designs. The aim of this paper is to perform a preliminary analysis of the structural design of an accessible flexible Ferris wheel, evaluating safety coefficients through a parametric study of its geometry, including actions related to its operation, loading, and wind action. The structure modeling is conducted via Finite Element Method (FEM) using Ansys Mechanical APDL software using beam and mass elements. A routine implemented through MATLAB software communicates the input parameters and the modeled structure via FEM, allowing an easy alteration of the geometric variables, as well as the rectangular or square steel tube sections standardized by NBR-6591. Finally, a multi-objective optimization is implemented via Genetic Algorithms (GAs) with a fitness function aiming to maximize the safety coefficient and minimizing the mass. Optimal combinations are investigated and compared, proving the efficiency of this design methodology.

Dynamic model adjustment of a honeycomb sandwich panel using response surface methods and parametric optimization algorithms

2024-12-11T16:54:26+00:00

The aeronautical and aerospace industries have been evolving in technologies that improve the efficiency of their structures, where, in this context, sandwich panels with honeycomb cores are one of the frequently employed technologies in aircraft and nano satellites. This type of structure presents superior mechanical properties compared to traditional panels, as well as a low structural weight due to its porous core. However, they exhibit complex characteristics both geometrically and behaviorally, requiring the use of more sophisticated computational tools such as finite element analysis packages. Precise numerical models are required to allow for reliable analysis during the design process of aerospace structures. The most commonly employed approach is to create a numerical model and refine it through adjustments using experimental data. This study presents the modal numerical analysis of a sandwich panel with a honeycomb core using finite elements and proposes an adjustment of the obtained numerical model. The panel is composed of Aluminum 2024 skins and an Aluminum 5056 honeycomb core. This panel had its vibration modes and frequencies previously identified through experimental tests. Once the numerical and experimental values are compared, a numerical-experimental adjustment is proposed using the optimization algorithms NLPQL, MISQP, and Genetic, which are applied through two methodologies, with and without the use of a metamodel, where the metamodel is constructed using the kriging algorithm. The optimization problem was formulated considering the minimization of a function defined as the sum of squared differences between experimental and numerical frequencies. The ANSYS Workbench software package was utilized for the numerical modeling, which also provided the necessary optimization algorithms. The results demonstrate good agreement with the experimental data, and the numerical adjustments made using the optimization algorithms proved to be effective.

Evaluation of Optimization Algorithms for Calibration of Numerical Models of Engineering Structures

2024-12-11T16:58:02+00:00

In civil engineering, the finite element method (FEM) is used to simulate the behavior of buildings, bridges, and other structures. However, there are several uncertainties that make it difficult to obtain a representative computational model suitable for evaluation and monitoring of existing structures. To overcome this, the calibration of the numerical model based on experimentally obtained modal data is employed. This step allows for the updating of parameters that are difficult to obtain directly, in order to approximate the dynamic response of the computational model to that of the real structure. For this purpose, various algorithms can be employed, presenting differences in approach, effectiveness, and computational cost. This study aims to compare the performance of different optimization algorithms applied in the calibration of numerical models. To achieve this, the model of a structure will be established beforehand, with initial uncertainties represented by masked parameters; a set of modal parameters will be extracted, and then a new calibrated model will be developed through distinct optimization processes. The calibrated models will be compared with the initial model to evaluate their performance in predicting structural behavior, considering aspects such as accuracy in reproducing initially unknown parameters and the computational cost of each solution. Thus, it will be possible to enhance the calibration process by identifying the most appropriate algorithm.

Integrating metaheuristic and machine learning for optimization of a full-scale transmission line tower

2024-12-11T17:02:18+00:00

In long transmission lines (TLs), the design of a transmission line tower (TLT) can be replicated multiple times, a contrast to most structures that feature a unique design. Various optimization methods have been developed to reduce the overall mass of these structures. Historically, most research has relied on metaheuristic algorithms to identify optimal solutions. More recently, machine learning (ML) techniques have begun to be integrated with metaheuristics to speed up the optimization process, although ML has primarily been applied to smaller TLTs, in academic settings, or to simplify structural analysis, potentially compromising accuracy. This paper introduces a new approach that combines the Backtracking Search Algorithm (BSA), known for its efficacy in similar real-world TLT optimization challenges, with Kriging-based Efficient Global Optimization (EGO). This methodology starts by optimizing the size using BSA and subsequently employs EGO to refine the shape. This dual-step optimization effectively significantly reduces the mass of the TLT with only a few hundred additional objective function evaluations (OFEs). In comparison, simultaneous size and shape optimization using BSA alone requires over one hundred thousand additional OFEs to achieve comparable results, showing the potential of the proposed approach in dealing with expensive engineering design optimization problems.

Many-objective design of tall buildings considering second order effects

2024-12-11T17:05:43+00:00

This research investigates the application of multi-objective optimization methodologies in the development of economically viable and structurally efficient spatial steel constructions. It emphasizes the significance of optimizing performance alongside cost reduction in practical engineering scenarios. The investigation encompasses the minimization of maximum horizontal displacement, the maximization of the first natural frequency of vibration, the maximization of the critical load factor pertaining to the initial global buckling mode of the structure, and weight minimization as primary objectives. Furthermore, the analysis integrates considerations for both local and global second-order effects. Moreover, it delineates a systematic framework for the selection of optimal designs, employing three distinct evolutionary algorithms grounded in differential evolution, coupled with a multi-criteria decision-making approach.

Modified genetic algorithm for efficient optimization: application to prestressed concrete structural elements

2024-12-11T17:08:52+00:00

Prestressing, whether bonded or non-bonded, has become increasingly attractive as it allows for larger spans, greater architectural flexibility, greater agility in execution and greater durability. All of these advantages are capable of making prestressed concrete structures more economical solutions when associated with an efficient scaffolding system and formwork. The use of prestressed beams combined with ribbed slabs allows the slabs and beams to have the same height, thus favoring the architecture, in addition to facilitating the assembly of formwork and concreting. The designer can appropriately define the dimensions of the beams and slabs, as well as parameters such as the quantity and layout of cables by trial based on experience. However, the use of numerical optimization techniques are tools recognized as appropriate for the search for a structural solution, where design parameters, whether at the level of design (topology), intermediate (shape) or detail (dimension), can be determined such that the solution minimizes a performance measure, for example, cost, which takes into account the cost of materials, the volume of concrete, the weight of passive and active reinforcement, and labor productivity. Given the discrete nature of some variables, genetic algorithms (GA) have been widely used. GAs have control parameters and operators that are, in general, dependent on the problem, requiring calibrations in each case. The objective of this work is to review some optimization models and improve the GA of the BIOS program - developed at the (Computational Mechanics and Visualization Laboratory) LMCV of the Federal University of Ceará (UFC) - investigating new operators, thus aiming at the efficiency of the algorithm for prestressed elements, using a prestressed band beam as a case study. Genetic operators, in particular crossover, will be targets of the study.

Multi-objective structural optimization of a space truss considering geometric nonlinearity and global stability aspects

2024-12-11T17:11:55+00:00

The literature has broadly discussed developing and solving multi-objective structural optimization problems (MOSOPs) with two objectives. The conflicting objective functions commonly addressed are minimizing the structure's weight and maximum displacements. In this paper, the two objective functions considered are minimizing the weight and maximizing the first critical load factor related to the structure's global stability. The constraints are related to the maximum stresses in the bars, the maximum allowed nodal displacements, and the minimum value determined for the first natural frequency of vibration. The analyzed structure is a 25-bar truss. When defining the displacements and deformed configurations of the structure, a geometrically nonlinear analysis is applied using the arc-length method. This analysis allows the decision-maker to obtain more realistic and accurate values regarding the objective functions and constraints. The evolutionary algorithm used is the multi-objective meta-heuristic with iterative parameter distribution estimation (MM-IPDE). The Pareto fronts obtained in the proposed problems are presented, as it is possible to observe, for example, how the growth of the truss' weight causes increases in the first critical load factor. Finally, optimized solutions are extracted from the Pareto fronts.

Multi-objective structural optimization of ground stuctures considering dynamic and stability behaviors and automatic member grouping

2024-12-11T17:17:14+00:00

This paper aims to formulate the many-objective structural optimization problem to find the optimal design of ground-structure systems. The objective functions are the weight of the topologically optimized ground structure (to be minimized), the compliance (to be minimized), the different number of discrete cross-sectional areas (to be minimized), the first natural frequency of vibration (to be maximized), and the first load factor concerning the global stability of the structure (to be maximized).
It is worthwhile to emphasize that minimizing the number of distinct cross-sectional areas of the optimized ground structure makes finding the best member grouping possible. As a result, the smaller the number of different groups, the greater the weight of the structure, and the greater the number of groups, the smaller the structures weight. Also, minimizing compliance, maximizing the first natural frequency of vibration, and maximizing the critical load factor directly impact the structures mass. The constraints are defined as the maximum allowable stress in the bars, and when the natural frequency of vibration or the critical load factor is not set as one of the objectives, they become part of the set of constraints. DE-based multi-objective algorithms are adopted to solve the proposed optimization problem. Benchmark problems are analyzed, and Pareto fronts are obtained, showing the non-dominated solutions. Multi-criteria decision-making (MCDM) is adopted to extract solutions from the Pareto front according to the preferences of the decision-maker (DM) used in the ground-structure system. The complete data for each extracted non-dominated solution, including its optimized topology, is provided.

Multi-objective truss structural optimization considering dynamic and stability behaviors and automatic member grouping

2024-12-11T17:20:40+00:00

This paper aims to address the challenge of multi-objective structural optimization in the search for the most efficient configuration of members in truss structures. Conflicting objectives, such as the structure's weight, the number of discrete cross-sectional areas, the first natural vibration frequency, and the first load factor relative to overall structural stability, must be optimized simultaneously, resulting in a Pareto Front (PF) that provides non-dominated solutions. NSGA-III is the multi-objective evolutionary algorithm adopted to solve the proposed optimization problems. Non-dominated solutions are extracted from the FP using multi-criteria decision-making (MCDM). New competitive configurations of structural members can be discovered, offering attractive alternatives to decision-makers in manufacturing, cutting, transportation, checking, and welding.

Multiobjective Optimization of prestressed composite steel and concrete beam via non-dominated sorting genetic algorithm (NSGA)

2024-12-11T17:24:00+00:00

The use of prestressing in steel beams and composite steel and concrete beams is still underexplored in the design of structures with large spans due to the lack of specific normative codes for this type of structural element. Studies involving optimization techniques for these types of structures are scarce in the literature, thus opening up a vast field of research to be explored. This study aims to propose the formulation of a multi-objective optimization problem for composite steel and concrete beams with external prestressing. The final cost of the beams, CO2 emissions from the materials used in their fabrication, and the maximization of the payload that the beam can support are considered minimization objectives. Constraints include the requirements for composite steel and concrete elements from NBR 8800:2008 and the prestressing provisions from NBR 6118:2021. The non-dominated sorting genetic algorithm (NSGA) from the Matlab package will be used to solve the optimization problem. Examples demonstrating the solution's effectiveness will be compared with examples from the literature, and Pareto frontiers will be evaluated to verify the best solutions for the proposed problems.

Optimal Design of Composite Floor Systems composed of Cellular Beams via Ant Colony Algorithm

2024-12-11T17:27:02+00:00

The use of composite floor systems has been increasing in recent years, primarily with full-web beams, while other beam topologies, such as cellular beams, remain underutilized. The objective of this study is to propose a formulation for the optimal design of composite floor systems composed of cellular beams. The objective function will analyze the costs and final CO2 emissions of the floor. Technical prescriptions proposed in the literature will serve as constraints, as Brazilian standards lack clear guidelines for the design of cellular beams. To solve the optimization problem, the Ant Colony Algorithm (ACO) will be employed. A comparative analysis with solutions proposed in the literature for floors with solid beams will be conducted to assess the efficiency of the proposed solution for composite floors with cellular beams.

Optimal Design of Pile Caps considering Soil Structures Iteration

2024-12-11T17:31:41+00:00

This study presents a formulation for the optimum design of pile caps considering the soil structure interaction. To solve the optimization problem, the Bonobo algorithm is used. This algorithm was developed based on the social behavior of bonobos and is implemented for the design of the pile caps and the piles. The objective function considers the CO2 emissions and the pile cap final costs related to the materials used for its execution. The Brazilian standard impositions, and the criteria for determining the optimal dimensions of piles are the considered problem constraints. Comparative analyses are developed between the optimal solution against the proposed by structural design offices, and results proposed in the literature.

Optimal Design of Prestressed Steel and Concrete Composite Beams

2024-12-11T17:35:07+00:00

The application of prestressing techniques is typically associated with concrete structures and has been relatively underexplored in the context of concrete-steel composite beams. The objective of this study is to propose a formulation for the optimal design of prestressed steel and concrete composite beams. The objective function will analyze the costs and final CO2 emissions of the beam. As constraints, the guidelines outlined in NBR 8800:2008 for steel structures and NBR 6118:2021 for prestressing in concrete structures will be adhered to. To solve the optimization problem, the Ant Colony Algorithm (ACO) will be employed. Additionally, a parametric analysis will be conducted and compared with examples proposed in the literature, aiming to identify the key factors that impact the final solution.

Optimal design of structures using metaheuristics and metamodeling

2024-12-11T17:38:54+00:00

Computation-intensive structural design optimization problems are common in engineering. The computation burden is often caused by expensive simulation models and becomes a problem in practice. To address such a challenge, metamodeling techniques are often chosen to improve the optimization efficiency. Metamodels, or surrogate models, are very popular methods and are considered a valuable tool to support a wide scope of activities in modern engineering design. The paper discusses strategies to obtain suitable metamodels to assess their quality concerning prediction, considering machine learning techniques used in the literature. A multi-objective structural optimization problem is used to illustrate the applicability of the approach, considering as objective functions the structures weight, and critical load factor concerning the structures global stability. The numerical results demonstrate the efficiency and computational advantages of the proposed methodology.

Optimization of materially nonlinear trusses subjected to dynamic loads

2024-12-11T17:43:59+00:00

The structural optimization of trusses has been extensively studied over the past few decades. However, investigations incorporating material nonlinearity are still relatively scarce. The objective of this study is to propose a formulation for optimizing spatial truss structures, considering the material nonlinearity of the structure under dynamic loading. To address this problem, the Particle Swarm Algorithm (PSO) integrated into the Ansys program will be utilized for nonlinear dynamic structural analysis. To validate the optimization approach, a problem from the literature, considering material nonlinearity, will be analyzed. Additionally, will be compared the results obtained from the structural optimization considering and neglecting the material nonlinearity. This comparison aims to assess the real impact of material nonlinearity on optimization results.

Strategies in Decision Making in a Multiobjective Context: Integration of DOE, NBI, and CFD in the Optimization of a Centrifugal Fan

2024-12-11T17:47:04+00:00

Multiobjective optimization problems present significant challenges when attempting to balance conflicting variables simultaneously; furthermore, the creation of an adequate dataset can be a complex task. To address these challenges, an integrated approach is adopted, combining Design of Experiments (DOE) and Normal Boundary Intersection (NBI).
DOE is employed to plan experiments in a balanced and economical manner, allowing for valuable information to be obtained with fewer resources. Subsequently, NBI is used to optimize multiple objectives simultaneously, creating an equispaced Pareto surface that defines an efficient boundary.
To handle uncertainty in parameter estimates and analyze variable clustering, a confidence ellipse is constructed. This ellipse provides a visual representation of the uncertainty associated with estimates and assists in identifying patterns in the data.
Once the efficient boundary with numerous results is obtained, the challenge arises of choosing the best solution among those available. For this purpose, Mahalanobis Distance (MD) is utilized, which are weighted Euclidean distances, taking into account the covariance of variables. This technique aids the decision-maker in selecting the most suitable solution.
To demonstrate the effectiveness of integrating these techniques, a problem involving Computational Fluid Dynamics (CFD) is explored, encompassing an industrial centrifugal fan. In this scenario, conflicting variables include mass flow rate at the outlet and required torque, with four control variables: number of blades, blade inlet angle, blade outlet angle, and blade length.
After identifying the best possible fan based on the smallest MD, the product is computationally replicated under optimal conditions, and the result is verified.
This integrated approach combines techniques from DOE, CFD, and NBI that address all stages, from dataset creation to optimization and confirmation of results obtained, offering a comprehensive methodology for solving complex engineering problems.

Topological optimization with support structure filter for additive manufacturing

2024-12-11T17:51:28+00:00

Topological optimization proves to be an important tool for analysis and design of projects, seeking the best structural performance within criteria such as stiffness, strength, economy, and stability. However, manufacturing optimized structures by traditional methods is not always feasible, due to the complex and unconventional configuration of the geometry. Additive Manufacturing (AM) emerges as a solution, allowing the production of objects layer by layer, without the need for molds. However, angles greater than 45° formed in the geometry may require support material to avoid failures and deformations during printing, increasing material costs and manufacturing time. This study combines topological optimization with AMfilter, a support structure filter for AM developed by Langelaar (2016). Using the open-source MATLAB® code of 88 lines developed by Andreassen et al. (2010), in which AMfilter is integrated during the numerical analysis of the topological optimization problem. The objective is to evaluate the effectiveness of topological optimization with the implementation of AMfilter, through simulations of printing the optimized models, highlighting the potential cost reduction benefits. The results demonstrate a decrease in the use of supports, and in some cases, their complete elimination, making this methodology efficient in the cases examined in this study.

2D nonlinear Acoustic Wave equation in heterogeneous fluid

2024-12-13T12:40:40+00:00

In this work, the non-linear equation of Acoustic Wave propagation in a heterogeneous fluid (CHACALTANA et al., 2015; PERES et. al., 2023) is solved in two dimensions by Finite Element Method (FEM). The Weighted Residual Method (Petrov-Galerkin) and linear and parabolic approximation basis functions are used to minimize the residue in each element. Ricker-type pressure source (CHACALTANA et al., 2015; PICOLLI et al., 2020) and the sinusoidal type are used to generate the P-wave. Reflective Neumann (natural) and non-reflective ABC (Absorbing Boundary Condition) boundary conditions based on the non-reflective boundaries of Reynolds (1978) were implemented. The numerical code is written in Fortran 95 language and the Octave graphical interface is used to analyze the results. The GMSH mesher (v. 4.8.4) is used to represent the continuous domain by a set of discrete points that group together form a non-uniform mesh of triangular elements. Numerical tests on square and circular geometries are performed to verify the implementations of the Neumann and ABC boundary conditions. Finally, a good agreement is found between the results of numerical simulations when compared with existing results in the literature.

Effects of modal coupling on the nonlinear dynamics of hyperelastic circular cylindrical shells

2024-12-13T12:50:19+00:00

The nonlinear dynamics of a simply supported circular cylindrical shell is analyzed using an analytical model that considers both physical and geometric nonlinearities. The material that composes the shell is assumed as homogeneous, isotropic, hyperelastic and incompressible, being described by the Mooney-Rivlin hyperelastic constitutive law. The geometric nonlinearity is introduced into the analytical model by applying the Sanders-Koiters nonlinear shell theory. The Rayleigh-Ritz method and Hamilton's principle are employed to obtain the nonlinear equilibrium equations. For that, the energy density function is expanded in Taylor series up to the fourth order and the transversal displacement field is described in Fourier series that considers both asymmetric and axisymmetric modes. This works focusses on evaluating the influence of the asymmetric and axisymmetric modes, selected in the modal solution of the transversal displacement field, on the frequency-amplitude relationships of the shell and resonance curves. It can be observed that the asymmetric modes provoke nonlinear hardening behavior of the hyperelastic shell. On the other hand, when the axisymmetric modes are added, there is a significant change in the nonlinear behavior of the hyperelastic shell - which indicates the importance of this modal coupling in the nonlinear dynamic analysis.

Evaluation of Integration Methods for Time-Domain Response Analysis of Vibrations in a Full-Car Model

2024-12-13T12:59:05+00:00

Vibrations generated by road surface irregularities are intrinsically linked to the comfort level experienced by drivers and passengers in several means of transport. Consequently, the effects can range from mild discomfort to permanent trauma, depending on the vibration amplitude and exposure time. This effect is further exacerbated when traversing off-road terrain. Therefore, this study aims to determine the time-domain system responses and investigate system transmissibility in an 8-degree-of-freedom full-car vehicle model of a vehicle used in rural areas. To achieve this, a class E road surface according to ISO 8608 was generated for all four wheels using power spectral density and transformed into its corresponding time-domain representation. The system's natural frequencies and vibration modes were calculated using the vehicle's input data. Three integration methods (Newmark, Central Finite Differences, and State Space) were used to obtain the displacements and accelerations of both the vehicle body and the driver's seat, demonstrating the equivalence of the methods.

Experimental and numerical modal analysis of the steel frame

2024-12-13T13:05:17+00:00

In engineering, it is extremely important to direct research towards the identification and understanding of dynamic behavior in structures, as dynamic loads are present in all types of structures, including civil construction. Dynamic loads can range from the interaction of the wind with the structure to people's footsteps and car movements, and cause vibrations. These vibrations can cause damage to the structure and users, depending on their intensity and duration. For this, the structures are dimensioned and designed to support all the efforts required, this includes vibrations and other dynamic actions. Thus, the present work aims to determine the dynamic properties of a steell frame through a numerical and experimental modal analysis.
The steel frame is made of cold-rolled A36 steel. The profiles of the columns and beams are formed by cold rolled profiles forming sections of the type closed stiffened double u-profile and hat profile, respectively. The beams are joined to the columns by rigid connections. The dimension of the steell frame is 2m in height by 1m in width and length, approximately. Numerical analysis was performed by the Finite Element Method using shell elements. In the experimental analysis, the structure was excited by an impact hammer and the vibration response was measured by piezoelectrics accelerometers. The frequency domain method Rational Fractional Polynomial (RFP) was used to estimate the natural frequencies, mode shapes and damping factor. There was a good agreement between the experimental results and the numerical values obtained by the proposed procedure.

Finite prism approach for stability analysis of laminated glass fins

2024-12-13T13:12:41+00:00

The use of laminated glass (LG) as a structural material for load-bearing components within buildings has been growing over the last decades. LG can be obtained by bonding two or more pieces of glass by means of polymeric interlayers (e.g., poly vinyl butyral PVB). This building process gives LG elements a huge advantage over the same ones made of fully monolithic glass with respect to safety, since after breakage the fragments usually remain attached to the interlayer, reducing the risk of injuries. As LG members usually present a high slenderness, they are susceptible to flexural buckling under compression, requiring specific calculation methods and verification procedures in order to guarantee appropriate and safe structural performance. Compared to literature, this work presents a novel approach that is focused on the prediction of the elastic critical buckling load of LG columns without any lateral restraints at the tensioned edges. The buckling loads of LG columns have been determined using Finite Element Method, generally using shell elements, or analytical models. Usually, such approaches make use of the concept of effective thickness, in which the thickness of a monolithic element with equivalent bending properties in terms of stress and deflection is employed. However, the effective thickness approach is either difficult to apply or inaccurate. Therefore, this work presents an efficient and accurate approach to evaluate elastic critical buckling loads of LG columns applying Finite Prism Method (FPM). The accuracy of the proposed approach is assessed comparing the results obtained using solid finite element and analytical models for fully monolithic glass columns, as well as LG columns composed by multiple glass layers.

Geometric nonlinear analysis of soil-structure interaction with trusses using positional formulation

2024-12-13T13:19:19+00:00

Although in many situations it is possible to consider civil structures as supported on immovable foundations, in situations of moderate settlement it is necessary to consider the interaction between the soil and the structure, considering both flexible. Soil deformability can cause considerable changes in support reactions and stresses, which are fundamental for structural design. In turn, this change in the loads transmitted to the soil causes the deformations presented by the soil to change. Thus, this work deals with coupling a formulation for nonlinear analysis of spatial trusses with a solution to the problem of settlements in stratified soils. The truss analysis follows the positional formulation of the finite element method (FEM), as presented in Coda (2018), while the soil domain analysis is based on fundamental cases of elasticity theory, as presented in Pinto (2006), Mundim, Cruvinel and Cavalcanti (2014), and in Poulos and Davis (1980), considering the characteristics of the soil based on geotechnical field tests. The calculation of soil deformation considers both the influence of direct loads on the support considered and the indirect effects of tensions due to adjacent supports, considering the variation in tension spatially, that is, along the depth of the soil below the foundation and of the adjacent region. The computational code for dynamic analysis of three-dimensional trusses is verified using analytical and numerical examples from the literature, showing compatible results. In the context of soil mechanics, the code is also verified through examples, considering homogeneous, stratified soils with three-dimensional stress propagation. Finally, examples are studied considering the soil-structure interaction, where the degree of influence of the soil-structure interaction on the results of the requesting efforts is evaluated.

Geometrically nonlinear analysis of planar frame structures with positional finite element method

2024-12-13T13:25:02+00:00

Problems in structural engineering involving geometric nonlinearity are widely studied from numerical and experimental perspectives. From the numerical modeling point of view, to investigate the resistance mechanisms that develop in structures when subjected to large displacements, a mathematical formulation capable of numerically representing the phenomena that occur during the nonlinear behavior is necessary. This work addresses problems of planar frame structures involving geometric nonlinearity with a formulation available in the literature of the Finite Element Method (FEM) based on positions and generalized vectors as degrees of freedom. In this formulation, nodal positions are used as degrees of freedom of the problem, and the Saint-Venant-Kirchhoff constitutive law for plane stress state is adopted. Unlike the FEM formulation for displacements, the positional formulation adopted requires strategies for connecting non-collinear finite elements, involving penalization techniques to satisfy boundary conditions. As detailed in the literature the connections between non-collinear elements are performed with uniaxial and flexural springs. The strain energies of the springs are calculated based on the nodal positions of the structure, and their contributions to the Hessian matrix and internal force vector of the structure are performed with a penalization technique. To validate the implementation developed the solutions of the positional FEM are compared to analytical and numerical solutions obtained by the finite element software DIANA FEA. In addition, parametric analyses varying the connections stiffness values are carried out to determine minimum stiffness values for the connection springs to allow the representation of the nonlinear equilibrium trajectory of planar frame structures.

Influence of neighborhood on the longitudinal response of a building under wind action

2024-12-13T13:29:11+00:00

As structures grow in height, the complexity of their design and structural analysis also increases. Specifically, the impact of wind becomes a crucial consideration in construction. This study aimed to examine how distances between adjacent buildings affect the longitudinal response of a standardized tall building, known as CAARC, under the influence of wind. Wind effect analysis was conducted in two main directions, with wind acting at 0º and 90º, considering three different neighborhood scenarios. Utilizing the force data obtained in a wind tunnel by Vieira (2016), computational analyses were performed using MATLAB software, combined with the High-Frequency Pressure Integration (HFPI) method. The results revealed that greater distances between neighboring buildings result in less impact on the analyzed building.

Influence of the unilateral elastic base on the backbone curves of an imperfect cylindrical panel

2024-12-13T13:32:12+00:00

This work evaluates the influence of a discontinuous unilateral elastic base and an initial geometrical imperfection on the nonlinear free vibration of cylindrical panels. The Donnells nonlinear shallow shell theory is considered to describe the cylindrical panel, then the equations are discretized by the Galerkin method. The unilateral elastic base is represented by the Signum function, and the Heaviside function describes the discontinuity of the elastic base. The results show the analysis of the nonlinear free vibrations of the cylindrical panel through the backbone curves, investigating the influence of the hypothesis of contact of the unilateral elastic base and the initial geometrical imperfection of the cylindrical panel. The modal solution employed has with five degree-of-freedom, being sufficient to describe the nonlinear softening behavior of the imperfection cylindrical panel in contact with the discontinuous unilateral elastic base. The numerical results reveal that the imperfect cylindrical panel in contact with unilateral elastic base presents less structural stiffness than in contact with bilateral elastic base, with decreasing the natural frequencies. In conclusion, the backbone curves are strongly influenced by discontinuous unilateral elastic base and the imperfections of the cylindrical panel.

Local and distortional buckling of thin-walled laminated lipped channel columns

2024-12-13T13:40:19+00:00

The great versatility in manufacturing and handling, as well as the mechanical capacity in structural applications, lead to the increase in the application of composites in various engineering applications, including aerospace industry, automotive industry, renewable energy, and civil construction. Due to the high strength and stiffness of fiber reinforced composites, they are mostly used to manufacture thin-walled structural components. It is already known that buckling plays a significant role in the design of thin-walled structures subjected to compressive loads, such that failure can occur with stresses much lower than the material mechanical strength. Thus, the design of many structural components is carried out considering constraints related to stability along with traditional criteria of strength and stiffness. This work focus on the stability analysis of laminated lipped channel columns. These columns present three main buckling modes: local, distortional, and global. It is important to note that the buckling loads of laminated open-section columns with arbitrary layup can be accurately computed using the Finite Element Method. However, the application of this approach to trace the signature curve of composite columns with channel sections is cumbersome and presents a high computational cost. Therefore, this work presents a simple, efficient, and accurate methodology to evaluate the local and distortional buckling load of laminated channel columns applying the Rayleigh-Ritz method. The accuracy of the proposed approach is assessed comparing the results obtained using the Finite Strip Method, Finite Element Method, and experimental data available in the literature.

Nonlinear analysis of static and dynamic stability of spatial truss structures using the positional Finite Element Method

2024-12-13T13:59:36+00:00

In order to ensure stuctural safety, in addition to checking for strength, structures must also be analyzed for stability, as structural collapse can occur due to material rupture or instability. The study of local or global stability loss in a structure is conducted considering geometric nonlinearity, where the structure's equilibrium is always satisfied in its deformed configuration. One way to study structural instability is by using numerical methods such as the Finite Element Method (FEM) based on positions. Positional FEM relies on the change in the body's configuration through an initial and current mapping system. This characteristic considers geometric nonlinearity. In this context, this work aims to apply positional FEM with a total Lagrangian reference system for the analysis of instability in spatial truss structures. The equilibrium equation system will be solved using the Newton-Raphson method, and dynamic behavior will be considered using the Newmark method. The expected results include nonlinear equilibrium curves, structure responses over time, natural frequencies, and vibration modes.

Nonlinear Dynamics of a Cantilever Beam under a Transversal Harmonic Follower Force

2024-12-13T14:02:49+00:00

The nonlinear geometric of cantilever beams is well disseminated in current literature. Normally, in this type of analysis the load does not maintain its constant slope throughout the analysis. This work addresses the case of large displacements for beams considering a follower transversal load to the deformed axis. This type of situation generates interesting nonlinearities and has several applications, for example, the wind load in wind turbine blades must be considered always perpendicular to the beam element axis. This work will also address the dynamic behavior of this structural system as well as its implications regarding stability. According results for large response its possible to observe the great influence of load level, the beam curvature suffer a abrupt change highlighting the importance of nonlinearity in this problem

Nonlinear normal modes to analyze the nonlinear forced vibrations of cylindrical shells with internal resonances

2024-12-13T14:06:17+00:00

In this work, the nonlinear normal modes are applied to analyze the nonlinear forced vibrations of a simply supported cylindrical shell with internal resonances. The nonlinear equilibrium equations are obtained considering the Donnell's nonlinear shallow shell theory. The modal solution to the transversal displacement field, used to discretize the equilibrium equations, is obtained by perturbation techniques that consider an internal resonance between the linear vibration modes. The discretized equations of the reduced order model are obtained using an invariant manifold approach. The nonlinear dynamic behavior is analyzed from the resonance curves that are obtained by the continuation method. The resonance curves are obtained for both full and reduced order models, and these results are compared to determine the level of a harmonic load that can be reliably represented by a reduced order model. Several multi-modes are considered to assemble the best nonlinear normal modes basis that contains the most important information of the interactions that occur between the modes of the transversal displacement field. Time responses and phase portraits, with mapping Poincaré sections, are also used to analyze the nonlinear dynamic behavior of the cylindrical shell and to check the accuracy of the reduced order models.

Nonlinear Vibrations of Wind Towers with Variable Cross Section and Elastic Foundation Under Base Excitation

2024-12-13T14:08:27+00:00

In this work, the nonlinear vibrations of coupled tower-nacelle-blade system, considering variable cross section and elastic foundation, subjected to base excitation (harmonic and seisme) are studied. For this, the nonlinear Euler-Bernoulli beam theory is applied to model the tower and nacelle and the elastic base is described as a Winkler model, considering contact problem. The Rayleigh-Ritz method together with Hamilton principle are applied to obtain the set of nonlinear dynamic equilibrium equations which are, in turn, solved with the fourth order Runge-Kutta method. Numerical results show the strong influence of parameters and base excitation on the natural frequencies, on the resonance curves and on bifurcation diagrams.

Optimization of tuned mass dampers parameters using Artificial Neural Networks

2024-12-13T14:10:40+00:00

Control systems are usually employed to minimize the dynamic effects on structures. These controllers must be designed according to the physical and geometric characteristics of the system and the environmental loads to which the structure will be subjected. Passive control is the most suitable for extreme events because it does not depend on an external power source to function properly. The use of a linear attenuator, such as the tuned mass damper (TMD), allows for dynamic analysis in the frequency domain, which provides a reduction in the computational cost of the analysis. Among the several methods used to determine the optimal parameters of the damper, analytical methods in their closed form can be applied to simpler structures. In structures with several degrees of freedom or complex geometry, the optimal TMD parameters, as well as its optimal position, can be acquired by methods based on stochastic optimization. This kind of problem is commonly solved in the state-of-the-art by Metaheuristic algorithms. However, in general, these procedures require high computational costs, which makes Artificial Neural Networks (ANN) a viable alternative to minimize the processing time. Thus, this paper proposed a methodology based on ANN in comparison with the Circle-Inspired Optimization Algorithm (CIOA) to determine the optimal parameter of tuned mass dampers, i.e., the damper period. Training of the neural networks was performed with a dataset of optimal TMD values, which were obtained in the frequency domain. The model developed from these results was subsequently tested on different shear-building models, including the influence of seismic excitation. The response of the structures in displacements was evaluated with the optimal values obtained through ANN and compared with the structures without the control device. In addition, the optimal parameters obtained by ANN were also compared with the closed analytical formulations. The results obtained by the neural networks were as effective as the CIOA metaheuristic algorithm but required up to 0.02% of its processing time.

Parametric study of the apparent modal parameters of crowd-footbridge systems

2024-12-13T14:13:49+00:00

The modal parameters of footbridges are time-variant as pedestrians walk along them, resulting in a new dynamic system comprising the isolated structure and the walking persons. This phenomenon is known as human-structure interaction (HSI) and is particularly significant for lightweight footbridges, where the effective damping ratio of the combined system is significantly higher than that of the isolated structure. This paper proposes an analytical-numerical approach to address the effects of HSI on the modal parameters of the coupled system. The effective damping ratios and natural frequency are determined by solving the eigenvalue problem of a two-degree-of-freedom mass-spring-damper system, with one degree of freedom representing the isolated structure and the other representing the equivalent model of the walking persons. The obtained results are compared with experimental measurements from the literature, illustrating the effectiveness of the proposed approach while also demonstrating its computational cost-effectiveness in comparison to existing methods.

Seismic Performance Assessment of an Unreinforced Masonry Historical Building Using Nonlinear Static Methods

2024-12-13T14:16:41+00:00

Historical heritages embody the identity and evolution of a people, making their preservation paramount. Buildings from the 17th and 18th centuries constitute a significant portion of this heritage, and evaluating their behavior under potentially damaging actions is crucial for mitigating and preventing irreparable losses. Despite Brazil's location in a tectonically stable region, seismic events with the potential for considerable damage have occurred and could impact these historical structures. Among the methods for assessing the seismic vulnerability of buildings, nonlinear static methods stand out, aiming to quantify the effect of earthquakes on a structure using an incremental lateral force analysis considering nonlinearity, known as pushover analysis. This study aims to evaluate the seismic performance of an 18th-century masonry historical building using a nonlinear static method, notably the oldest one in the urban complex of the central-south region of the state of Ceará. To this end, a finite element numerical model of the main façade was developed to represent the historical building. The seismic performance of the building was then evaluated, and the expected damage to the historical building under seismic loading was quantified.

Study of the influence of physical nonlinearities of spherical caps made by Elastomeric Materials

2024-12-13T14:19:58+00:00

The analysis of the behavior of structural elements in terms of variations in physical and geometric influences has been the subject of study since the early days of mechanical and structural engineering research. When it comes to shells, especially those composed of hyperelastic materials, many researchers have carried out work evaluating both the influences of the type of curvature of these elements and the type of deformation expected due to hyperelasticity. This work will investigate the behavior of a spherical cap with a boundary condition established by the locking of the circumference that makes up its base and subjected to uniformly distributed loading on its surface. Two different types of material were considered, one elastic following Hooke's Law and the other hyperelastic represented by elastomeric constitutives models. The Novozhilov and Donnell-Mushtari-Vlasov (DMV) shell theories together with the Rayleigh-Ritz method are used to obtain the governing equations of the problem. The displacements will be approximated using trigonometric functions in the circumferential direction and the Legendre polynomial of the first type in the meridional direction. Linear results are obtained, such as natural frequencies, and non-linear results, such as frequency-displacement and load-displacement relationships.

Theoretical Analysis of Human Rhythmic Jumping on Oscillating Floors

2024-12-13T14:22:12+00:00

This study investigates the dynamic interaction between a human jumper and a concrete rectangular plate under cyclic vertical jumps. The plate is described using Von Kármans nonlinear relations, while the jumper is modeled as a spring-mass-damper (SMD) system with a harmonic force acting on the humans center of mass to represent the propulsion force during jumping. The mechanical system is described by a set of piecewise smoothtouch nonlinear differential equations, allowing the loss of contact between the jumper and the plate during jumps. The results show that the jumper exhibits complex dynamics, including periodic and chaotic responses, depending on the systems parameter combinations. Additionally, the SMD model can affect the mechanical behavior of the plate by coupling the jumpers vibration modes with the structures, creating new resonance frequencies and redistributing the vibrational energy.

Time domain analysis of a pultruded composite cooling tower under dynamic wind loads

2024-12-13T14:25:00+00:00

Pultruded glass fiber reinforced polymer (pGFRP) profiles have been used in cooling tower frame structures for decades. Its advantageous properties such as high strength-to-mass ratio and corrosion resistance make it well-suited for the highly humid environment of cooling towers. On the other hand, pGFRP also has a relatively low modulus of elasticity, about 10% that of steel, which makes the structures more flexible. This results in low natural frequencies and brings the risk of resonance to dynamic loads such as wind fluctuation. The present study assesses the response of a pGFRP cooling tower under dynamic wind loads. A finite element (FE) model of the structure was developed to obtain its modal properties and assess the structures dynamic response. A spectral representation method was implemented in Python to generate artificial wind fluctuation time series, which were input into the FE model to produce the fluctuating component of the wind drag force. The results show that, despite the flexibility, the structure satisfies the serviceability limit states and can be safely exposed to dynamic wind loads, benefitting from the materials favorable properties.

Analysis of Tensile Specific Deformation of Fiber Reinforced Concrete Beams via FEM

2024-12-16T12:32:17+00:00

The use of fiber reinforced concrete (FRC) for structural purposes has been gradually increasing and this growth has resulted in the emergence of several standards. With regard to Brazil, the first standard related to the design of FRC structures was published in 2021. In this standard, the calculation aspects for sizing FRC structural elements are represented, however, the behavior of specific tensile deformations is not fully illustrated. Based on this, a study is presented regarding the determination of the tensile specific deformation at the beginning of the plastic boundary (ε_Fp) of beams fiber reinforced concrete (FRC) and beams fiber reinforced high strength concrete (FRHSC). To establish these deformations, we used works found in the literature and through numerical analysis via the finite element method (FEM), and through the mesh convergence analysis of the finite elements obtained from the ABAQUS software, the beams were analyzed. According to the study carried out, it was found that, for FRC beams and FRHSC beams, ε_Fp corresponded to a value in the order of 5.0 and 6.5, respectively. This illustrates the possibility of greater deformation occurring at the beginning of the plastic boundary for the FRHSC and shows the potential of the work to contribute to the establishment of guidelines for the structural aspects of the FRC.

Applicability of inverse analysis to obtain the tensile behavior of bamboo bioconcretes

2024-12-16T12:37:14+00:00

In view of the difficulties in obtaining traction laws in the experimental field, it is of the utmost importance to adopt alternative tools to overcome this problem. Thus, this work is a brief manual for obtaining tensile laws using numerical modeling, which describes the steps for obtaining them, from defining the fixed parameters of the numerical model to characterizing the material's tensile mechanical behavior. The DIANA® software was used to run the numerical simulations and the numerical model calibration was based on average results of experimental curves. The target material for this study is a new bamboo bioconcretes developed by researchers at COPPE/UFRJ. The results show that the traction laws developed through inverse analysis using numerical modeling are highly accurate compared to experimental responses. The calibration of the numerical model makes a significant contribution to the quality of the results. Among the evaluated tensile models, the ones that best reproduce the experimental behavior of the bamboo bioconcrete are the multilinear and exponential models.

Comparative Analysis of Constitutive Models for Concrete Using the Finite Element Method: Microplane Model, Menetrey-Willam, and Concrete Damaged Plasticity

2024-12-16T12:40:35+00:00

The nonlinear physical behavior of concrete can be represented by models from the theory of plasticity with associated damage. In the commercial software ANSYS and ABAQUS, three distinct models are available that can represent the mechanical behavior of concrete, considering the uniaxial and biaxial states under compression and tension, named the Microplane Model, Menetrey-Willam Model, and Concrete Damaged Plasticity. This article aims to present the theory regarding these models, examples of application, and sensitivity analysis of the plastic and damage parameters in numerically simulated cylindrical specimens. Finally, there is a comparison of the use of these models in a reinforced concrete beam simulated with cyclic loading.

Comparative study of strategies for creep simulation in the calculation of second-order effects in reinforced concrete columns

2024-12-16T12:43:44+00:00

This dissertation project aims to investigate the effects of creep in reinforced concrete columns, considering different strategies. With the democratization of computer access and the evolution of structural models, most part of building projects developed nowadays relies on more comprehensive structural models, which incorporate non-linear behaviors in their analysis, either through simplified or refined approaches. However, despite the evolution of these models, the simulation of the effects of creep is an aspect that still needs improvement. Creep is defined as the phenomenon of increasing deformations in concrete over time when subjected to constant stress. The topic is especially relevant in reinforced concrete columns, where the phenomenon can cause increased forces as well as increased second-order moments. The complexity of the creep phenomenon leads to simplified methods dominating the scenario, although there is still a shortage of studies on practical methodologies applicable in projects. In this context, the main objective of this work is to conduct a comparative analysis between commonly employed methods in practice for simulating creep with more refined models. The strategies considered are the Approximate Method of Additional Eccentricity e_{cc}; Standard-Column Method coupled with M, N, 1/r Diagrams considering creep effects through extended stress-strain curve; General Method coupled with M, N, 1/r Diagrams also considering creep effects through extended stress-strain curve; and Mathematical Model with analytical incorporation of the time variable. This study aims to formulate algorithms, to produce different models and simulations, to compare the results obtained by the different analyzed methods, and, if necessary, to propose practical solutions to achieve more reliable results. In this way, this study seeks to highlight both the effectiveness and limitations of the analysis strategies considered, aiming to contribute to the improvement of safety in implementing these strategies, especially those presented by Brazilian standards.

Corrosion impact analysis: a numerical model for reinforced concrete structures using the Finite Element Method based on Position

2024-12-16T12:51:23+00:00

Reinforced concrete (RC) structures face environmental challenges like carbonation and chloride ingress, leading to decreased stiffness, serviceability, and security. A key issue is accurately simulating structural responses to environmental effects and their impacts. This article addresses this by proposing a numerical model based on the Finite Element Method with Positions (FEMP), employing frame elements to forecast post-corrosion structural behavior. Subsequently, a probabilistic study is conducted using Monte Carlo simulations to predict failure probabilities amidst changing environmental conditions. The study reveals corrosion's significant impact on structural stiffness and a high probability of failure within 50 years. These findings underscore the necessity of constructing structures with future climate change challenges in mind.

Coupling of discrete and smeared cracking models applied to reinforced concrete structures

2024-12-16T12:54:41+00:00

The nonlinearity inherent to concrete comes from the cracking process and the inelastic phenomena in the fracture process zone (FPZ). It is understood that initially, microcracks appear diffusely in the material medium, even under low-intensity loading conditions. In these initial stages, cracking develops stably, causing the structure's nonlinear response, which can still absorb loads. With the advancement of the process, the crack coalescence causes the significant growth of cracks so that a discontinuity in the material medium is observed. At this stage, propagation occurs in an unstable manner, and the structure loses the ability to absorb loads. In reinforced concrete, the manifestation of cracks occurs through multiple fronts due to the reinforcement steel that absorbs tensile forces and locally contains the crack propagation, which initially appears in regions not covered by the reinforcement steel. In more advanced stages, cracks can be observed that surpass the reinforcement steel region and propagate throughout the structure until its collapse. Over the years, two main approaches have stood out in the representation of concrete fracturing: smeared crack models and discrete crack models. Each model aims to represent the concrete response based on different hypotheses. In the smeared models, the medium is considered continuous, and the effects of cracking are represented by the elastic degradation of the material computed through constitutive models. In discrete models, the crack is represented by a material discontinuity inserted into the mesh. This work presents a strategy that combines smeared and discrete models applied to the modeling of flat reinforced concrete structures. The reinforcement steel will be represented by one-dimensional elements with elastoplastic behavior while maintaining the perfect bond between the steel rebar and concrete. In the representation of concrete fracturing, the FPZ will be represented by a scalar damage model for the continuous degradation of the material, and from a critical damage value, a discrete model, which considers multiple crack fronts, is activated by inserting a discontinuity into the mesh using a nodal duplication strategy, thus describing the final rupture process. Finally, numerical simulations will be presented to illustrate the model's performance.

Dynamic Analysis of Slender Buildings under Wind Loading

2024-12-16T12:57:25+00:00

This dissertation project aims to understand and compare methods that simulate the dynamic characteristics of atmospheric wind loads acting on slender structures, with a focus on NBR 6123 and the Synthetic Wind Method. The amount of research conducted on this topic since the 1960s has led to significant advancements in understanding the dynamic behavior of wind. This progress has facilitated the development of methodologies for quantifying its impact on buildings and the continuous refinement of these methodologies up to the present day. In this context, it is possible to encounter two key approaches: NBR 6123 (2023), developed by the Brazilian Association of Technical Standards, and the Synthetic Wind Method, initially proposed by Franco (1993). The Brazilian standard provides two methods to determine maximum values of variables such as acceleration, displacement, and forces for structures subjected to wind, without describing how these values vary over time. Despite advances in wind engineering studies and methodologies, the procedure described in the 1988 version of the standard remained unchanged in its 2023 update. On the other hand, the Synthetic Wind Method, first published in 1993 and subsequently refined until 2014, works by decomposing the fluctuating component of wind into harmonic functions. This approach not only allows to obtain absolute maximum values but also provides the structural response over time. To address this, a comparative study is planned between NBR 6123 (2023) and the most updated version of the Synthetic Wind Method. Additional relevant methods may also be included in the analysis to identify the limitations, advantages, and disadvantages of each approach.

Eco-resilient (ECORE) concrete constructions: a new challenge and a new concept

2024-12-16T13:00:13+00:00

This paper presents a new concept concerning the development of eco-resilient concrete constructions, that is to say constructions with a reduced carbon footprint and which can withstand mechanical stress and physico-chemical attacks worsened by climate change. After a critical analysis of current research and development policies in the field of concrete construction, a new global approach is proposed which should allow this concrete construction profession to better respond to the challenges caused by global warming. This approach is based on two strong ideas: 1) the use of fiber concretes in combination with passive or active reinforcements in all constructions susceptible to crack 2) the use of numerical models based on non-linear finite element calculations in order to optimize the design of eco-resilient concrete constructions.

Formulation of a nonlocal bimodular damage model based on mechanical properties parametrization

2024-12-16T13:02:09+00:00

Material media representation by damage models presents difficulties in the parametrization process. The damage laws are generally written as functions of mathematical variables and, in many cases, without physical meaning. This lack of connection between the evolution of degradation and the material properties requires a diversity of tests to numerically reproduce results obtained experimentally, which makes such a process slow, costly, and subjective. Based on this context, a constitutive model capable of describing the material response with damage evolution laws defined in terms of material parameters obtained from experimental tests is proposed in this paper to overcome parametrization adversities. Such a model is focused on reproducing the bimodular behavior of quasi-brittle materials, such as concrete, which respond differently to tension and compression efforts. While these materials have a significant resistance under compression, they manifest cracks when subjected to tension, collapsing due to fracturing. The current model presents a nonlocal character as a regularization technique to avoid strain localization phenomena. The nonlocal equivalent strains are calculated according to the principal strains associated with uniaxial constitutive laws and physical parameters obtained experimentally. Finally, numerical simulations are conducted to validate and verify the constitutive model performance to represent the response of concrete structures.

Heterogeneity Modelling of Concrete Structures by Nonlocal Damage Models

2024-12-16T13:05:01+00:00

The behavior of structural concrete is usually represented by considering the homogeneous material media and its macroscopic properties. The problem can be represented in more realistic models considering the material as a heterogeneous multiphase media. In representing heterogeneity, either a direct or indirect description of the phases can be considered. The direct approach considers the phases to be geometrically described in the discrete model. In the indirect approach, phases are represented by homogenizing their physical properties or by the random distribution of points in the domain with material parameters corresponding to each phase. In the physically nonlinear analysis using the Finite Element Method, a constitutive model capable of differentiating the response to tension and compression and computing the gradual cracking process of the concrete is necessary. Furthermore, these models must be coupled with regularization mechanisms to deal with numerically induced localization problems, such as the nonlocal approach. Given the above, this work proposes a model for representing the heterogeneity of concrete aiming at the physically nonlinear analysis of structures. Two phases will be considered to describe the heterogeneity: the cement matrix and the coarse aggregates, which will be incorporated into the discrete model using a hybrid method, which combines characteristics of direct and indirect methods. For material media degradation, a non-local damage model will be adopted with appropriate constitutive laws for each constituent material. Finally, numerical simulations will be presented to evaluate the model's characteristics.

Massivity index and numerical analysis of concrete specimens

2024-12-16T13:08:32+00:00

This study is focused on the behavior of massive concrete structures and the stresses caused by the temperature variation, which occurs along the development of the hydration reaction. However, before a heat transfer analysis takes place, it is necessary to determine if the structure is massive or not. In this scope this article studies a proposal of enhanced massivity index, which is helpful to determine what kind of analysis is more suitable for each structure element. It also presents an analysis of a concrete block, which was modeled with two different softwares, considering also two different situations. The first one considered the block was filled with concrete at once. The second considered the concrete was discharged in four steps, which lasted fifteen minutes each. That gives us an insight of the thermal effects variation according to the different possible concrete plannings. The model results were compared with experimental results, since the the block was concreted in the laboratory and monitored with thermocouples.

Numerical Analysis of Semi-Buried Cisterns Constructed with Precast Cementitious Plates

2024-12-16T13:12:40+00:00

Semi-buried cisterns formed by cementitious plates represent an important solution for water harvesting and storage in arid and semi-arid regions, being fundamental to ensure water security and combat water scarcity, as presented in the governmental program One Million Cisterns. Therefore, this study proposes to explore preliminary strategies of numerical modeling using finite element methods, employing Abaqus Simulia software. The objective is to analyze in detail the structural behavior of these cisterns, aiming to optimize their design and performance. The adopted methodology involves a literature review to support the numerical modeling and subsequently compare the results with traditional analytical methods. The preliminary results indicate a promising possibility of reducing the horizontal reinforcement of the walls compared to the technical recommendations of the current agencies. Thus, preserving safety and durability conditions while implying constructions with lower costs, thereby promoting the social development of the served communities. Therefore, this study represents a significant advancement in the understanding and optimization of semi-buried cisterns, emphasizing their importance and potential to address challenges related to water storage.

Numerical analysis of the beam-column connection stiffness in precast concrete with welded steel angle

2024-12-16T13:15:54+00:00

The use of precast elements in civil construction has the main advantag of expediting the structures construction process, as well as increased technological control of the materials used. Despite this, precast structures presente a discontinuity in the connections between the elements, such as between beam and column. This has become an important object of study, where we seek to improve the continuity of these regions, ensuring better distribution of loads and increasing the stiffness of the connection. Therefore, the objective of this study is to analyze, using numerical methods, the stiffness of the beam-column connection in precast concrete using a steel angle welded to the beams and column. To achieve this goal, the structure will be modeled using the Finite Element Method. A structural system composed of two beams and a column with the steel angle welded to the elements in the connection region. The angle is employed to assure a level of continuity in the connections between structural elements and increase its rigidity hence creating a with semi-rigid condition. The result of the numerical model will be verified with a proposed analytical model, considering the existence of a spring in the connection that guarantees the increased stiffness, reducing rotation in the support. From the rotation predicted in the numerical model, we can estimate the rotational stiffness and apply it to the analytical model for comparison and validation. In the numerical model, 4 analyzes will be carried out, the first analysis wont have the welded angle. The other three analyzes will be carried out with the welded angle, changing the weld area on the column and beams. Finally, the results are expected to demonstrate that the application of the welded angle on the beam and column presents better performance for semi-rigid connection, bringing greater rigidity to the connection, reducing the existing rotation and achieving a better redistribution of loads, thus ensuring a lower maximum positive bending moment for the beam. It is also expected that angles with larger weld areas guarantee greater rigidity for the connection than those with smaller weld areas.

Numerical modeling of steel deck slabs with position based finite element method and immersion techniques

2024-12-16T13:19:05+00:00

Steel deck slabs are an efficient construction system thanks to the deck's double role of molding the concrete in the builiding phase and resisting to flexural loads within its lifespan. Due to the high costs and semiempirical nature of experimental programs, it is important to formulate a numerical model that broadly and accurately describes the behavior of these structures. This article proposes a numerical model employing a finite element method based on positions, which naturally allows for geometrical nonlinear analysis of structures. A prismatic element is developed to represent the concrete matrix, and active face immersed elements are included to represent the steel deck. Additional immersed bar elements are also featured as reinforcement bars. The results are expected to conform with previous numerical and experimental results from literature and to allow for the proposal of new benchmarks taking advantage of the capabilities of the employed theory.

Numerical simulation of behavior of masonry mechanics made with ecological bricks

2024-12-16T13:22:32+00:00

Soil-cement brick masonry structures have gained prominence in developing countries due to their practicality, low cost and excellent ecologically sustainable alternative. However, the literature presents few numerical studies on masonry structures in soil-cement bricks, since most of the studies carried out focus on concrete and ceramic bricks. Therefore, in this work, the finite element model of a small wall made of soil-cement brick with structural masonry mortar joints, subjected to compression, is calibrated. The experimental analysis of these small walls was conducted at the Laboratory for Experimental Analysis of Structures at the Federal University of Minas Gerais, and the experimental results are used to calibrate the numerical simulation. The numerical model was developed in the finite element program ABAQUS CAE. A detailed micromodeling strategy was adopted, that is, the models were developed considering the individual representation of bricks and mortars, in addition to the interface between the materials. Using the proposed finite element model, a numerical investigation was conducted to verify the validation of the model concerning experimental investigations. The present study allowed us to adequately replicate the concentration of damage in the bricks, corroborating what was observed in the experimental tests.

Numerical Simulation of Three-Point Bending Test on Steel Fiber-Reinforced Concrete Specimens Using DIANA FEA

2024-12-16T13:28:11+00:00

This study presents a numerical investigation of the behavior of steel fiber-reinforced concrete specimens under three-point bending tests employing different model approaches. Steel fiber-reinforced concrete has gained significant attention in the construction industry due to its enhanced mechanical properties, including improved ductility and crack resistance. Understanding its behavior under loading conditions is crucial for optimizing structural design and ensuring durability. The simulations were conducted using DIANA Finite Element Analysis (FEA) software, and the comparative analysis was design to compare their effectiveness in predicting the structural response. The simulations were validated against experimental data from laboratory tests to ensure the accuracy and reliability of the numerical predictions. Through comparative analysis, this study evaluates the performance of each modeling approach in predicting key parameters such as load-displacement response, crack mouth opening and ultimate failure mode. Insights gained from these comparisons will provide valuable guidance for selecting the most appropriate modeling technique for similar structural analyses in practical engineering applications.

Seismic Analysis of Nonlinear Reinforced Concrete Frame Structures

2024-12-16T13:39:56+00:00

Seismic structural analysis attracts significant interest in Brazil, even though much of the country exhibits low seismicity. Some regions in northwestern Brazil, such as most of the state of Acre and the southwest of the state of Amazonas, present ground motion accelerations that require dynamic analysis for earthquake loading. The construction of some special structures, such as nuclear power plants, requires the consideration of their seismic responses, regardless of their location. The internal forces provided by the Response Spectrum Method, in the frequency domain, are not always suitable for the design of reinforced concrete structures. The behavior of concrete is different under compression and tension. The sum of the modal absolute values through SRSS (Square Root of the Sum of Squares) and CQC (Complete Quadratic Combinations) approaches provides maximum absolute internal forces. However, negative or positive values indicate compression and tension, and reinforcement design is greatly influenced by whether stresses are compressive or tensile. The purpose of this research is to present a methodology for the seismic dynamic analysis of nonlinear framed structures, in the time domain, in which the equilibrium is rigorously examined at the end of each time step. The constitutive models adopted for the cyclic behavior of concrete and steel are discussed. A Timoshenko beam element suitable for this nonlinear analysis is presented. A time integration algorithm, based on Newmark's implicit method, is developed using the element's implicit stiffness matrix that considers the nonlinear behavior of the material. Equivalent nodal forces are calculated from accelerograms of known earthquakes. The adoption of the classic Rayleigh damping model is discussed. The numerical implementation is detailed. Examples are presented and conclusions are drawn.

Sensitivity Analysis of Oil Well Cement Pastes Under Creep

2024-12-16T13:42:27+00:00

Creep is the phenomenon of increasing deformation under sustained loads. Cement pastes, used for cementing oil wells, are subjected to this phenomenon through the application of mechanical, temperature, and pressure loads. These pastes under these conditions are the focus of this study. Consequently, this work uses the creep functions developed in Vitor Colimodio's master's dissertation, defended at COPPE research center of Universidade Federal do Rio de Janeiro, and applies them on the behavior of concrete casings for cementing oil wells. A sensitivity analysis was performed to evaluate the importance of each variable. The Tencim software, developed at COPPE, was used to perform the models.

Thermal behavior of air-fluid in triangular cavities of 3D printed concrete walls

2024-12-16T13:45:13+00:00

The civil construction industry has shown increasing interest in 3D printing technology due to its ability to produce highly complex structures with different internal wall geometries using concrete as the raw material. With the advancement of technology, the use of numerical modeling software has become necessary to simulate heat transfer and the thermal performance of objects developed through 3D printing. The objective of this work is to simulate heat transfer in a wall geometry obtained by 3D printing, featuring triangular cavities filled with air, and to compare the results using two different approaches. Initially, computational simulation with air voids in a wall as solid elements will be presented using DIANA FEA software, and subsequently, the air voids will be treated as a fluid using OpenFOAM software. The comparison between the two simulations will be presented, highlighting the influence of modeling air voids on the thermal properties of 3D-printed structures.

Analysis of the climatic effects on the stability of a tailings dam

2024-12-05T12:27:27+00:00

Tailings dams are structures of significant economic and environmental importance in the Brazilian territory. These structures play the fundamental role of containing tailings, which consist of water and waste resulting from regional mining activity. The release of this material into nature results in serious environmental consequences. Additionally, in situations of dam rupture, downstream populations are subject to direct losses from the generated flood wave and indirect damages due to contamination of the groundwater that supplies nearby cities.
These structures have become the focus of more detailed investigations due to the increasing frequency of incidents and accidents. Recently, Brazil witnessed two significant disasters that resulted in substantial loss of human life and considerable environmental damage: the collapse of Barragem I at the Mina de Feijão in Brumadinho and the Fundão Dam disaster in Mariana, both located in the state of Minas Gerais.
Because of these two incidents of great magnitude, the analysis of mining dam stability and constant surveillance of these structures have become the focus of detailed investigations. Such analyses consider various factors, going beyond the consideration of the structure's geometry and the physical and mechanical parameters of the soil, also the evaluation of water presence in the dam through a flow analysis. The study of water presence in the dam is highlighted because it is closely related to the assessment of susceptibility to liquefaction, which was the main cause of the incidents in Mariana and Brumadinho.
Based on this, the present study aims to analyze the impact of precipitation on the stability of a mining dam. For this purpose, Plaxis 2D for numerical modeling will be employed, through which models will consider climate effects such as rainfall and evapotranspiration to obtain the desired results. The results will be presented in terms of the safety factor over time. The variation in stability resulting from climatic fluctuations will be studied.

Effect of spatial variability of soil properties on slopes stability under rapid water drawdown conditions

2024-12-05T12:30:44+00:00

Stability analysis of slopes is a fundamental problem of Soil Mechanics. Its main objective consists of evaluating the potential failure of the slope structure under a prescribed loading mode. A major component of the latter refers to the seepage forces induced by pore-pressure gradient, which is known to be responsible of destabilizing effects. This contribution employs a kinematic approach of limit analysis theory to obtain upper-bounds solutions to the stability problem of saturated slopes submitted to rapid water level drawdown. Random fields are used to model the uncertainty surrounding the spatial distribution of soil cohesion, friction angle, and permeability. In the context of effective stress governing the strength capacities of the soil material, it is shown that the seepage forces related to the water flow regime can be considered as external volumetric loads in the assessment of stability. The hydraulic problem governing the water filtration velocity is evaluated by resorting to an analytical variational approach, whose results are validated by comparisons with finite element solutions. The impact of hydraulic-related parameters on stability is first investigated for slopes within a deterministic framework. Subsequently, random fields are considered to take into account the variability related to the spatial distribution of the material properties, which are discretized using the Karhunen-Loève expansion with numerically computed eigenfunctions. The failure probability of slopes is assessed through Monte Carlo simulations. Several analyses have been performed to discuss the influence of the spatial variability of relevant problem parameters.

Evaluation of the influence of masonry walls on the soil-structure interaction mechanism through computational modeling of a reinforced concrete building

2024-12-05T12:34:11+00:00

The present study aims to investigate the influence of masonry walls on the soil-structure interaction mechanism for a reinforced concrete building. For this purpose, two finite element models are developed using the SAP2000 program, namely: (i) a three-dimensional model without masonry walls and (ii) a three-dimensional model with discretized masonry walls. The latter model, closer to reality, provides greater stiffness in the superstructure. In the analysis, both fixed supports and spring supports are employed. The results of the model with discretized masonry walls are similar to those of the model without masonry walls, i.e., when considering the soil-structure interaction, a redistribution of forces in the structural elements was observed. Peripheral columns showed an increase in demand while the central column showed a reduction in demand. There was a tendency for uniformization of differential settlements especially in the model with discretized masonry walls, and also an increase in positive bending moments in the spans and negative bending moments in the peripheral supports of the central beam at the ground level. That is, if the structural design does not consider settlements (as in the case of a design without soil-structure interaction), settlements can lead to localized plasticizations in the beams. Thus, the importance of refined models is perceived, and also, in cases where settlements are significant, the effect of soil-structure interaction is relevant in the design, not only of foundations, but also of the structure.

Fast semi-analytic sequential explicit coupling analysis of 3D planar hydraulic fracturing

2024-12-05T12:36:31+00:00

Hydraulic fracturing is a relevant issue in Geomechanics, especially when analyzing hydrocarbon production activities and their physical phenomena. Several numerical, analytic, and semi-analytic methods have been developed to predict fluid-driven fracture propagation response. Tradicional continuum-based numerical coupling methods, such as FEM or XFEM, allow the study of complex and realistic scenarios. However, they frequently require enormous computational effort, which is more evident in 3D modeling. On the other hand, most analytic solutions provide fast solutions but are limited to basic conditions, such as the analysis of the fracture domain only. In this context, semi-analytic methods are an alternative that can provide solutions faster than traditional numerical methods. In addition, those methods apply to more realistic scenarios than analytic solutions. This work proposes a sequential explicit two-way coupling methodology to analyze planar hydraulic fracture propagation in pressurized rock formations. The coupling methodology associates the Finite Element Method, used to solve the fluid flow problem, with the semi-analytical Displacement Discontinuity Method to solve the mechanical problem. The proposed approach allows predicting fluid-driven fracture propagation in a planar domain considering arbitrary in-situ stress and fluid flow conditions into the surrounding porous medium. The numerical results are compared to asymptotic analytical and numerical solutions showing good accuracy and expressively lower computational cost than traditional numerical schemes.

Finite element analysis of rock deformation in deep twin tunnels

2024-12-05T12:56:56+00:00

Relying upon a three-dimensional finite element analysis, this contribution investigates the instantaneous irreversivel response induced by the constitutive behavior of the rock mass in the convergence profile of twin tunnels. At the rock material level, elastoplastic state equations based on a Drucker-Prager yield surface with an associated flow rule are adopted in the modeling. As regards the tunnel support, the formulation accounts for the presence of an elastic shotcrete-like lining. From a computational point of view, the deactivation-activation method is used to simulate the excavation process and the installation of the lining. The accuracy of the finite element predictions is assessed through comparisons with the available analytical solutions formulated in a simplified scenario for the twin tunnel configuration. A parametric study investigates the mutual interaction induced by the proximity of the tunnels.

Impact of cold fluid injection on caprock integrity

2024-12-05T13:09:34+00:00

In Brazilian pre-salt fields, the extracted carbon dioxide (CO2) is reinjected with lower temperatures into the reservoirs to maintain reservoir pressure, improve oil recovery and reduce greenhouse gas emissions. The cold CO2 injection can alter the mechanical and hydraulic properties of the subsurface and induce variations in formation stresses. Stress changes can be sufficiently high to generate undesirable fracture propagation, damage the caprock, and activate natural fractures or geological faults. Consequently, they can induce seismicity, leaks, and contamination of shallower aquifers and CO2 release into the atmosphere. This work investigates the thermo-hydro-mechanical effect of cold fluid injection on caprock integrity. To this end, a fully coupled thermo-hydro-mechanical (THM) finite element model governs the rock formation behavior. The proposed model considers poroelasticity, fluid flow, and convection/diffusion heat transfer within the permeable rock formation under single-phase fluid flow conditions. The temperature diffusion, pore-pressure buildup, and stress variation under isothermal or non-isothermal injection scenarios are investigated. The results show reservoir expansion in the isothermal scenario due to fluid injection, which is expected in the pressurization process. In the non-isothermal scenario, the thermally disturbed region throughout the reservoir resulted in compaction rather than expansion, even though it was subjected to injection. The instantaneous drop in temperature induces a hard drop in pore pressure and plastic deformations in the reservoir. The lower interval of the caprock presents critical horizontal tension stresses compromising its integrity. Finally, the study adds valuable insight to better understand the complex cold fluid injection process, considering hydraulic, mechanical, and thermal coupling.

New approach to predict load-displacement curves of bored piles in homogeneous sandy soils: numerical analyses

2024-12-05T13:12:08+00:00

Large-diameter bored piles (LDBPs) are increasingly used as foundations elements for various structures such as tall buildings, highway bridges, retaining structures, and power transportation structures, among others. Stabilizing fluids like bentonite or polymers are commonly employed to maintain borehole integrity in soils with high water tables and low resistance. Previous research has highlighted the significant influence of stabilizing fluid and construction methods on the performance of bored piles. Due to the absence of routine design methods for bored piles with stabilizing fluids, full-scale instrumented load tests are regularly conducted to investigate load transfer mechanisms and predict bearing capacity. Alternatively, numerical modeling offers a cost-effective approach to analyze pile performance in layered soil with stabilizing fluids. However, the complexity of this problem, involving different soil layers, and the thin layer of soil-stabilizing fluids in the shear band, presents challenges for numerical analysis. In this study, a numerical model is proposed to analyze bored pile performance in sandy soil, considering different pile diameters and lengths. The model is calibrated using data from instrumented vertical load tests conducted on a 1 m diameter and 24.10 m long bored pile constructed with bentonite. Based on previous research findings, simplifications were made regarding soil layers and stabilizing fluids. Calibration involved utilizing Abaqus/CAE software and the Mohr-Coulomb failure criterion to describe granular material behavior. The soil model comprises a unique sand layer with 12.5 m in length and 36.15 m in depth and mean parameters derived from seven in-situ layers data. Load test simulations involve applying a vertical displacement equivalent to 10% of the pile 1m-diameter and analyzing load-displacement curves, load transfer mechanisms, interface behavior, and field stress-displacement. Initial findings show good agreement between experimental and numerical load results. Parametric analysis investigates the influence of pile geometry and soil properties on various resistances (Q_u,Q_b and Q_f) and coefficients (β,μ and K), proposing normalization expressions to estimate load capacities based on soil and pile properties. This study provides insights for developing supplementary methods to predict bored pile resistance and behavior and conducting future numerical analyses with stabilizing fluids and layered soils, thereby enhancing engineering practices in this field.

Numerical and parametric analyses of four unreinforced embankments on soft soils

2024-12-05T13:15:29+00:00

The conventional method of estimating safety factors during various stages of construction remains prevalent for embankment stability analysis. This typically involves employing stability charts, equations, Limit Equilibrium Methods, and the Strength Reduction Method, with the Limit Equilibrium Method being the most conventional and widely adopted. Additionally, there is an increasing trend in leveraging results from instrumented embankments for performance and stability analyses, indirectly assessing parameters such as horizontal and vertical displacements, pore pressure, and soil displacement volumes. Despite the widespread acceptance of these traditional methods, many studies tend to evaluate results individually, overlooking the benefits of direct comparison for a more comprehensive analysis. This study employs a variety of methods and approaches to assess the stability of embankments under different geometries and soil conditions. The safety factors for various embankment configurations are estimated directly using two stability charts (O'Connor and Mitchell, 1977; Barnes, 1991), two stability equations (Huang, 2018; Sampa and Schorr, 2024), the Limit Equilibrium Method implemented in GeoSlope software, and the Strength Reduction Method in Abaqus and Plaxis. Conversely, the results of the soil deformability analysis are normalized for the purposes of indirect stability analysis, with the Abaqus software serving this purpose. Analyses were conducted on models featuring either a single material for both the embankment and the soil foundation or different materials for each. The elastoplastic model employing the Mohr-Coulomb failure criterion characterized the behavior of granular materials, while modified Cam-Clay models implemented in Abaqus described the behavior of soft soils. The analysis results focus on three key aspects: (i) comparison of safety factors, (ii) establishment of behavior patterns from stability and deformability analyses, and (iii) discussion of limitations, accuracies, and advantages of the assessed methods and approaches. Finally, a critical analysis addresses the impacts of varying criteria used in Abaqus and Plaxis software for determining safety factors based on the Strength Reduction Method concept.

Numerical finite difference modeling of cylindrical panels under Pasternak contact constraints

2024-12-05T13:18:10+00:00

This study examines the radial displacement of cylindrical panels in contact with a Pasternak elastic foundation. Permanent contact situation between the structure and the medium is considered, characterizing the contact problem as bilateral. Simply supported isotropic cylindrical panels are defined and subject to concentrated external loads, and the finite difference method is adopted to approximate the equilibrium differential equation derivatives. The cylindrical panel approach follows the Sanders theory. Thus, a computational tool is developed, using the Fortran programming language, to study this class of bilateral contact problem. The results analyze focus on: the panel radial displacements for different meshes when nodal points variation occurs in different directions; the influence of the cylindrical panel thickness; the stiffness offered by the two parameters base model; and the boundary condition influence.

Numerical modelling of a soil structure interaction for a torpedo base conductor in a petroleum well under an extreme lateral load

2024-12-05T13:21:34+00:00

This work aims to compare the performance, regarding the soil structure interaction, of a torpedo base conductor and a jetted conductor, considering a drilling rig drift-off scenario. This can be considered an extreme load scenario and the results will be shown for lateral loads coming from the interaction between the wellhead and the drilling rig, drilling riser and BOP.
A complete 3D CAD model of the Torpedo Base Conductor was created and the soil was also modelled with 3D elements. Based on previous references, the selected 3D soil element was the Drucker-Prager constitutive model (Costa, 2008, Aysen, 2016 and Sanomia, 2016). Notably, the Drucker-Prager model accounts for non-homogeneous soil, meaning that the material properties vary with depth according to its undrained shear strength profile.
The final results show the behavior of soil under lateral loads for both the torpedo base and the jetted conductor, as well as the structural response. The final conclusion is that the torpedo base has a better performance under lateral loads than the jetted conductor and can be considered a good well foundation solution to mitigate problems associated with interventions with dynamic position drilling rigs in shallower water depth.

Numerical simulation of the lateral load test on piles through a parametric analysis

2024-12-05T13:24:40+00:00

Pile foundations are utilized to transfer load from the superstructure to the soil mass when the surface layer of the ground exhibits low load-bearing capacity. For an axially loaded pile, the load is transmitted to the soil through lateral friction at the soil-pile interface and via tip resistance. However, these elements are subject to significant lateral forces in addition to vertical ones. The resistance of piles to lateral loads depends on boundary conditions, stiffness, and concrete strength of the pile, as well as soil type, soil stiffness, and soil strength. Several models are employed to analyse laterally loaded piles, including soil modelling using nonlinear springs, commonly known as p-y curves. This article aims to investigate the impact of pile geometric properties, soil type, and the chosen model on simulating soil-pile interaction on the structural performance of a pile embedded in soil subjected to a transverse load. The study encompasses the variation of three pile diameters (60 cm, 80 cm, and 100 cm), three pile lengths (5.5 m, 10.5 m, and 15.5 m), and three soil types (soft clay, stiff clay, and moderately compacted sand). The effects of diameter (D), pile length (L), slenderness ratio (L/D), and soil type on the lateral response of the pile are examined. Additionally, an analysis is conducted regarding the influence of linear and nonlinear (p-y curves) Winkler models on simulating soil-pile interaction. The presented results indicate that the foundation behaviour, when considering soil-pile interaction, is contingent upon various factors and should be rigorously assessed by designers. It is noteworthy that, depending on the soil type, soil modelling using horizontal linear springs yields acceptable results, obviating the need for a nonlinear model. However, when soil particles exhibit friction or low cohesion, a careful analysis of soil parameters and the chosen model for simulating soil-pile interaction is warranted, with numerical simulation via FEM in conjunction with lateral load testing recommended to determine the optimal method.

Probabilistic Analysis of Slope Stability Considering Random Fields

2024-12-05T13:26:59+00:00

The study of slope stability is of paramount importance for society, as it enables the evaluation of slope security and the establishment of alert parameters to mitigate financial losses and, in severe cases, prevent human casualties. Improving alert criteria necessitates a comprehensive assessment not only of the slope's safety factor but also its probability of failure. Therefore, the use of probabilistic techniques becomes imperative, with the Monte Carlo Method (MCM) emerging as a prevalent choice in geotechnical investigations. Employing MCM for slope stability involves modeling the target profile while varying crucial material parameterssuch as friction angle, cohesion, and specific weightin each iteration. As a result, the outcome yields a distribution of safety factors, aiding in the assessment of both average safety levels and failure probabilities. Failure probability is determined by counting simulations with safety factors below unity. Conventional approaches identified in the literature often employ uniform profiles in successive rounds, overlooking the spatial distribution of parameters. Hence, this study introduces a case analysis where failure probability is quantified through MCM, integrating random fields in each iteration. For assessing variability, the PLAXIS software was utilized, employing classical limit equilibrium methods alongside the LAS technique (Local Average Subdivision). This facilitates a comparative analysis of probabilities derived from distinct equilibrium methodologies. The case study will focus on a slope within Brazilian territory, where a comprehensive geotechnical survey encompassing field and laboratory assessments has been conducted.

Submarine Mudflows: Insights from Depth-Averaged Numerical Simulation

2024-12-05T13:30:56+00:00

Submarine mudflows, frequently triggered by underwater landslides, lead to substantial debris accumulation stretching over kilometers once the landslide subsides, posing significant risks to vital infrastructure and the potential for triggering tsunamis. As these events are challenging to measure directly, simulation becomes imperative. Furthermore, these simulations must accurately depict the intricate dynamics of mudflow sliding processes, often modeled as viscoplastic fluids, and effectively captured by rheological models like Herschel-Bulkley and Bingham. The potential nonlinearity inherent in the Herschel-Bulkley model adds to the complexity of predicting final runout distances. The governing equations, comprised of a set of partial differential equations, further compound this challenge, making their solution difficult. In this paper, we delve into the numerical simulation of mudflows using the Depth-Averaged Method (DAM), a technique that streamlines the governing equations by integrating the momentum and continuity equations over the depth dimension. The mud descends down a slope with a fixed angle of declination. Employing both the Herschel-Bulkley and Bingham models within the DAM framework, we analyze the final runout distance and explore how various mud parameters - such as density, initial shape, and bed slope angle - affect the resulting deposit length. Using an explicit finite difference scheme to solve the governing equations, we first conducted a validation case to ensure the accuracy of our implementation, followed by a comprehensive comparison of runout distances across simulations, varying mud parameters.

Two-Dimensional Numerical Analysis of the Effects of Different Construction Methodologies on Tunnel Behavior

2024-12-05T13:33:58+00:00

Abstract: The growth of urban populations necessitates the construction of robust infrastructure, including highways, public transportation systems, sanitation networks, and housing. Consequently, underground space utilization becomes pivotal, prompting the construction of tunnels, access shafts, and galleries. However, such construction encounters challenges due to the unpredictable geotechnical and geological characteristics of the excavation site, especially when sensitive structures are nearby. This study examines the impact of various tunnel construction methodologies on earth mass behavior, with a particular focus on deformations, surface displacements, and forces exerted on linings. To this end, numerical simulations were conducted utilizing ABAQUS finite element software under plane strain conditions. These simulations were designed to simulate conditions akin to a tunnel project in Florianópolis. The numerical model encompasses four layers of soils and rocks, spanning approximately 70 meters in depth and 190 meters in width. The tunnels, with an excavated area of 161.29 m², are situated 20 meters below ground and are equipped with primary and secondary linings. The soils/rock and linings are modeled using Mohr-Coulomb and linear elastic failure criteria, respectively. The soil domain was modeled with CPE4 elements, while the linings domain employed CPE4I elements. The study initially examines the convergence and confinement curves to incorporate the three-dimensional effects of construction, considering the degree of mass relaxation during lining application. The construction sequences for single and twin tunnels entail full-section excavation, subsequent placement of the definitive crown and inverted arch, and side drift associated with half-section and inverted arch. The results discuss and highlight earth mass deformation patterns, critical areas during construction, surface displacement basins, and forces exerted on linings at various excavation phases. The effectiveness of various construction methodologies in reducing deformations and enhancing project safety is evaluated. The conclusions drawn from the numerical analyses offer valuable insights for tunnel project professionals, facilitating the development of more efficient and safer construction practices.

Utilization of Random Fields for Prediction of Displacements in Laterally Loaded Piles

2024-12-05T13:36:55+00:00

Soil is composed of materials that have organized over the ages, following the natural flow in the formation and development of the planet. Thus, we can infer that soil possesses characteristics of a random nature. Recent studies have been assisting geotechnical engineering in understanding this randomness, providing parameters for a more consistent mathematical representation of soil mass, aligned with probabilistic mathematics. Within this context, this work employs the theory of random variables coupled with the finite element method to estimate the behavior of laterally loaded piles. The study modeled the behavior of two piles using deterministic and stochastic methods, comparing the results with real load tests. These results showed good correspondence between predicted behavior and real tests.

A finite element model to predict axial forces with friction in tubing strings

2024-12-06T10:59:13+00:00

This work shows a one-dimensional finite element model to predict axial forces with friction in tubing strings subjected to operational loads in the production of oil and gas. These strings undergo different combinations of axial forces throughout their lifetime. Accurate prediction of these forces is essential to maintain the structural integrity of this fundamental component of the well barrier system. Frictional forces, which impact axial forces, occur due to the contact between the string and the casing, which happens when the tube buckles. In directional wells, the weight and trajectory of the tubing also generate frictional forces along the casing. Due to the variety of operational loads, a general solution to the friction problem requires a numerical approach. To achieve the proposed objective, the adopted modeling is verified through analytical solutions, investigating results regarding the axial forces and displacements experienced by the tubing in different operations. Mesh refinement studies and computational cost of the model are also discussed. Its observed a good concordance between numerical and analytical results, coupled with an acceptable computational cost. The main contribution of the work is the possibility of using numerical modeling for tubing, including friction, with good accuracy, low computational cost, and potential for real-time analysis.

A model for predicting temperature and pressure profiles in gas-lifted oil wells

2024-12-06T11:05:58+00:00

This work presents a methodology for predicting temperature and pressure profiles in oil wells that employ the artificial lift technique through gas-lift. When the reservoir pressure is not sufficient to bring the oil to the surface or when increasing production efficiency is desired, artificial lift techniques are employed. The injection of gas (gas-lift) is one of the most commonly used techniques. In the oil and gas industry, the accurate prediction of temperature profiles during various operations is crucial for ensuring well integrity. These profiles serve as inputs for calculating variations in annular pressures, casing stress, corrosion rates, and other critical parameters. However, calculating these profiles is challenging, requiring data on the well's underground structure, simultaneous resolution of the differential equations governing heat transfer phenomena in the structure, and modeling the hydrodynamic behavior of fluids. In wells where production operations are carried out using gas-lift, the complexity is even greater because the annular fluid, previously static, now circulates downward. This fact increases the number of equations to be solved and the number of fluids to be modeled. Thus, the development of strategies for obtaining these profiles is justified. To achieve the proposed objective, the methodology adopted in this work is based on three main steps: a) description of the mathematical formulation of the problem, considering the energy, momentum, and mass balance in the flow of both the produced fluid and the injected fluid; b) development of a numerical strategy enabling the simultaneous solution of the equations formulated in the previous step, thus allowing the determination of temperature and pressure profiles in the well; and c) verification of the strategy by comparing the results obtained using the procedure described in this work with thermal profiles from wells reported in the literature. The main contribution of this work is to enable the prediction of thermal profiles in oil wells in production operations with artificial lift by gas injection, allowing these profiles to be used in the design and monitoring of wells, thereby adding safety and efficiency to the operation.

A Numerical Investigation of Conductor Casing Installation Using Material Point Method

2024-12-06T11:11:26+00:00

The initial phases of well drilling projects involves the crucial step of installing conductor casing, which can be achieved through various methods, including conductor driving. This operation consists by three distinct stages: self-weight penetration, suction, and hammering. Given the often-challenging environmental conditions, conducting experimental analyses of drilling parameters becomes impractical. Consequently, numerical modeling emerges as a feasible and reliable alternative for process control. In this study, the open-source software ANURA 3D was adopted, which utilizes the Material Point Method (MPM) in its solutions. Therefore, this research aims to explore the impact of numerical parameters associated with computational modeling on problem solution. For this purpose, a two-dimensional axisymmetric computational model of self-weight penetration was employed. This model facilitated the necessary modifications to deeply understand the problem while optimizing computational cost. This approach enabled an understanding of how the analyzed parameters influence not only the displacement of the conductor casing but also the behavior of soil stresses.

Advancing Anomaly Detection in Oil Production Wells with TranAD: A Deep Transformer Network Approach

2024-12-06T11:16:47+00:00

The oil and gas industry is undergoing a profound transformation, leveraging cutting-edge technologies such as artificial intelligence, cloud computing, and the Internet of Things to optimize operational efficiency and safety. Within this context, ensuring the integrity of oil production wells is paramount for operational safety, environmental preservation, and minimizing production losses. Detecting unexpected events, namely anomalies such as spurious closures of Downhole Safety Valves (DHSV) and rapid productivity loss events, in well operations in a timely manner is crucial. The integration of sensor-based monitoring and computational modeling provides vital insights for identifying and mitigating such anomalies, thereby bolstering the industry's reliability and sustainability. However, the complexity of anomaly detection in oil production wells presents significant challenges. Firstly, historical data from producing oil wells tends to be highly unbalanced, with only occasional unexpected events occurring over the well's lifetime. Secondly, frequent valve change operations during the well's productive lifespan, while expected, can substantially alter pressure and temperature behavior, potentially confounding unsupervised techniques. To address these challenges, this paper proposes the evaluation of TranAD, a deep transformer network-based multivariate time-series anomaly detection model, applied on oil production wells data. TranAD utilizes attention-based sequence encoders to detect anomalies solely based on non-anomalous training data in the context of oil production wells. This study aims to assess the effectiveness of TranAD models in detecting anomalies using the 3W database, the first public repository released by Petrobras containing rare real-world undesirable events in oil wells. This dataset serves as a benchmark for the development of machine learning techniques tailored to the inherent complexities of real-world data. TranAD models trained on the 3W dataset will be compared with established benchmark techniques to validate their efficacy in this scenario. Drawing from previous case studies where TranAD demonstrated superior performance in detection and diagnosis across various domains, along with its data and time-efficient training, it is anticipated that TranAD will yield promising results in detecting anomalies in oil production wells.

Analysis of the transport of monoethylene glycol inside oil pipelines using numerical simulation and deep learning modeling

2024-12-06T11:21:35+00:00

One of the challenges faced by oil production systems is the formation of inorganic fouling, which is one of the problems of flow assurance. It is caused by the precipitation and deposition of substances such as barium and strontium sulphate, silicon sediments, calcium carbonate and sulphate, iron, and other insoluble solids, in a single phase or a combination of different minerals. Effective methodologies are being sought to mitigate or prevent the damage caused by this phenomenon, such as injecting inhibitors to prevent the nucleation and growth of fouling crystals. The solvent many of these inhibitors use is monoethylene glycol (C2H6O2), a liquid substance of low toxicity, miscible in polar solvents and relatively non-volatile. For this approach to be effective, it is necessary to understand the behavior of the product used inside the pipe since incorrect injection can accelerate and promote the recurrence of these formations. In order to understand the effectiveness of inhibiting this phenomenon, this paper investigates the behavior of the multiphase, multicomponent flow resulting from the injection of monoethylene glycol into a mixture of oil and formation water in an oil production system pipeline, using computational numerical simulation employing the Ansys Fluent commercial simulator, and applying deep learning models to calculate polynomials that describe the thermodynamic properties of the fluids that make up the flow. Using this methodology, we could predict the distribution of the mass fraction of monoethylene glycol in this system and verify the influence of different injection velocity profiles of this substance on the coefficient of variation of this fraction to predict the uniformity of the resulting mixture between the inhibitor solvent and the formation water. The results made it possible to verify the pipeline sections where there is total, partial, or no inhibition of the formation of inorganic fouling. This study is an essential tool for understanding efficient strategies for controlling and mitigating the occurrence of this flow assurance problem.
YUE, Hairong; ZHAO, Yujun, MA, Xinbin, GONG, Jinlong. Ethylene glycol: properties, synthesis, and applications. Chemical Society Reviews, [S. l.], v. 41, n. 11, p. 4089-4380, 7 jun. 2012. DOI 10.1039/c2cs15359a.

Application of YOLO V5 for front-end loader detection in collision risk zones with reclaimers within a coal yard

2024-12-06T11:29:16+00:00

In port operations, large machines known as reclaimers are used. Some of these machines are capable of reclaiming stored products at a nominal capacity of 8,000 tons per hour. While utilizing these colossal machines enhances productivity and reduces costs, their large dimensions have an unintended side effect: an increased risk of material and personal damage in the event of a collision.
To mitigate this risk, a solution was proposed: training a YOLO V5 neural network to detect and alert the presence of other equipment within the defined risk zone. The target object for detection in this work is the front-end loader (pá carregadeira), chosen due to its high exposure to collision risk.
For training the neural network, 3,195 images of various types of front-end loaders were collected, depicting different scenarios and positions. Additional background images were included. Annotations for bounding boxes were created using a tool provided by the website app.roboflow.com. The dataset was divided into 80% training images and 20% validation images12.
For training the network, 3,195 images of various types of front-end loaders were collected, depicting different scenarios and positions. Additional background images were included. Annotations for bounding boxes were created using a tool provided by the website app.roboflow.com. Only a single class was defined, and the dataset was divided into 80% training images and 20% validation images.
The training process was conducted in a staggered manner to optimize GPU consumption on Google Colab. Initially, a test was performed with 50 epochs, a batch size of 30 samples, and input images in the 640x640 pixel format. Subsequently, based on the weights from the first training, a second test was conducted by increasing the number of epochs to 100. Following the same logic, a new test was performed with the following parameters: a batch size of 60 and tests at 100 and 200 epochs.
Remarkably, even in the first training, promising results were achieved: Recall: 0.94; mAP@0.5: 0.97; mAP@0.95: 0.77; Precision: 0.97
The second training yielded even better results when compared to the first:
Overall recall: 0.94; mAP@0.5: 0.97; mAP@0.5:0.95: 0.78414; Precision: 0.99
Upon analyzing some machine images, the confidence of the markings increased to approximately 90% certainty. In conclusion, the work thus far has demonstrated satisfactory and promising results, justifying the continuation of further studies and simulations

Automated Approach for Modeling APB in Oil Wells

2024-12-06T11:33:50+00:00

This paper presents an automated approach for modeling APB (Annular Pressure Build-up) in vertical oil wells. The APB phenomenon is characterized by an increase in pressure in the annular spaces of wells due to the variation in temperature of confined fluids, resulting in significant loading differentials on the casings. Therefore, to ensure the wells structural integrity, it is essential to consider the effects of APB in the design of equipment and casings. However, the calculation of pressure buildup is complex and lacks a closed (or analytical) solution, requiring the use of computational tools. In the literature, some successful works can be identified that model the APB phenomenon in finite element-based software, such as ABAQUS, for example. However, creating models through the graphical interface is a slow and limited process. To achieve the proposed objective, a work methodology is developed based on the following steps: a) development of a strategy for modeling APB in ABAQUS; b) creation of Python scripts to automate all tasks (pre-processing and solving) of the developed strategy; and c) validation of the proposed strategy through scenarios with results available in the literature. In the developed approach, all scenario data is described in a JSON structured file. To model the APB, the main Python file is executed, and thus, the entire developed strategy is automatically executed in ABAQUS. Finally, the ABAQUS graphical interface is opened, displaying all results. All annular fluid modeling is performed using ABAQUS's own fluid cavity interaction. Compared to another approach available in the literature, the developed strategy shows relative errors of up to 10% in predicting APB. This discrepancy can be justified by the simplifications in calculations adopted by the reference work and by considering the Fluid Cavity at a constant temperature throughout the annulus, as done in this study. Despite the differences found this study contributes by providing an additional tool to assist studies related to the APB phenomenon and in predicting its corresponding effects on casings. Furthermore, the proposed automation adds speed to modeling and prevents errors in scenario construction or strategy reproduction.

Comprehensive reliability-based well integrity analysis: application to worst case discharge (WCD) scenario

2024-12-06T11:39:38+00:00

The global increase in energy demand, combined with the availability of hydrocarbons, positions oil and gas among the main non-renewable sources in the world's energy matrix. In the scope of well design, ensuring their structural integrity under increasingly severe conditions, especially in deep and ultra-deep water, has become a critical factor for the oil and gas industry. Consequently, there has been an investment in modeling extreme environmental scenarios found in challenging wells to ensure their integrity throughout their lifecycle. This work proposes a new methodology for probabilistic analysis of structural integrity during the construction and operation phases of wells, taking into account the uncertainties associated with variables related to the behavior of tubulars, cement sheath, formation, and applied loads . It aims to analyze well integrity through safety barrier failure events in a scenario of severe blowout known as Worst Case Discharge (WCD), using structural reliability theory. The calculation of failure probability will be carried out using the First Order Reliability Method (FORM) and Monte Carlo simulation. It is understood that the proposed methodology can be applied in the design and monitoring stages of wells, contributing to decision-making process.

Computational Modeling of Torpedo Base Penetration at Seabed Using Piezocone Tests

2024-12-06T11:43:42+00:00

This study presents a comprehensive investigation into the dynamics of torpedo anchor penetration at the seabed, leveraging real marine soil data obtained from Piezocone Tests (CPTu tests) provided by a prominent Brazilian oil and gas company. Recognizing the significance of accurate soil characterization, particularly in marine environments, the research meticulously characterizes undrained shear strength in a piecewise manner, thus addressing a key limitation of existing methods. By overcoming the one-layered soil constraint inherent in True's method, the study offers a more comprehensive understanding of torpedo anchor behavior across diverse soil stratifications. The utilization of CPTu tests provides several advantages, including real-time data acquisition, continuous profiling, and minimal soil disturbance, enabling precise modeling of torpedo anchor penetration. This approach not only enhances the accuracy of anchor penetration depth predictions but also contributes to a more robust analysis of seabed stability and anchor performance. To further refine the computational methodology, the study integrates the fourth-order Runge-Kutta technique, enhancing the precision of numerical simulations and facilitating more reliable predictions of anchor behavior. In addition to analyzing anchor penetration depths, the study comprehensively examines the balance of forces during the penetration phase, shedding light on the dynamic interplay between various factors influencing anchor embedment. Detailed torpedo base velocity profiles, analyzed depth-wise, provide valuable insights into the velocity distribution and its implications for seabed interactions. Furthermore, comparative analyses between controlled velocity deployment and free-fall installation scenarios offer practical insights into optimizing anchor performance and enhancing seabed stability in offshore engineering applications. By integrating real marine soil data with advanced numerical techniques and comprehensive analyses, this research significantly advances our understanding of torpedo anchor dynamics. The insights gleaned from this study have profound implications for the design and implementation of seabed installations, informing more efficient and reliable practices in offshore engineering.

Deep Learning-Based Reservoir Simulation Proxy Models

2024-12-06T11:48:20+00:00

The behavior of oil reservoirs, characterized by geophysical, geochemical, and geological properties, can be understood through the simulation of computational models, involving the construction of meshes of finite volume elements with equations derived from fundamental principles. However, the execution of multiple simulations for activities such as optimization and uncertainty assessment results in substantial computational costs.
To overcome this challenge, proxy models are proposed, aiming to replace reservoir simulators with adequate precision. This work proposes the implementation of data-based proxies for reservoir simulators using Artificial Neural Networks (ANNs). This approach utilizes time series of well controls as inputs, generating responses for Bottom Hole Pressures (BHPs) and/or flow rates.
In recent years, proxy models based on neural networks have been applied to obtain predictions of flows and/or pressures in reservoirs. For example, Recurrent Neural Networks (RNNs), specialized in handling sequential data, were used by [1] to predict water flows in the Xiluodu hydroelectric reservoir in China. Convolutional Neural Networks (CNNs), specialized in pattern recognition in images and videos, were also employed by [2] to predict pressures and flow rates of injector and producer wells, respectively.
In the scope of this study, distinct neural network architectures were evaluated to predict outputs of a synthetic two-phase model with partial faults. Given the adoption of mixed controls, where producer wells are controlled by BHP and injector wells by flow rate, the use of Multihead Neural Networks [3] was also investigated. This approach allows differentiated processing of input data, contributing to more robust and efficient learning.
For each considered architecture, the impact of the number of timesteps in the samples and their size on the accuracy of predictions was analyzed. The results indicate that parallel hybrid architectures exhibit the best performance, forming a complementary mutual network where each architecture contributes with different learning approaches. Additionally, a higher number of samples contributes to reducing result dispersion, while an increase in the number of timesteps does not show a significant contribution to reducing mean error.
We gratefully acknowledge the support provided by PETROBRAS, ANP, FINEP, PRH, EMBRAPII, FACEPE, CNPq, and CAPES, which has been instrumental in the successful execution of this work.

Detection of unexpected events in oil wells using deep learning with Autoencoders and Local Outlier Factor

2024-12-06T11:53:57+00:00

In the oil and gas industry, anomaly investigation is of great interest, as careful data analysis plays a fundamental role in preventing production losses, environmental accidents, and workforce reduction, while reducing maintenance costs. To achieve these goals, a variety of computational techniques has been applied, primarily to enhance operational safety. These techniques involve the use of data from pressure sensors, temperature sensors, and control valves installed both in wells and on production platforms connected to these wells. This work investigates unsupervised machine learning models using density-based architectures such as Local Outlier Factor (LOF), combined with autoencoders to detect unexpected events in sensors of production/injection subsea wells. The first approach leverages data from operational wells, examining pressure and temperature sensors throughout the well structure, and applies them to autoencoders for data preprocessing, thereby reducing its dimensionality and capturing important characteristics. Subsequently, these processed data are fed as input to the LOF-based architecture analyzed in this work. In the second approach, the data is inserted directly to the analyzed machine learning model, avoiding any kind of dimensionality reduction with autoencoders, followed by comparisons with previous works on anomaly detection of wells. The experiments were conducted in real cases of wells that experienced operational failures, focusing on the anomalies identified by Vargas et al. (2019) and recorded in the 3W public database. Previous studies in the literature have highlighted that the LOF algorithm has shown satisfactory performance in identifying anomalies in production wells with gas lift and in spurious closures of DHSV (Downhole Safety Valve), when compared to other approaches, even outperforming recurrent neural networks, as observed by Nascimento et al. (2020) and Aranha et al. (2023), respectively. Therefore, it is expected that LOF will also demonstrate good performance results in detecting other instances present in the database. Furthermore, its integration with autoencoders for data dimensionality reduction is anticipated as a complementary strategy to enhance the results.

Effect of Soil-Conductor Gap Formation on the Fatigue of Subsea Wellheads

2024-12-06T11:58:38+00:00

The construction of offshore oil wells in deepwater typically involve the use of floating rigs. These rigs transmit their motion through the drilling riser to the wellhead and casings, which can result in fatigue damage. In our research, we verified a hypothesis suggesting that high loads (e.g., a storm or a rig drift-off) can cause plastic deformation in the soil, causing the opening of a gap between the conductor and soil. This would result in change of the dynamic behavior of system, and consequently on the cumulative damage. We modelled numerically the problem using Finite Element Method. Wave and current loads were simulated stochastically. Soil was implemented as nonlinear springs that obey a bounding surface plasticity model. The results compare displacements, bending moments and fatigue damage across several scenarios, as well as the likelihood of VIV onset.

Geological storage of CO2 in depleted reservoirs with lithological modeling and analysis of technical viability

2024-12-06T12:01:35+00:00

The objective of the work is to understand the key variables that dictate the complexity and viability of the implementation of carbon capture and storage (CCS). This involves examining the mathematical relationship between the storage capacity available in a reservoir and the various costs associated with injection implementation together with technical challenges such as, for example, lack of porosity or not proper lithology Initially considering factors such as the distance from the reservoir to gas pipelines and facilities survey around them In other words: Will make it able to conclude which fields have a higher viability for CCS project installation.
This research began with the survey of geological and production data from all fields that have been in production for over 30 years [1,2], totaling 104 production fields. Then were calculated the feasibility value by multiplying the fractions of oil and gas produced by the OOIP and OGIP, summing them, and then dividing by the distance in meters from the pipelines. These fields were then narrowed down to the 10 most viable fields in each basin according to these feasibility value. On another front of the study, the fields, and pipelines in the two basins were georeferenced using the QGIS software [3] and organized within it with bubble charts depicting their workable value. It was concluded that the most viable fields, respectively, are Guamaré (with almost double the viability of the second-ranked), Fazenda Junco, and Porto Carão. All fields in the Recôncavo Basin proved to be significantly more feasible for the storage technique than those in the Potiguar Basin. This is mainly due to the estimated 'storage space' determined through OOIP (Original Oil in Place) [4]. That was bigger in Recôncavo Basin.
Then, were made lithological descriptions, and properties of previously produced methane from wells in the Guamaré field will be gathered. The goal is to estimate a comprehensive geological model of the fields and reservoir through statistical interpolation. This process will involve compilation, geotransformation, spatial location, and 3D geometry generation using Python scripts [5] in order to integrate with tnavigator simulator and the reservoir shape made with Python/VTK in 3D using spatial location of the wells. This stage is crucial to predict and contributes to a better understanding of the storage quality in terms of time and quantity of CO2 stored. This, in turn, leads to a more reliable conclusion regarding the feasibility of CCS in these two fields.

Integrated Computer-Aided Design for Well Cementing: Analyzing Containment in Deepwater Wells

2024-12-06T12:05:43+00:00

Objective: This study investigates the impact of numerical simulations on cement integrity during the drilling of deepwater top holes through salt formations. The primary aim is to enhance well containment analysis by optimizing cement sheath quality.
Approach: We begin with a comprehensive literature review, examining industry practices for drilling and cementing in salt zones. By analyzing existing literature, we gain insights into best practices and challenges related to cementing in deepwater wells. Next, we leverage field data from hundreds of wells in the Santos basin pre-salt region. This data allows us to identify critical aspects affecting cement quality and determine the main variables necessary for consideration. The heart of our approach lies in real-scale numerical simulations using chemo-thermo-mechanical finite-element models. These simulations guide our design process, considering factors such as well geometry (inclination, tortuosity, and hole enlargement) and different cement slurry properties. Importantly, the simulations also account for severe thermal and mechanical stress during worst-case scenarios of discharge and shut in. By ensuring effective well-control containment, we assure that the casing cement will not fail in the event of a blowout.
Key Findings: For geometry requirements, meeting specific well geometry criteria is essential for achieving the desired cement sheath quality. As for cement slurry design, simulations indicate that salt-based cement slurry is favored due to its superior bond strength and field performance. We also evaluate the impact of cement expansion and shrinkage for different scenarios, showing the enhanced performance of expansive cement in long-term integrity.
Industry Impact: Integrating simulations into standard cementing practices offers significant advancements in maintaining deepwater well integrity. By optimizing cement sheath quality, we enhance well containment and contribute to safer drilling operations in challenging environments.

Local Models for Oil Well Casing Subject to Subsidence Deformations

2024-12-06T12:10:33+00:00

When oil and gas wells become depleted and reservoir pressures decreases, the porous formation contracts due to poromechanics effects, causing significant stress redistribution and global deformation of the rock mass. In severe cases, there may be significant displacement of the surface (or ocean bottom), termed subsidence. Both surface and underground displacements are transmitted to well barrier elements, including wellheads, casing and cementing, potentially leading to hydrocarbon leaks. However, coupling geomechanical models of subsidence with well structures presents significant modeling and simulation challenges. Axisymmetric modeling of vertical wells subject to transversely isotropic subsidence strains is relatively straightforward and extensible to slightly deviated wells, but any other cenario requires costly and challenging tridimensional modeling. Therefore, although subsidence is a global problem, it is important to develop local coupling models. In this work, we present the axisymmetric modeling approach and discuss the challenges associated with applying boundary conditions for the general case of a deviated well in a fully triaxial strain state. Using a contracting material model for the rock, we were able to observe pipe loads such as axial and shear forces, as well as ovalization and external pressure, in the cemented casing. This opens a path toward 1D modeling of casing pipe, which is the traditional well casing design approach.

Local remesh procedure to model reaming in vertical oil wells drilled through salt rocks

2024-12-06T12:12:49+00:00

This paper presents an alternative methodology, based on cutting and adjusting finite elements, to model reaming of salt rocks during vertical wells drilling. The developed strategy ensures that the stress, deformation, and displacement fields are maintained after the remesh. To reach the pre-salt hydrocarbon reservoirs it is necessary to pass through thick layers of salt rocks. The mobility of these salt rocks can cause serious operational problems, such as the imprisonment of the drill string, casing collapse and annular entrapment of columns, compromising the casing integrity. Therefore, adequate monitoring of the well diameter must be done constantly throughout the entire drilling process. Thus, reaming procedures may be required to recondition the diameter of the well to its original state. The reaming strategy presented in this work is based on removing and adjusting mesh elements reestablishing the initial radius of the well in specific regions. This procedure improves the precision and realism of the simulations, avoiding the appearance of a gap between the mesh and drill bit passage. Stress graphs along the wellbore and comparisons with real wells data are used to enhance the phenomena understanding and validate the proposed methodology

Numerical modeling of rupture disk as a method of controlling pressure in oil well annulus

2024-12-06T12:20:15+00:00

The work objective is to present a methodology for computational modeling for pressure control in confined annulus of oil wells using rupture disks. Throughout the oil wellbore cycle life, different operations cause variations in its temperature, causing pressure increases in its annular spaces, a phenomenon called APB (Annular Pressure Build-Up). In some cases, the difference between internal and external pressures on the casing or production columns can result in the loss of their respective integrity caused by burst failure or collapse. When using a rupture disk, once the pressure difference over the column is greater than the disk collapse pressure, there is a hydraulic communication between the annulus, balancing the volume and pressure between them. This pressure balance significantly increases the safety factors of the coatings, whether for burst failure or collapse. The methodology adopted to achieve the objective of this work consists of five macro steps: i) bibliographical review on the use of rupture discs in the context of APB, identifying their functioning and advantages; ii) definition and numerical implementation of pressure balance models following those available in the literature; iii) simulation of a reference scenario to verify pressure balance models; iv) simulations of variations in the rupture disc positioning in the reference scenario and calculation of the casing safety factors (burst and collapse); and v) final evaluation of the disk's ability to control annular pressures and protect the casings. The results indicate that the proposed methodology presents good results compared to the state-of-the-art. Additionally, possible modeling adjustments can allow a closer approximation to reality in the field. The main work contribution is to advance studies on pressure control methods in annular using a methodology proposed in the literature. In addition, to developing a computational tool that reproduces this methodology.

On the accuracy of prediction models for the collapse strength of worn casing

2024-12-06T12:57:03+00:00

Oil and gas wells are typically built in highly complex and harsh environments. Casing is a crucial part of the well structure, undergoing a wide range of loads during the well life cycle, such as internal and external pressures, and axial force. After installation, these tubulars may develop wear grooves on their inner wall, caused by contact with the tool joints of the drill string. This reduction in wall thickness, combined with initial geometric imperfections, such as ovality and eccentricity, as well as residual stresses, may cause a significant reduction in tubular resistance, especially under external pressure (collapse). Thus, models that can estimate accurate collapse pressure, validated with realistic data, are extremely relevant. In this context, some collapse prediction models of worn casing are proposed in the literature, based on experimental, analytical, or numerical approaches. However, in several cases, the data used in deriving the models are limited in quantity and variety of cases. The present study aims to investigate and propose improvements in the equations for the collapse pressure of worn casing by using a large database of numerical simulations. Several Finite Element (FE) simulations are performed to generate a large database of collapsed pipes. Then, the accuracy of collapse prediction models from the literature is evaluated, while calibrating new model parameters to enhance precision. The study is carried out adopting material and geometric configurations that are commonly observed in worn casing tubulars of oil and gas wells. Two subsets of the large databases were generated: one is used for fitting the models and the other for testing them. The exploratory analysis of the FE database provides insights into the collapse strength deration in relation to relevant parameters, such as damage depth, tool joint radius and tube slenderness. The results compare the accuracy of the models, and a discussion about features influence is carried out in parallel.

On the generation of submarine landslide models for Material Point Method simulations through bathymetric data

2024-12-06T13:03:16+00:00

Submarine landslides are natural phenomena that can cause economic problems and environmental disasters, as the force of the sliding mass can break pipes, interrupting production and destroying whole ecosystems. By simulating these landslides using bathymetric data, one can optimize the design and construction of subsea equipment to minimize its risks. This work aims to create a wizard that, using bathymetric data, guides the engineer through the process of creation of the simulation input for the submarine landslide study. The simulator used was developed in-house and uses the material point method to solve continuum mechanics momentum conservation equations for a vast library of constitutive models. The wizard objective is to streamline numerical parameters by automating and optimizing model choices inherent to the computational method, allowing the engineer to focus on the physical problem rather than the numerical details. Furthermore, it will be possible to configure a vast range of physical parameters, such as the definition of the sliding mass, the constitutive model and its parameters.

On the probabilistic assessment of casing applied to top hole design by FORM

2024-12-06T13:08:01+00:00

This study employed reliability-based models to optimize the design of top-hole casing sections considering the uncertainties associated with soil behavior and casing manufacturing. The integrity of oil and gas wells significantly depends on the casing system throughout its life cycle, ensuring tightness, stability, and load support. Various load scenarios were analyzed to estimate the probability of occurrence of different soil-casing system failure modes. Analyses for various types of top-hole designs are included in this work. Reliability-based techniques have emerged as interesting tools for structural analyses and design. This research leverages soil characterization data from piezocone tests (CPTu) to statistically define the mechanical parameters crucial for conductor and surface casing design. Additionally, random variables linked to the material and geometrical properties of tubulars are incorporated, drawing from the casing manufacturing data outlined in API/TR 5C3 (2018). Probabilistic models are developed using the first-order reliability method (FORM), an efficient optimization-based procedure, and applied across multiple load scenarios to gauge the failure probability in the top-hole casing design. The analysis primarily focuses on the variability associated with undrained soil strength derived from CPTu data, which is deemed the most influential random variable owing to its spatial heterogeneity. The results underscore the viability and importance of estimating the probability of relevant failure modes aligned with internal regulations concerning the conductor casing load capacity, surface casing triaxial stress, and wellhead displacement. The work in progress considers random variables obtained from correlated soil test data and related to casing manufacturing (outer diameter, wall thickness, and yield strength) in a combined probability density function applied to the failure functions. The findings reveal that the conductor casing capacity is the critical failure mode, which is consistent with deterministic design practices. Moreover, the analysis highlighted that the outer diameter insignificantly influences the probabilistic response owing to its low dispersion. This novel approach combines soil statistics information and casing manufacturing data within a reliability-based framework, achieving a balance between cost and safety while aiding decision-making in top-hole design.

Predictive Characterization of Fracture and Absorption Tests in Halite Formations: an integrated approach of numerical modeling and field data

2024-12-06T13:13:41+00:00

This study introduces a predictive model based on field data from oil wells in the pre-salt region, focusing on the analysis of fractures in saline rocks and the simulation of leak-off tests through integration with the finite element method. The analysis utilized a variety of techniques, including the construction of a correlation matrix, statistical testing, linear adjustment methods, and numerical modeling. Utilizing specific field data from halite formations, the study identified overburden stress and sediment depth as the most critical variables for minimum stress. Three linear adjustment methodsleast squares, genetic algorithms, and Bayesian methodswere employed. All methods demonstrated a strong correlation among the variables, with Bayesian methods exhibiting the lowest percentage error relative to experimental data. Residual analysis showed that the regression models provided accurate predictions, with most points closely matching the actual values. Numerical modeling further allowed for the assessment of rock behavior under different fluid conditions, indicating that the compositional fluid provides a more realistic simulation and adheres more closely to theoretical expectations and field data. The results affirm the efficacy of the proposed models, particularly highlighting the use of Bayesian methods and mathematical modeling integrated with the finite element method, in predicting the dynamics of fractures and fluid absorption in saline formations. This model significantly enhances the characterization of fractures and absorption pressures in oil wells, improving its utility in predicting behaviors in formations associated with pre-salt fields.

Sensitivity analysis of thermal phenomena in APB (Annular Pressure Buildup) in oil wells

2024-12-06T13:18:57+00:00

This paper presents a sensitivity analysis aimed at understanding how certain parameters of the thermal problem affect the increase in Annular Pressure Buildup (APB) in oil wells. The structure of an oil well experiences high-temperature gradients throughout its lifespan, directly affecting its components such as casings, cement, and rock formation. Among the undesirable effects caused by temperature variation, APB stands out, related to the expansion of fluids confined between casings, being a severe phenomenon that can lead to well collapse. This justifies studies aimed at better understanding temperature distributions and, consequently, the increase in pressure in the annular spaces of oil wells. On the other hand, changes in fluid and component temperatures during well operation depend on many factors, such as operating flow rate, inlet pressure and temperature, operating time, formation type, and properties of the produced/injected fluid. Some of these parameters are chosen for inclusion in the parametric analysis proposed in this work. To achieve the proposed objective, the methodology adopted in this work is based on four steps: a) selection of a reference well used for the analyses; b) definition of the variables to be studied and their assumed values; c) generation and simulation of scenarios formed by the combination of chosen variables; and d) selection and description of the sensitivity analysis method to be employed. The main contribution of this work is to present a sensitivity analysis of certain well parameters in annular pressure buildup, allowing inference about the importance of some isolated properties in the thermomechanical response. Additionally, the methodology presented can be applied to other parameters and thus improve understanding of how each property influences well APB.

Simulation of continuous gas-lift technique in oil-gas systems using OpenFOAM and the Volume of Fluid method

2024-12-06T13:23:19+00:00

In order to maintain optimal production rates in oil reservoirs, artificial lift methods are employed as reservoir pressure declines over time due to oil extraction. The gas lift technique is one of such methods where a compressed gas, usually a mixture of hydrocarbons with low molecular weight, is injected into the lower section of the pipeline through valves. The expected result is that the additional energy provided will propel the oil to the surface and the mixture of gas and oil will have a lower effective density, thus making it easier to be transported to the surface. This artificial lift method, when applied to restore productivity is not limited by the well depth and can be applied to offshore facilities and allows operation regimes in both continuous or intermittent lift. While computational fluid dynamics (CFD) simulations for gas lift problems commonly use commercial softwares, we propose CFD simulations using the free toolbox OpenFOAM-10 using the Volume of Fluid (VOF) method. This approach aims to simulate a gas lift scenario where a methane-like gas is injected horizontally into a pipe containing upward-flowing oil, replicating real-world oil industry conditions. The main goal is to investigate the gas lift process, analyzing how the gas propels oil and increases oil production compared to scenarios without gas lift. We focus on the continuous gas lift injection regime and compare VOF simulation results with those obtained from the Smoothed Particle Hydrodynamics (SPH) method for the same problem.

Streamlined workflow for the simulation of submarine landslides with the material point method

2024-12-06T13:26:30+00:00

Industry demand for numerical simulations is growing every year due to the advances in computer hardware that make increasingly complex and detailed simulations possible. Numerical tools are particularly useful for situations in which the available analytical and experimental tools are limited or unavailable. For that reason, they are a powerful tool for the analysis of natural phenomena, such as submarine landslides. Submarine landslides are commonly accompanied by large deformations and large displacements, which makes them challenging for traditional numerical tools, such as the finite element method. Thus, a numerical tool which is equipped to handle this behavior is necessary. In this paper, we describe a streamlined workflow to simulate submarine landslides that encompass problem modeling, simulation and post-processing. The simulator, developed in-house, uses the Generalized Interpolation Material Point (GIMP) to solve momentum conservation equations and is able to handle large deformations, contact and physical nonlinearities. The proposed workflow acts as a wizard that creates templates for multiple problem definition strategies, automates simulation execution, and provides a range of postprocessing variables to better describe the results. Furthermore, practical examples are presented, detailing the process of mesh and particle definition, simulation execution and analysis of run out distances, deposition height and impact pressure assessment.

Nonlinear metabeam for vibration absorption and energy harvesting

2024-12-12T14:01:27+00:00

Metamaterials are engineered materials that surpass conventional ones with their exceptional performance. These systems exhibit diverse properties, including excellent energy absorption, acoustic insulation, cloaking, negative Poisson's ratio, and more. In addition, they can possess the remarkable ability to serve multiple functions simultaneously, thereby achieving more than one objective. This study delves into the creation of a beam based on metamaterial engineered to attenuate vibrations while harvesting this kinetic energy for electricity generation. The system works by preventing elastic wave propagation along its length and focusing the incident wave into piezoelectric generators, responsible for the energy conversion. Consequently, we can use this energy to power microelectronic devices such as sensors and actuators. The proposed metabeam consists of a cantilever beam with nonlinear resonators equipped with piezoelectric layers. This arrangement establishes a wide local resonance bandgap on the frequency spectrum of the host beam forbidden the elastic wave propagation. The incident wave is transmitted to the resonators, where they convert kinetic energy into electricity. Nonlinearity is strategically introduced into the resonator to broaden the operational bandwidth. Mathematical modeling is developed, and numerical simulations are conducted to study and demonstrate the performance of the proposed system.

Wave and vibration attenuation analyzes of 2-D phononic crystals using the scaled boundary finite element method

2024-12-12T14:32:40+00:00

This study uses the scaled boundary finite element method (SBFEM) to study the wave propagation and vibration in a 2-D phononic crystal (PnC). The SBFEM is a general semi-analytical method where a problem domain is divided into subdomains satisfying the scaling requirement. It offers the advantages of the finite element method (FEM) and the boundary element method (BEM), avoiding some drawbacks and making it very attractive for PnC applications. In this investigation, the SBFEM is formulated using the Bloch-Floquet theory to model the periodic 2-D PnC unit cells. The 2-D PnC is composed by square inclusions distributed in a matrix with square lattice. The SBFEM results are computed in the form of dispersion diagram and forced response of the 2-D PnC. The dispersion diagram obtained by the SBFEM is validated with those obtained by the FEM and plane wave expansion (PWE) method. The unit cell wave attenuation (i.e., the imaginary part of wave number multiplied by the unit cell length) is also computed by using the extended plane wave expansion (EPWE) approach.

Exploring Herschel-Quincke Ducts for Enhanced Sound Attenuation: An Investigation into Acoustic Metamaterial Systems

2024-12-12T14:37:35+00:00

This present study evaluates the effectiveness of a periodic acoustic metamaterial system comprised of Herschel-Quincke (H-Q) ducts for noise control. The methodology employed is based on a transfer matrix (TM) approach. The results regarding sound transmission loss are validated through finite element simulations carried out in the COMSOL Multiphysics software. Furthermore, the Floquet-Bloch theory is utilized to identify bandgaps in infinite periodic silencers, highlighting the frequency ranges where sound waves are significantly attenuated. Additionally, several Herschel-Quincke tube models are proposed, incorporating variations in the number and shape of H-Q tubes. This results in the definition of structural parameters that exhibit substantial improvements in their sound attenuation capabilities, particularly in expanding the frequency range where attenuation occurs.

2Frame: Web Software for Application in Non-Linear Geometric Analysis of 2-Dimensional Frames

2024-12-11T18:13:47+00:00

This work presents the development of a web software tool for the linear and nonlinear geometric structural analysis of plane frames. The software leverages matrix methods, specifically the Direct Stiffness Method, and incorporates the Two Circle Iterative Method to account for geometric nonlinearity, alongside principles from solid mechanics. The user-friendly interface allows for easy modeling of frames and input of material parameters, facilitating the determination of stiffness matrices and internal forces. The accuracy and reliability of the software are demonstrated through comparative analysis with data obtained from solved examples in existing literature. Results indicate close agreement, validating the efficacy of the developed tool for nonlinear geometric structural analysis of plane frames. This software stands as a valuable resource for education, research, and professional practice in the field of structural engineering, targeting both undergraduate and graduate students as well as structural professionals in need of nonlinear analysis.

An educational computational program for nonlinear geometric analysis of truss structures using the Finite Element Method based on Positions

2024-12-12T11:19:25+00:00

This study describes an educational computational program for the analysis of truss structures using the Finite Element Method based on Positions (FEMP). FEMP adopts the nodal positions of discretized elements as degrees of freedom, in contrast to the displacements used in conventional Finite Element Method (FEM). This approach enables FEMP to straightforwardly and naturally incorporate geometric nonlinearity into its positional formulation, simplifying the nonlinear geometric analysis of structures. The developed educational program provides a range of functionalities, allowing users to conduct both static and dynamic analyses of truss structures.

Development of an educational software for the assessment of natural slope stability

2024-12-12T11:28:50+00:00

The analysis of natural slope stability is critical for reducing or mitigating potential catastrophic risks associated with landslides. This kind of disaster not only generates substantial economic and material losses but also creates significant threats to human safety. Landslides occur when forces acting down-slope exceed the soil strength of slopes. In particular, critical factors such as the slope gradient and the thickness of the soil layer can increase such forces, making a slope prone to sliding. Another cause for landslides is rainfall because it can increase the forces acting in the slope (such as the soil weight) or reduce the soil strength (such as the soil cohesion and friction angle), in particular under unsaturated conditions. The deterministic approaches based on numerical or limit equilibrium methods are used to check slope stability through the computation of the Factor of Safety (FOS). However, the impact of the slope geometric features, soil properties or rainfall cannot be assessed unless sensitivity studies are carried out, making difficult the learning process of slope stability. Therefore, in this study, we introduce an educational software for the quick assessment of FOS in natural slopes. The application allows the analyses of FOS considering input data such as 3D declivity maps, soil thickness, soil properties and rainfall intensity. The application boasts user-friendly navigation and delivers real-time results, enabling sensitivity analyses of the safety factor concerning parameters, alongside risk appraisal and prognostication of local condition changes following rainfall episodes.

Educational interactive graphics tool for teaching Mohr Circle

2024-12-12T11:35:25+00:00

Mohr Circle is a two-dimensional graphical representation of the transformation law for the Cauchy stress tensor. The components of the Cauchy stress tensor at a specific material point are known with respect to a coordinate system. Mohr Circle graphically determines the stress components acting in a rotated coordinate system, i.e., acting on a differently oriented plane passing through that point. The e-Mohr program is an interactive graphics tool that explains the Mohr Circle to Solid Mechanics (Strength of Materials) students in engineering courses. The program demonstrates how the Mohr Circle works for plane stress states, allowing users to interactively manipulate the plane's orientation where the stress tensor components are calculated. Furthermore, e-Mohr involves determining a point in the Mohr Circle called the pole or origin of the planes. Any straight line drawn from the pole will intersect the Mohr Circle at a point representing the state of stress on an inclined plane in the same orientation (parallel) in space as that line.

Educational interactive graphics tool for teaching the Cross process

2024-12-12T11:38:18+00:00

The program demonstrates to students in the Structural Analysis discipline of the Civil Engineering course how the Cross Process (Moment Distribution Method) works for continuous beams, visually showing the physical interpretation of the method associated with the calculations in the same way as they are done in calculation memory. In addition to the calculations, the program shows the structural model with the loads (uniformly distributed forces across each span), its deformation, and its bending moment diagram. The program, with open source code, was implemented in the Java language, based on the Object Oriented Programming paradigm OOP.
The program for calculating continuous beams using the Cross Process has four canvases. It is on these canvases that the structural models, their diagrams, and their results will be drawn. The user can interact using the mouse to model the continuous beam, create new internal supports, remove internal supports, modify the dimensions of the spans, or modify the load values. The student can track the results by following the incremental analysis of the method step by step. Furthermore, the student can interfere in the iterative solution process by forcing the bending moment balance of any internal node in any order. All these procedures help the student to understand the analysis process. Well-documented source code is also an essential component for learning the method.

Expansion of an Object-Oriented Framework to Consider Reddy Model for Reticulated Structures

2024-12-12T11:45:01+00:00

Classical softwares to perform structural analysis using the Finite Element Method (FEM) considers the Euler-Bernoulli and Timoshenko beams theories. However, these theories may not provide stress results with sufficient accuracy. Therefore, this study presents the expansion of an open-source object-oriented framework for structural analysis of frame structural models considering the Reddy beam model. Also, is presented a 3D Reddy formulation to perform linear and nonlinear geometric analysis. The computational implementation evidence the importance of use object-oriented frameworks, and open-source codes. The developed examples clearly shows the improvements in the shear stress prediction when considering higher order beams formulations in a frame element, and clarify for graduate and undergraduate students the diferences between the most usual beams formulations.

Geometric Nonlinear Analysis using the Two-cycle Method in Ftool

2024-12-12T11:52:04+00:00

With recent advances in design and material technology, increasingly slender structures are being conceived, which makes nonlinear analysis an important task for efficient and safe projects. Geometrically nonlinear problems are usually solved using the Finite Element Method (FEM) along with iterative numerical schemes, in which the structure response is directly influenced by the level of discretization and the nonlinear solution algorithm used. Thus, nonlinear analysis demands some experience from the analyst in terms of the parameters involved in the solution algorithms and structural behavior in general. To reduce the discretization dependence, exact solutions based on the deformed infinitesimal element equilibrium can be used as interpolation functions. To circumvent the difficulties in dealing with parameters related to the numerical methods, the two-cycle method can be used, since it is not dependent on load or displacement steps. The structural analysis software Ftool, widely used by Civil Engineers and students was adapted to perform two-cycle analyses employing frame elements based on solutions of the differential equations obtained from the deformed configuration. The results in terms of displacements and rotations for the examples studied are identical to the analytical solutions, showing that the combination of the two-cycle method with the exact element formulation is promising and can diminish the need for discretization and the use of complicated nonlinear solution algorithms.

Geometrically nonlinear truss analysis using Python's optimization libraries

2024-12-12T11:58:16+00:00

This paper presents an efficient computational framework for analyzing trusses subject to geometric nonlinearities using Python common libraries for numerical optimization. Beginning with a brief discussion on truss kinematics and linear material behavior, we proceed to describe the deformed configuration of the truss and its internal energy based on nodal displacements. We then evaluate some numerical optimization libraries available to select the most suitable method for our problem, thus avoiding the explicit derivation of equilibrium equations and tangent matrices. The equilibrium of the truss is defined as the configuration with minimal potential energy and this is taken as the objective function of the optimization algorithm. Finally, we conclude with numerical examples comparing our approach with classical solutions based on a system of nonlinear equations. The proposed framework offers an interesting alternative for solving the nonlinear equilibrium problem, with particular potential for educational purposes and code prototyping. While our approach may not optimize computational runtime, it significantly streamlines coding time, thereby enhancing accessibility and usability in engineering applications.

Hydraulic Modeling of Water Distribution Networks: Hardy-Cross Method Implemented in Python

2024-12-12T12:18:13+00:00

Distribution network is a part of the water supply system that, formed by pipes and accessory parts, aims to provide potable water to consumers continuously with recommended quantity and pressure (TSUTIYA, 2006). However, due to the exponentially growing demand for potable water, the design of network layouts has become increasingly complex nowadays. In this regard, due to regional parameters such as topography and supply size, the use of meshed networks is feasible, in other words, networks that can supply a point through different paths due to their ring or block shape. Thus, this study aims to evaluate the performance of a meshed distribution network of a fictitious layout developed by undergraduate Civil Engineering students at the Federal University of Alagoas (UFAL) through system modeling in a Python program using the Hardy-Cross method. Furthermore, the effectiveness of the computational program was validated by comparing its results with those provided by the EPANET software. The methodology was based on the bibliographic review of issues related to solving meshed networks using the Hardy-Cross method, where a fictitious problem was modeled with parameters specified in NBR 12218/2017. Thus, this method was implemented in a computational program in Python language, and from this, the results related to the established layout were obtained. Additionally, the same layout was built in the EPANET software, and its results were used to validate the computational program. Therefore, it was possible to conclude that the computational program presented satisfactory results when compared to the EPANET software data, obtained due to recent performance advances in the Python language, which adds greater ease of use, result accuracy, modeling problem speed, and expands the possibilities of evaluating network performance. Finally, it was found that both modeling approaches are in accordance with the reference values established by TSUTIYA (2006) and recommended by NBR 12218/2017.

Implementing Steel Design in Educational Software: The Linear Elements Structure Model Program

2024-12-12T12:24:05+00:00

The Linear Elements Structure Model, or LESM for short, is a user-friendly, free-to-use, and open-source educational software for the structural analysis of models composed of linear elements. Aimed at aiding students, teachers, engineers, and architects to understand the behavior of structures better and improve their workflow, its intuitive and straightforward GUI (Graphical User Interface) allows a simple yet effective approach to modeling, running calculations of linear-elastic static and dynamic effects, and visualizing the internal stresses and strains in two-dimensional and three-dimensional trusses and frames. This paper expands upon the capabilities of LESM by detailing the implementation of steel design for bidimensional frames in compliance with the Brazilian steel structure design code, NBR8800:2008, within the current version of the software, building upon previous efforts to enhance LESM's functionality through object-oriented programming in the MATLAB environment. With the feature of steel design initially conceived as an extension for a prior version of the software, the LESM program has since been updated and reworked with more straightforward and quicker user interaction, a more optimized source code, and the addition of new features. By comparing past and current versions of the software and examining the source code of the steel design extension, it was possible to successfully integrate the steel design feature into the latest iteration of LESM, broadening the programs scope of use, both for the academic and industrial sectors in the field of analysis and design.

Interactive Modeling of NURBS for Isogeometric Analysis

2024-12-12T12:29:48+00:00

Isogeometric Analysis (IGA) is a numerical analysis method for structures that arises with the proposal of unification between design and simulation, allowing the creation of computational models that preserve the exact geometry of the problem. This approach is possible by a class of mathematical functions called NURBS (Non-Uniform Rational B-Splines), widely used in CAD (Computer Aided Design) systems for modeling curves and surfaces. In isogeometric analysis, the same functions representing the geometry approximate the field variables. In this context, this work was developed to provide a tool within the scope of computational mechanics for two-dimensional isogeometric analysis of linear elasticity problems, including the steps of modeling, analysis, and visualization of results. The system consists of two software programs: FEMEP (Finite Element Method Educational Computer Program), developed in Python and responsible for the geometric modeling stage, and FEMOOLab (Finite Element Method Object Oriented Laboratory), a MATLAB software for analysis and display of results. The proposed tool features a graphical user interface (GUI) that allows intuitive visualization and manipulation of NURBS curves with advanced modeling features such as curve intersection and region recognition features that streamline and simplify the process. The open-source system allows collaboration and continuous development by the community of users and developers.

STONEHENGE A toolbox for nonlinear vibration energy harvesting

2024-12-12T12:36:36+00:00

In this work, we present STONEHENGE - Suite for nonlinear analysis of energy harvesting systems, a comprehensive toolbox engineered to study nonlinear piezoelectric vibration energy harvesters. These harvesters can harness kinetic energy from the environment and convert it into electricity using the piezoelectric effect. By introducing nonlinearity through strategically placed magnets, their efficiency is enhanced across a wide frequency spectrum. However, it comes at the cost of increasing complexity in system dynamics. To investigate this complexity and comprehend the potential of nonlinear energy harvesting, the STONEHENGE library was created. It is tailored to analyze the harvesting performance and dynamic behavior of these systems and allows users to explore and characterize system dynamics across a diverse range of physical parameters and excitation conditions using advanced numerical simulations. The toolbox encompasses six key modules, (i) initial value problem, analysis of system behavior from initial conditions; (ii) dynamic animation: which provides visual representations of system dynamics, aiding in intuitive understanding and interpretation; (iii) nonlinear tools: equips users with tools to dissect and comprehend the nonlinear aspects of vibration harvesting systems, essential for comprehensive analysis; (iv) sensitivity analysis: facilitates the assessment of how system behavior responds to variations in parameters, offering insights into its robustness and performance under different conditions; (v) stochastic simulation: allows for the exploration of system behavior under stochastic excitation, crucial for understanding real-world operating conditions; (vi) chaos control: offers methods for mitigating chaotic behavior within the system, enhancing predictability and stability. Utilizing a bistable oscillator as a benchmark, STONEHENGE aims to serve as a valuable resource for the development and refinement of both existing and emerging nonlinear vibration-based energy harvesting systems. By providing a comprehensive toolkit for analysis and characterization, STONEHENGE seeks to catalyze advancements in this field, ushering in an era of more efficient and sustainable energy harvesting technologies. Moreover, this library was developed to be easily adaptable to different dynamic systems and can contribute to different application fields.

A Parametric Study of Intervening Factors in Vibration Mitigation in Wind Towers Controlled by TLCDs

2024-12-16T11:56:31+00:00

Wind turbine support towers are tall and slender structures, because of this, they have low natural vibration frequencies, which make them susceptible to vibrations due to wind, earthquakes and/or other dynamic actions. These vibrations can cause sensory discomfort and structural damage, causing collapse by amplification of structural responses or the failure of some structural components due to fatigue. Therefore, it is interesting to implement vibration control devices to attenuate the vibrations. This work analyzes Tuned Liquid Column Dampers (TLCDs) as a passive structural control. The mathematical formulations of the wind tower motion equations are presented for structural systems with a single, and with several degrees of freedom, under bending effects, and for the incompressible fluid column (TLCD). Initially, the tower and TLCD systems are studied separately, and later in a coupled manner, within a wide range of parameter values, an aspect that allows the construction of response maps representing the ratio of attenuated and non-attenuated structural response. A simplified way of optimizing parameters of a TLCD model in the time and frequency domain under harmonic excitation is proposed to improve the performance of TLCDs, as well as simulations on wind towers with many degrees of freedom, dimensions, and real conditions.

Aesthetic Integration of Structural Elements: Joaquim Cardozos Legacy in Modern Architecture

2024-12-16T12:01:04+00:00

In established architectural projects, the structure serves as a guiding parameter, meaning architecture is designed simultaneously with the structure. "Once the structure is complete, the architecture is already present, simple, and beautiful" (NIEMEYER, 2002). In modern Brazilian architecture, the role of structure in the composition of buildings is particularly noteworthy. Structural elements are often incorporated in an apparent manner, directly linked to the building's aesthetics. Engineer Joaquim Cardozo's works highlight several structural elements with these features, including the arches of the Alberto Torres Rural School in Recife (1935), the shells of the Igreja de São Francisco de Assis in Pampulha (1943), and the columns of the Igrejinha Nossa Senhora de Fátima in Brasilia (1957). In this study, we analyze these and other structural elements calculated by Joaquim Cardozo, using the software SAP2000. Our goal is to identify the significant contribution of the engineer and his structural solutions to modern Brazilian architecture, while also highlighting the relationship between structural systems and architectural aesthetics.

AI-based automation for structural design of buildings

2024-12-16T12:03:54+00:00

With the recent advancement of technology and computational empowerment, processes that were executed manually have the potential to be automated. In Civil Engineering, this is being seen through the implementation of technologies such as Building Information Modeling (BIM), Generative Design, Machine Learning and Artificial Intelligence. The objective of this work is to develop a computational system aiming to optimize the development of architectural and structural projects, implementing technologies such as artificial intelligence and generative design to automate and systematize processes inherent to the project pre-dimensioning phase when designing a building.

Initially, the user interacts with an AI-based chatbot interface which allows the definition of a buildings main characteristics, such as number of stories, apartments per story and minimum areas. The system has access to a database that contains different architectural BIM models and will filter them in order to provide the best option according to the user specifications. The selected model is processed by a Dynamo script in Autodesk Revit that automatically creates and allocates structural elements, e.g. beams, columns, slabs, and foundation. The script considers the intersection between walls and building corners, also positioning columns in wider spans avoiding doors and windows.

This structure is converted into an analytical model, so it can be exported to Autodesk Robot Structural Analysis where another Dynamo script is executed, which contains loads determined by technical standards as the Brazilian ABNT NBR 6118:2023 for concrete design. This script analyzes bending moments, shear effects and axial forces of the structural elements and, through limiting parameters, sends messages to Autodesk Revit, stating if a structural element needs to be modified to attend applied loads. This process runs continuously until all elements are adequate.

Using this technology, enterprises specialized in architectural and structural projects will save time, since allocating and pre-dimensioning structural elements are processes that are executed manually. Therefore, engineers are then able to focus on greater challenges involved in structural analysis and architects can simulate the dimensions of elements more accurately. There are still many processes in Autodesk Revit and Robot Structural Analysis that can be automated, and these will be further developed as a sequence of this study.

Determination of the Drag Force Disturbance Index for Analysis of the Neighborhood Effect in Tall Buildings Subject to Wind

2024-12-16T12:06:42+00:00

The presence of obstacles around a building can interfere with wind flow, modifying the pressures on the facades and, consequently, the resulting forces and moments. These interferences can generate protective effects or increase pressure coefficients. Therefore, it is important to study wind behavior in buildings in the presence of neighbors to better understand these effects and ensure the safety of structures. Most physical phenomena cannot be predicted with complete certainty and repeated measurements of these phenomena generate random results, with some of these results being more frequent than others. Reliability analyzes are commonly used to examine the behavior of structures subjected to such phenomena, and one of these analyzes is considering the beta reliability index, which has several representations and in this case, the determination of beta is proposed, not being considered a criterion of failure, but rather as a change in the state of the drag force. In this sense, the present work presents the determination, through reliability, of the drag force disturbance index, that is, how much the drag force is being modified depending on the presence of the neighbor, in order to evaluate the behavior of the effects of the wind from the CAARC (Commonwealth Advisory Aeronautical Research Council) standard tall building model, using experimental data generated in a wind tunnel. The standard tall building model was studied in different positions, subjected to variable drag force actions, in isolation and with the existence of different neighborhoods. Probabilistic concepts and graphs of results are presented and discussed in relation to the directions adopted by CAARC for beta variation indices. With the results found, it was observed that the existence of a neighborhood affects the average values of the data, as well as the aforementioned index, both for increase and reduction compared to the isolated building, depending on the situation. Therefore, this study presents interpretations that can help predict the behavior of tall buildings subjected to wind loads in the presence of neighborhoods.

Numerical modeling for the structural analysis of the unbuilt Praça Maior design by Oscar Niemeyer for the University of Brasília

2024-12-16T12:09:28+00:00

Many established architectural works follow the structural component as a guiding parameter of the project. The architectural works of Oscar Niemeyer are renowned for their seamless integration of structure and design "once the structure is finished, architecture is already present, simple and beautiful" (NIEMEYER, 2002). The structural elements are deliberately showcased, adding to the overall aesthetic of the building. Niemeyer was responsible for Brasilia's most significant public buildings, including the National Congress, the Metropolitan Cathedral, and the Planalto Palace. However, there are numerous unrealized projects, preserved in history through sketches and even detailed plans. One such project is 1962 Niemeyer's design for the Main Square of the University of Brasilia, which featured a distinguished architectural complex composed of four blocks - Auditorium, Museum, Library, and Rectory. In this article, we explore the relationship between structures and architectural engineering by modeling structural systems and conducting numerical analysis using the software SAP2000. The main objective of this investigation is to determine how the structural system played a key role in the architectural conception of Oscar Niemeyer for this iconic project. The study aims to offer an analysis of the relationship between form and function, with a focus on how the structural elements of the project influenced its overall design and aesthetic result.

Numerical simulation method for masonry partition walls affected by the deflections of concrete structures

2024-12-16T12:12:06+00:00

Non structural masonry walls can be damaged when submitted to in plane loads, imposed by the vertical deflections of their support structures (e.g. concrete slabs).
Given the high complexity of this problem associated to the masonry anisotropy and behaviour of interface joints wall/structure, including the difficulty of reproducing real scale prototypes for laboratory testing, the use of more generalised and time efficient models are important aspects to be considered.
Therefore, a numerical simulation method and its application is presented to simulate this type of problem. This method is based on a FEM macro-model, witch includes a constitutive damage model for concrete calibrated for masonry walls and a shear-cohesion model to simulate the interface joints. This method was simulated in a case study of a masonry partition wall loaded by the vertical deflections of adjacent concrete slabs. Results obtained highlighted a high risk of damage in the masonry partitions when these are affected by the structural deflections limits referred in literature, specially if no detachment wall/structure joints and reinforcement techniques are used.

Seismic Vulnerability Assessment Mobile Application for Rapid Visual Screening

2024-12-16T12:24:57+00:00

Similar to the Federal Emergency Management Agency's (FEMA) FEMA 154 method in the United States, which provides a rapid on-site survey method for building data to assess vulnerability indices and offers the RSV App mobile electronic form, this paper proposes the development of a mobile application for the visual rapid screening method for the Brazilian community of engineers and inspectors to assess the seismic vulnerability of existing structures. The simplified qualitative method adopted in the application originates in Japan, and a similar initiative was observed in that country at the symposium "Future of post-disaster assessment for buildings"; however, such an application was not found. Considering that the evaluation is carried out on-site, the application aims to facilitate the rapid screening process and disseminate the use of the method. Seismic-V was developed based on the Dart programming language and the Flutter framework. The Android Studio Giraffe IDE (Integrated Development Environment) | 2022.3.1 Patch 3 was chosen. Among the functionalities, it allows the structural verification for the five seismic zones with soil classes recommended in NBR 15.421. The user is required to provide real structural deterioration conditions, data, and structural characteristics such as number of floors, number of pillars, and respective cross-section that will support the seismic performance sub-index. Other features will be discussed in the paper and, at the end, a comparison will be developed between the results issued by the application and those calculated manually, with a discussion of the results. The proposal is relevant given the speed of application of the method and the initial screening that helps to prioritize existing buildings in future quantitative analytical approaches.

Study of the influence of construction stages on the analysis of tall reinforced concrete buildings

2024-12-16T12:27:12+00:00

This dissertation project proposes to investigate the influence of considering construction stages in tall reinforced concrete buildings by evaluating conventional strategies, which do not take the construction stages into account, and strategies that consider them in an approximate way, including a model interpreted as a reference, known as construction effect. Nowadays, with the development of structural analysis and design programs, a change in the structural calculation is observed, moving from conventional models to those that describe the real sequence of loading and construction. Since the structure is subjected to internal forces as it is built, it is desirable for structural engineers to consider the loading being applied progressively and the evolution of the mechanical properties of materials with time. The conventional method, by considering the action of all loads on the completed structure and the modulus of elasticity of concrete at 28 days, does not reflect the reality of constructions. The main distinction between analysis strategies lies in how displacements along the height of the building are treated. In the conventional model, since the loads are applied in a single step, displacements occur simultaneously and cumulatively. On the other hand, in incremental analysis, the loads acting on a given floor do not cause displacements, or consequent internal forces, on an upper floor not yet built. Analysis without consideration of the construction stages may result in an inconsistent distribution of internal forces and may not represent the real behavior of the structure, wich may even result in inadequate design and consequent pathological manifestations and/or collapse of the structure. Therefore, it is intended to conduct a comparison between the methods of conventional analysis, axial stiffness increaser, called the approximate method, and incremental analysis, seeking to understand the main differences in terms of internal forces and the design of buildings. For this purpose, softwares for modeling, analysis, and structural design that allow the simulation of these strategies will be used.

Twisted Tall Building Structural Response Under Lateral Wind-Induced Loads

2024-12-16T12:29:22+00:00

The design and construction of tall structures have consistently presented unique difficulties as architectural pushes limits continuously. Such building challenges demands from engineers' innovative structural solutions. Among these problems, a particularly notable one is the definition of twisted tall buildings structural system, which demand breakthrough designs to guarantee stability, safety, and functionality. The first twisted building, Turning Torso in Sweden, is a 190m tower designed by Santiago Calatrava with a total rotation of 90 degrees and its construction was completed in 2005.
Twisted tall buildings, in contrast to prismatic ones, have non-uniform floor layouts and facades that spiral upwards, resulting in a visually appealing architecture. Nevertheless, this aesthetic innovation brings benefits and drawbacks to all building subsystems. Some authors have studied that the facade spiral decrease the natural illumination, other postulated that this shape reduces the magnitude of wind loads but decreases the lateral stiffness of the building.
There are few studies on the structural form and on the response of twisted tall buildings under lateral loads. In this study, the behavior of tall buildings with 120m height under wind-induced loads will be investigated and contrasted between a prismatic model and various twisted ones, increasing the angle of rotation between different stories for each model from 0.5 to 6 degree. The analysis will be performed with procedural generated models in SAP2000 using Python programming language.
The wind load will be estimated for the prismatic model according to the Brazilian Code NBR 6123:2023 and will be applied to the columns nodes each floor. The same numerical value of the load will then be applied to the columns of all twisted models and the only variable will be the twist angle between stories. The objective of this study is to evaluate and compare the maximum story drift, horizontal displacement, and the ratio between cross-sectional pre-dimensioning at the bottom level of the columns according to Brazilian Code NBR 6118:2023 and the total floor area.

A permutation algorithm for stacking sequence optimization of composite laminates

2024-12-16T17:04:26+00:00

Structures made of fiber-reinforced composite material are used in many industries, such as automotive, naval, aeronautical, and construction civil. Laminated structures are produced by thin layers of composite material, such as carbon fiber-reinforced laminates, which have high strength and stiffness. These composites are stacked in different orientations in order to provide superior mechanical properties compared to other conventional structures. Due to the number of variables, the conventional design methodology based on trial and error is not attractive, and it is advantageous to use optimization techniques. When designing laminated structures, strength, stiffness, and performance constraints must be satisfied. Using optimization techniques, it is possible to find an optimal lamination scheme that meets the established prerequisites. In this type of structure, the arrangement of the layers and the orientation of the fibers can have a significant impact on the final performance of the structure. The permutation problem in optimization refers to determining the most effective sequence of layers and fiber orientations that meets the design requirements. This work proposes the implementation of a heuristic optimization technique based on design variable permutation. In this specific combinatorial optimization problem, the quantity of layers of each type (i.e. orientation) is known a prior, and the optimal arrangement of these layers is to be evaluated. The algorithm is implemented in Octave language and is demonstrated in optimization of laminated plates.

Advanced Computational Modeling with FVDAM for Homogenization of Reinforced Concrete Beams

2024-12-16T17:10:50+00:00

Reinforced concrete is widely used in civil engineering due to its strength, durability, and versatility. This material is heterogeneous, as it combines concrete with steel bars, giving it a tensile strength much higher than that of simple concrete. However, the computational modeling of this type of material is challenging due to the need to consider the distinct properties of the phases, generating considerable computational costs. According to Almeida (2018), the simulation process of reinforced concrete beams requires a meticulous analysis of the interactions between concrete and steel, as well as the non-linear behavior of the material under different load conditions. This complexity significantly increases the time and resources needed to perform accurate computational analyses. An alternative to modeling reinforced concrete is to replace it with a homogeneous material with properties/behaviors equivalent to those of the original heterogeneous material.
The Finite-Volume Direct Averaging Micromechanics (FVDAM) method emerges as a promising and efficient alternative for obtaining the effective elastic properties of composite materials with complex microstructures. In this study, the efficacy of FVDAM in the homogenization of reinforced concrete beams was evaluated. The stiffness using this technique was compared with that obtained using the calculations presented by Pinheiro (2007). In addition, two unit cell models were compared, differentiating the shape of the fiber: square and circular (Escarpini and Almeida, 2023).
In this work, it is expected to understand the influence of the fiber shape in the unit cell and compare the results of FVDAM with those of Pinheiro, in terms of stiffness, evaluating issues in the context of safety.

Analysis of Soil-Structure Interaction in Raft Foundation Using Grid Analogy

2024-12-16T17:14:33+00:00

Anticipating the behavior of structural elements to be designed is an inherent necessity in Civil Engineering. Within the realm of foundation structures, this need is no exception. In this context, it is pertinent to state that structural analysis softwares represents a significant advancement in this field. Its utilization enables the attainment of precise and often complex results through a variety of analysis methods. Consequently, the Grid Analogy method, through its numerical application, offers a simplified and effective approach to analyzing two-dimensional plate elements by treating them as grid elements. This study focuses on analyzing the soil-structure interaction in raft foundations, using an approach based on the Grid Analogy Method. This is achieved through an adaptation of the LAGI software, developed in Python, aimed at the structural analysis of slab floors, which now includes support for analyzing rafts supported on soil, serving as a flexible base for the structure. The Grid Analogy is employed as a technique that facilitates modeling for soil-structure interaction analysis, providing relatively accurate results and enabling a deeper understanding of raft behavior under different loading conditions and soil characteristics. Practical applications are utilized to validate the implementation of the modeling, along with comparison of results obtained from other structural analysis software. These results, which include internal force diagrams emphasizing maximum bending moments and displacements with their values, underscore the effectiveness of the adopted approach and present an innovative alternative for analyzing a crucial area within Structural Engineering.

Application of the finite element method for analysis of the influence of dynamic loads on a machine foundation on piles

2024-12-16T17:16:59+00:00

This work presents the fundamental concepts of structural dynamics, applied to the study of machine foundations. It discusses a method of obtaining the representative parameters of the pile-soil set considering the effect of the group acting by the proximity of the piles. In addition, this monograph is dedicated to preparing a detailed case study with the aid of ANSYS®, software based on finite elements, in order to reach the displacement values incorporated by the foundation element. These results were obtained according to normative criteria in the questions of severity of vibrations, effects on people and damage to the structure, allowing for attesting the capacity of the chosen foundation to resist the dynamic loads caused by the operation of the machine.

Application of the Immersed Boundary Method in the Study of Two Tandem Cylinders

2024-12-16T17:19:03+00:00

The study of fluid flow around various surfaces is crucial in several applications of mechanical engineering, especially in cylindrical geometries of circular section, common in structures such as bridges, wind turbines, cooling systems, and power towers. In this work, we solve the two-dimensional mass conservation and Navier-Stokes equations in the x and y variables, ignoring gravitational effects, applying the Fourier pseudo-spectral method coupled with the immersed boundary method. We define a domain with two cylindrical boundaries of diameter equal to 0.0016m and a low Reynolds number. The obtained results are promising, approaching existing literature reviews.

Arc-shaped elements in 2D program of frames subjected to thermal loading

2024-12-16T17:21:53+00:00

This research deals with the creation of a 2D frame program that includes circumferential and parabolical arc-shaped elements subjected to thermal loading. It was based on the Finite Element Method and written in Fortran. The elements have two nodes each and three degrees of freedom per node (both in-plane translations and out-of-plane rotation). The matrices were derived using Virtual Work and some integrals demanded a numerical approximation, where a Gaussian Quadrature approach was employed. The algorithm was checked against results found in books and papers, usual software where curves need to be approximated using a great number of straight elements, and structures designed and solved by the authors using traditional methods. The results for rotations, displacements, reactions, bending, normal and shear forces are seen to be very precise at a less demanding input data in comparison to others programs.

Assessment of Strategies for Numerical Modeling of the APB in Oil Wells

2024-12-16T17:24:24+00:00

This study aims to study and compare numerical modeling strategies for reproducing the phenomenon of Annular Pressure Build-up (APB) in vertical oil wells, in order to contribute to the development of procedures with higher accuracies. APB occurs due to the tendency of confined fluids filling the annular region between casings to expand in response to thermal variations within the well. This phenomenon is critical in the petroleum industry, especially in deepwater environments, where greater temperature and pressure differentials are present. APB leads to increased stresses on well casings, which can cause structural failures and, in extreme situations, could in human, environmental, and economic losses. Therefore, studying the origins and effects of this phenomenon and considering them during the well design phase are essential to ensure safety and efficiency. Motivated by the significance of the topic and the challenge of reproducing APB analytically, several authors have sought to model the phenomenon and its effects using finite element-based computational software like Abaqus. To achieve the proposed objective, the methodology adopted includes: a) literature review of existing strategies for APB modeling; b) definition of a simplified scenario for reproducing selected strategies; c) comparison of methodologies and results obtained from each; and d) discussion on discrepancies, gaps, and potential improvement opportunities. This study evaluates two modeling strategies in Abaqus, both utilizing fluid cavity interaction to model fluid behavior within a plane axisymmetric analysis. The difference lies in the approach to thermal expansion. While one calculates APB directly from thermal variation, the other does so by introducing an equivalent mass flow. Furthermore, the strategies will be compared not only in terms of results and accuracy, but also with regards to computational cost, aiming to identify the most efficient approach for modeling the phenomenon. Despite methodological differences, both approaches yield similar results, with the second providing the flexibility to model fluids with different behaviors. Thus, this study contributes to understanding and optimizing APB modeling, aiding in the development of more robust and efficient strategies for predicting the effects of this phenomenon.

Assessment of the structural integrity of cement sheaths in oil wells.

2024-12-16T17:27:43+00:00

This work proposes a study on the analytical modeling of the system composed of casing-cement-formation, considering the displacements and stresses acting at the interfaces, in order to assess the structural integrity of the cement sheath in oil wells. The interaction of this system is also evaluated through numerical modeling, using the commercial software Abaqus, aiming to verify the results provided by the studied analytical model. In the process of oil well construction, the cementing phase is one of the most important and demands integrity analyses and risk assessment, as poorly executed results in increased costs and operational problems. Cement failure can be modeled using the traditional Mohr-Coulomb criterion, which provides the limiting stress for shear failure. In this context, a comparative case study is presented to illustrate the proposed investigations and verify the results obtained from the following methodology: a) implementation of a discrete analytical model that estimates the mechanical behavior of the system and evaluates the integrity of the cement sheath and b) modeling of a discrete numerical model, evaluated by a static structural analysis, considering the effect of temperature and the debonding failure mode. Through a comparative analysis of the results obtained, it is noted that the two strategies used (analytical and numerical) provide very similar results. Thus, the computational implementation of the analytical solution is an important tool for the design of oil wells, allowing rapid analysis and prediction of the structural integrity of cement sheaths.

Automatic Detection of Seafloor Bedforms for 3D Bathymetric Data

2024-12-16T17:30:30+00:00

Seafloor bedforms are sedimentary structures that can reveal the local hydrodynamics conditions as they are the result of the bottom sediments' response to the dominant flow. The studying of these dynamic bottom shapes is important given that they can provide auxiliary information for the mapping of benthic habitats and can present a risk to navigation and marine structures. Mapping of the sea bottom is often done with dense and spatially extensive 3D bathymetry data (point clouds) resulting in a more precise representation of the targeted area. However, the most common praxis in this field is to rasterize the original data for the easiness in computation and lack of yet well-established methodology for 3D bathymetric data processing. As a consequence, the rasterization process causes information loss and increase of data processing time. The advantage of points clouds is that they comprise a larger volume of information in the same file, e.g. depth, intensity, RGB, and point classes, enabling a closer representation of reality and simultaneous generation of multiple products as potential habitat maps, Landscape Information Model (LIM), and denser Digital Bathymetry Model (DBM). Therefore, the purpose of this work is to apply a modified U-Net convolutional neural network for detecting and classifying bedform types in the bathymetry point cloud. The methodology will be applied to two datasets collected on the Espirito Santo Continental Shelf: Recifes Esquecidos (RE) and Doce River (DR).The following methodological steps will be carried out: (1) data collection, (2) generation of bathymetry derivatives as slope, curvature, geomorphons, aspect, and data tiling up for data augmentation, (3) image labeling, (4) model implementation including the training, validation, and testing steps, (5) calculation of models performance metrics: Intersection over Union (IoU), mean Average Precision (mAP), recall, and precision. This study will also present a performance comparison between the modified U-Net and a Random Forest (RF) forest. The selected areas are very rich in sedimentary features, so it is expected as the final product a classified points cloud in transversal, parallel, transitional, and artifacts (errors related to the surveying method) classes. It is also expected to have better performance from the non-convolutional model, RF.

Buckling of columns with top and distributed loading using Rayleigh's method: assessment of two cases of boundary conditions

2024-12-16T17:33:36+00:00

The problem of buckling in compressed parts has been the subject of study by many researchers due to the importance that these structural elements have for different areas of engineering. The compressive capacity of columns can be quantified using the so-called critical buckling load. The first studies date back to the work of Euler and Greenhill that began in the 18th century. Other contributions have been made since then. One of the most relevant for this field of study is the Rayleigh solution formulated to understand the vibration of elastic systems, whose equations can be directly used in determining the critical buckling load. The central feature of this method is the possibility of associating continuous systems with an equivalent system with a single degree of freedom. The Rayleigh method is used to define the critical buckling load of two columns under the simultaneous action of concentrated and distributed load along their length. Prismatic section parts are evaluated considering two boundary conditions. The values suggested in the literature are compared to the current results.

Comparative analysis of wellbore closure in salt rock formations considering primary creep

2024-12-16T17:36:03+00:00

This study presents a comparative analysis of vertical wells wellbore closure behaviour considering constitutive models with and without the incorporation of primary creep in salt rocks. In the context of drilling wells in the pre-salt region, one aspect that can jeopardise the operation is the phenomenon of creep, as time-dependent deformations accumulate and can lead to irreversible drilling column entrapment due to wellbore wall closure. Because of the complexity of drilling in salt formations, vertical trajectories are usually adopted in this region. During the design stage, well closure simulations are necessary to predict undesirable scenarios and thus assist in the appropriate selection of drilling fluids and the planning of reaming operations. Therefore, it is crucial to employ constitutive models capable of adequately representing the behaviour of salt rocks in these simulations. The constitutive model traditionally adopted for Brazilian rocks is the so-called Double-Mechanism of deformation. This model describes only the secondary creep stage, which is dominant over longer periods of time. This study focuses on comparing the differences between the results of well closure simulations with the Double-Mechanism and with the EDMT model (Enhanced Double-Mechanism using a Transient Function), which incorporates primary creep into the Double-Mechanism of deformation, thus being able to better represent short-term deformations. To achieve this objective, a case study is employed with the modeling of a synthetic well, using data consistent with real pre-salt wells. Elastic and viscoelastic parameters of saline rocks are obtained from the literature. The numerical simulation is performed using the finite element method. The well closure profiles of a well section obtained over time are compared. In the comparative analysis, the importance of primary creep in the well wall closure is further discussed by comparing critical time windows for restricting the passage of drilling equipment.

Comparison between simplified and refined models for deflection in continuous reinforced concrete T-beams

2024-12-16T17:39:30+00:00

Verification of the Serviceability Limit State for allowable displacements is a mandatory step in the design of a reinforced concrete (RC) beam. In order to proceed this verification, simplified methods recommended by Design Codes or analytical models can be employed. In these models, the variation in flexural stiffness due to the concrete cracking is the primary factor to be considered. A T cross-section beam present greater stiffness compared to a rectangular section of equal height and area. The concentration of more area at one end of the section raises questions about whether this type of section exhibits the same behavioral response as the rectangular section when applying the models for predicting deflection as indicated by Codes. In this work, a comparative study of different simplified methods and finite element (FE) models used for calculating deflections in reinforced concrete T-beams is performed. Simplified methods employed are the one recommended by Brazilian Code ABNT NBR 6118, and the Bilinear method recommended by the fib Model Code. Two FE models are adopted, in which the material nonlinearities are considered by means of moment-curvature diagrams, these based on the simplified methods. The deflections obtained by the different models are compared for several examples of continuous RC T-beams at service, by varying the beam geometry and the reinforcing ratio. The results are analyzed for short-term deflections and long-term deflections. In the end of this work, differences between the models are pointed and recommendations regarding the use of then are drawn for this specific section type.

Comparison of Operational Modal Analysis Methods for Aerospace Applications

2024-12-16T17:41:48+00:00

Structures engineered by professionals must endure various loads contingent upon operational requirements. Among these, dynamic loads like vibrations pose a significant challenge due to their potential to induce undesired behavior, leading to damage, operational impracticality, and even structural failure. Therefore, comprehending how structures respond to vibrations is paramount for ensuring integrity and safety. Operational Modal Analysis (OMA) emerges as a crucial tool in this pursuit. OMA serves as a potent technique for assessing modal parameters dictating structural dynamical behavior, encompassing natural frequencies, damping ratios, and mode shapes. The OMA process involves measuring structure responses to assumed white-noise input, generating correlation functions in the time-domain, and subsequently deriving auto-power and cross-power spectra families. What sets OMA apart from other methods like experimental modal analysis (EMA) is its utilization of real boundary conditions and operational inputs, enabling analysis without interrupting structure operations. This paper focuses on applying OMA to various structures, comparing established modal extraction methods from literature, specifically the Numerical Algorithm for Subspace Identification (N4SID), and the Stochastic Subspace Identification methods SSI-COV and SSI-DATA. Initially, the OMA method is validated on a steel cantilever beam, where modal parameters estimated by these methods are compared with theoretical data derived from modal simulations using the Finite Element Method, ensuring the accuracy of OMA results. Subsequently, a wing from an aircraft and a drone structure are subjected to testing to estimate their modal parameters for operational safety assurance. Results indicate a good correlation between theoretical and experimental modal parameters across all tests, affirming the efficacy of the OMA approach. Overall, this paper explores the application of three Operational Modal Analysis (OMA) methods across diverse structures pertinent to the aerospace industry, aiming to unveil their dynamic characteristics.

Computational Modeling for Evaluation of Plane Frames in Seismic Zones

2024-12-16T17:44:01+00:00

Seismic events, also known as earthquakes, induce dynamic effects on structures due to the abrupt movement of the ground, potentially leading these structures to collapse. These earthquakes are often associated with the movement of tectonic plates and primarily occur in regions near the edges of these plates, where interactions are more intense. However, there exists a specific category of earthquakes called induced seismic events, which are triggered by human activities such as mining, natural resource extraction, and fluid injection into the ground. There has been an increase in the occurrence of these earthquakes in some countries, raising concerns among authorities, especially in urban areas. In this context, our work aims to present a computer program for the dynamic analysis of plane frames, focusing on the structural behavior of such frames under the influence of seismic events. We consider seismic actions as stipulated in the Brazilian standard NBR 15421/23, as well as real induced earthquakes. The results obtained are essential for understanding the behavior of the analyzed structures and are necessary to ensure proper structural design, providing greater safety when these structures are subjected to this type of action.

Development of a finite element program for acoustics

2024-12-16T17:46:11+00:00

Acoustic is the study of mechanical waves in solids, liquid and gases.
Altougth the differential equations describing these problems are well known, with analytical solutions for simple geometries and/or loads, there are no closed solution for general problems. Thus, it is common to sougth on numerical procedures to address such problems.
This work addresses the simulation of mechanical waves in loseless air using the linear finite element method. Solution in both time and frequency domains are discussed and compared to theoretical results.

Effect of proof loading on the fatigue life of mooring lines

2024-12-16T17:48:02+00:00

The oil and gas production sector has experienced substantial expansion in recent decades, playing a crucial role in the global economy. To enhance productive efficiency, several extraction operations are carried out on offshore floating platforms over deep waters, which require advanced mooring system technologies to maintain their positional stability. These systems are exposed to cyclic loads throughout their operation and must be properly designed to withstand fatigue. However, recent incidents of premature failures in mooring lines have revealed a new type of fatigue failure in mooring chain links, induced by mechanisms entitled Out-of-Plane Bending (OPB) and In-Plane Bending (IPB), characterized by fatigue phenomena due to moments out of the plane of the link and in the plane of the link. The origin of these bending mechanisms is related to the manufacturing process of the moorings, during which proof loads of approximately 65% to 80% of the Minimum Breaking Load (MBL) are applied, as recommended by technical standards to extend the moorings lifetime. This process, however, causes plastic deformations that restrict sliding movement between adjacent links, resulting, along with friction, in significant bending stresses in the links. In this context, various studies have shown that parameters such as operational tension, link diameter, friction coefficient, and the level of proof loading significantly influence the incidence of fatigue damage in mooring lines. Therefore, the present study proposes to conduct a parametric analysis through finite element simulations, focusing on the variation of the proof loading level to assess its effects on parameters directly related to fatigue calculation and, consequently, the lifetime of mooring lines, such as stress concentration factors, OPB angle variation, OPB moment, among others.

Effect of repair factors on multi-level optimization of maintenance planning for corroded pipelines considering different failure modes

2024-12-16T17:52:24+00:00

The use of pipelines for transporting fluids is essential and has been growing
significantly in the oil and gas industry. Although pipelines are one of the safest
methods to transport these materials, it is necessary to consider the risks of failures in
the design, as such incidents can cause considerable damage to the population, the
environment, and the infrastructure. In this context, the aging of the pipeline network
has been extensively studied, and corrosion is one of the main concerns regarding
structural integrity. Therefore, adequate maintenance planning is essential to ensure the
safety and cost-effectiveness of the sector, as effective pipeline integrity management
can reduce expenses and maintain safety standards throughout the operational life of the
pipeline. In this scenario, inspection and maintenance planning research has become
increasingly relevant; recent studies have utilized reliability analysis through Monte
Carlo simulations to define optimal maintenance schedules for corroded pipelines,
aiming to minimize operational costs associated with pipeline management. This paper
investigates the influence of repair factors on the estimated total costs of inspection
schedules optimized for a given number of inspections, considering only one failure
mode and the combination of these (small leak, burst, and rupture). For this, a
combination of methodologies already validated and presented in previous works is
used, in which a multilevel optimization is carried out by predefining an upper limit for
the maximum failure probability, which will act as a constraint on the optimization
problem. The reliability analysis will be performed using Monte Carlo simulations,
which are commonly used in the literature. Finally, preliminary results indicated that the
failure mode strongly influences the final cost, so the results considering only one
failure mode are expected to differ considerably.

Finite element method applied to plane frames

2024-12-16T17:57:03+00:00

The calculation of displacements and forces in structural models is of great relevance in structural design and provides information about the behavior of the structure under different loading conditions. Due to the complexity of real problems and the demands of the production sector, the solution of a structural model becomes unfeasible without the aid of computational tools. The direct stiffness method, also known as matrix structural analysis, can be considered as a particular case of the finite element method. This article presents a computer software for structural analysis of plane frames using the direct stiffness method. The software considers the presence of hinged nodes and elastic supports in the structural model. The computational code was developed in Python language. Excel files are used as data input and output. Results include information such as nodal displacements, internal forces, and support reactions in the structure. Variations of internal forces along the frame axis, i.e. internal force diagrams, are presented in graphical manner. The influence of considering rigid or elastic supports on the results is investigated in the article.

HOOP: a Python software for homogenization of multiphase composite materials using object-oriented architecture

2024-12-16T18:01:10+00:00

HOOP (Homogenization Object-Oriented Programming) is a Python software package designed for efficient and flexible mean-field micromechanical analysis. Utilizing an object-oriented architecture, HOOP enables researchers to investigate mechanical and thermal phenomena within multiphase composite materials. By leveraging established libraries like NumPy, Seaborn, and Matplotlib, HOOP offers robust numerical operations, data manipulation capabilities, and compelling visualizations. The strategic integration of various Python libraries within HOOP's architecture fosters inherent flexibility and interoperability. This enables tailored workflows and seamless integration with established tools. Users can leverage alternative libraries for specific tasks, expanding capabilities beyond core functionalities. Moreover, HOOP has been rigorously tested and validated, emerging as a powerful and cost-effective alternative to commercial software for multiphase composite analysis. This makes it an invaluable tool for academic researchers and engineers alike, democratizing access to advanced micromechanical analysis capabilities.

Implementation of a convolutional network for detection of PPE in automotive repair services.

2024-12-16T18:04:42+00:00

This study explores the application of computer vision to occupational safety in automotive services, specifically focusing on the real-time detection of Personal Protective Equipment (PPE). The automotive service context presents unique challenges in managing the proper use of PPE, such as safety glasses, gloves, and appropriate uniforms, to ensure the safety of those involved in service execution.

Identifying and monitoring the correct usage of PPE is crucial for maintaining work quality and preventing workplace accidents. The research aims to develop and implement a methodology tailored to the specific needs of automotive services, with a focus on repairing windshields, headlights, and mirrors. A detection model based on the YOLOv8 convolutional network is proposed for its simplicity and potential for integration into a portable platform.

The study's objective is to achieve satisfactory precision in PPE usage detection. Additionally, it seeks to optimize the efficiency of automotive services, avoiding interruptions and delays in service delivery due to workplace accidents. The research builds on prior studies that demonstrated the effectiveness of computer vision in PPE detection in industrial and construction settings. The proposed approach includes creating a dataset and training a convolutional network with approximately 2000 images from security cameras.

The research significantly enhances both computer vision and occupational safety in automotive services, reducing the number of non-compliances found in internal inspections and improving the quality and safety of the workplace. Moreover, it addresses challenges related to managing image banks and the complexity of detecting PPE. The study also examines successful experiences in other sectors that used convolutional networks for real-time PPE detection.

Implementation of Gaussian quadrature in Python program for grillages with curved elements

2024-12-16T18:07:38+00:00

This paper demonstrates the development of a Python program for linear-elastic structural analysis of grillages featuring circumferential arc-shaped and regular straight elements subjected to concentrated and distributed loads. The algorithm is based on the Finite Element Method. The force method was employed to compute the flexibility matrix, followed by the determination of the stiffness matrix and load vectors through inversion. A Gauss-Legendre Quadrature was incorporated in order to have a better control on accuracy for displacements, rotations, forces and moments. Results were validated through comparisons with literature data and similar software where curved structures are simulated using numerous straight elements. It was demonstrated that the Python-based program yields results closer to the exact solution with simplified input data, highlighting the effectiveness of both programming language and Gauss quadrature technique in structural analysis.

Isogeometric Analysis of Functionally Graded Plates using High-Order Theories

2024-12-16T18:10:16+00:00

Functionally Graded Materials are composites, usually of ceramic and metal, in which the volume fraction of their constituents varies smoothly along an interest direction. These materials were initially proposed as a solution for thermal barriers development, but are currently used in different applications. The composition variation results in a gradual change in their properties, enhancing the performance of structures subjected to thermal and mechanical loads, but making structural analysis more complex. Plates, on the other hand, are three-dimensional flat structures in which the thickness is much smaller than their other two dimensions. Different theories have been proposed for structural analysis of plates. These theories can be grouped based on the considerations adopted for the behavior of transverse shear deformations. In this regard, there are the Kirchoff-Love Theory (also known as the Classical Plate Theory - CPT), which disregards the effect of these deformations, the Reissner-Mindlin Theory (also known as the First-Order Shear Deformation Theory - FSDT), which considers shear deformations constant throughout the plate thickness, and Higher-Order Shear Deformation Theories (HSDTs), which consider a nonlinear variation of shear deformations through different approaches. Among these theories, the most robust and accurate ones are evidently the HSDTs. However, it is important to clarify that they require the displacement field to have a C1 continuity, which is complex for isoparametric finite elements. Thus, Isogeometric Analysis emerges as a more viable alternative by employing high continuity elements based on Non-Uniform Rational B-Splines (NURBS) functions. Therefore, this paper presents a NURBS-based isogeometric formulation for buckling and free vibration analyses of functionally graded plates using a HSDTs. A series of tests were conducted to assess the accuracy of this formulation considering examples available in the literature with different geometries, boundary conditions, and materials. The obtained results present excellent agreement with the reference solutions for thin and thick plates.

Matrix structural analysis of beams on elastic supports: implementation in Python

2024-12-16T18:12:36+00:00

Technological resources have made it possible to model natural phenomena and engineering problems more accurately, thus allowing better results. This article presents the computational implementation of a procedure for matrix structural analysis of beams. Both rigid and elastic supports were considered to represent the contact between the structural model and the external environment. A computational code was created in Python language. The matrix method allows a detailed analysis of the structural response. The developed code calculates stiffness matrices and force vectors of beam elements, which are assembled into a global stiffness matrix and a global force vector, and the equilibrium equation system is then solved. Results such as nodal displacements and slopes, support reactions, and internal forces are obtained. Different support conditions, namely fixed, hinged, and elastic supports, as well as different loading conditions, were investigated for beams. Results highlight that the presence of elastic supports can significantly affect the overall structural behavior of the system. By incorporating these effects into the analysis, more accurate predictions of structural response can be obtained, leading to safer and more economical solutions. The article provides a basis for further investigation of the behavior of complex structural systems. The use of Python language can be justified as it provides a versatile and efficient platform for conducting structural analysis and is suitable for future advances in the field of structural engineering.

Modeling of Creep Closure of Salt Rocks Drilled by Directional Wells

2024-12-16T18:16:26+00:00

This paper presents a strategy for three-dimensional modelling of directional wells penetrating salt rocks, aiming at predicting the closure of these rocks due to creep. One of the major challenges in oil production in the pre-salt region is drilling through thick layers of salt rocks. During drilling, these rocks deform in the direction of the wellbore closure due to creep. The accumulated deformation of the wellbore wall over a given time interval can lead to the restriction of the drilling string's passage and even its irretrievably trapped. Directional wells in salt regions present an even greater complexity, as changes in inclination alter the stress distribution around the well, changing the configuration of the deviatoric stress, with no symmetry around the well's central axis (as in vertical wells). This paper discusses a strategy for modelling directional wells in salt regions using the commercial software Abaqus. This software implements the Finite Element Method, including its three-dimensional formulation, and allows modeling of creep deformation of materials, enabling the implementation of constitutive models different from traditional ones through subroutines. The adopted constitutive equation is the most recurrent in the literature to describe the creep phenomenon in wells through Brazilian salt rock. To verify the developed strategy, a vertical well is modelled, and the obtained results are compared with those presented by axisymmetric modeling, already consolidated in other works developed by the group. After verification, directional wells are modelled and studied, and their behavior is discussed regarding the observed displacement and stress fields, mainly along the region near the wellbore wall. This work contributes to the understanding of the creep behavior in salt rocks when drilled by directional wells, and discusses some strategies that can contribute to the stability of the rock formation, aiming at the safe and efficient construction of wells in salt regions.

Numerical approximation of the Womersley problem in OpenFOAM.

2024-12-16T18:19:54+00:00

Replicating the pulsatile blood flow in simulations under various physiological conditions is essential for understanding hemodynamic behavior and its relationship with cardiovascular diseases, as well as for developing innovative clinical approaches. The Womersley number, which describes the relationship between pulsatile flow and mean flow in a blood vessel, directly influences vascular biomechanics. Computational Fluid Dynamics (CFD) simulation provides a detailed analysis of blood flow in three-dimensional models of vessels, allowing for precise representation of vascular geometry and the inclusion of pathological conditions such as stenoses and aneurysms. This study aims to implement the Womersley number in CFD simulations using the OpenFOAM software to model hemodynamic behavior in blood vessels. Cases will be developed to obtain Womersley velocity profiles in different vascular geometries using a periodic pressure difference. Results will be compared with literature data to ensure the accuracy and reliability of the Womersley number application.

Numerical investigation of wind loads on an industrial shed with rounded eaves with different height-width relationships

2024-12-16T18:24:47+00:00

Pressure distributions due to wind in structures are commonly estimated using computational analysis tools as an alternative to studies carried out in wind tunnel tests, thus making it possible to study the dynamics of this fluid for various boundary conditions and geometries. That way, this work discusses the behavior of the external pressure coefficients in an industrial shed with rounded eaves, taking into account the following height-to-width ratios (H/B): h/b=0.5, /b=0.75, h/b=1.0 and h/b= 1.25. In addition, the following radius-height ratios (R/H) were also investigated for this model considering the most critical case (θ=90°; H=18.75 m): R/H=2.5%, R/H=5%, R/H=7.5%, and R/H=10%. Using Ansys Workbench software, the external pressure coefficients were obtained for wind at 45° and 90°. In the height-width ratio analysis, the results indicated that the external pressure coefficients are more intense in the 90° configuration, and the behavior of these coefficients changes between the wind directions analyzed from approximately 50% of the width of the shed. For the radius-height reduction, there was a noticeable attenuation of the suctions in the roof. Therefore, the distribution of external pressures obtained using computational methods allowed us to conclude that the effects caused by the variation in the height parameter can be, in the worst of the cases analyzed, intensified or reduced by varying the rounding radius of the eaves.

Numerical investigation the influence of solid and porous parapets on wind loads on low-rise buildings.

2024-12-16T18:37:34+00:00

Several studies have shown that parapets mitigate the damage and economic losses due to wind action on buildings. Therefore, in this work, a computational analysis of the influence of different parapet geometries and heights on the wind flow on the roofs of low-rise buildings has been developed using the Ansys Workbench software. Solid and porous parapets were considered, and a decrease in the external pressure coefficient was observed as the height of the parapet increased, as well as a greater efficiency of porous parapets than solid ones.

Numerical Modelling of Conductor Casing Settlement Using a Two-phase Model

2024-12-16T18:42:18+00:00

Oil exploration in subsea wells is a complex activity that involves a number of technical challenges, including installation conductor casing installation. The conductor casing plays a crucial role in the structural stability and overall performance of the well. Thus, for the conductor sttelemnt, one can highlight, among other techniques, the jetting method. Jetting is a promising technique for clay soils since seabed sediments behave like fine mud. In order to numerically model the operation, the clayay soil can be represented by a highly viscous non-Newtonian fluid.
The aim of this study was therefore to carry out a numerical analysis of the conductor settlement by jetting. In order to achieve the proposed objectives, an eulerian - eulerian two phase model has been adopted. The soil phase has been modelled as a non-Newtonian fluid and computational fluid dynamics (CFD) has emerged as a powerful numerical tool for modeling and simulating problems of this nature in a attempt to bypass the issues that comes with large deformations problems other numerical methods. Ansys Fluent software was used, a CFD program based on the Finite Volume Method (FVM), which stands out for its robustness and precision when carrying out fluid dynamic simulations. The numerical analysis was carried out using the Gidaspow drag model to characterize the soil, which combines the Ergun and Wen-Yu empirical correlations.
The results obtained showed that the excavation of the seabed using the jetting technique is significantly influenced by the velocity of the jet. In addition, other criteria also affect excavation, such as the type of fluid injected and the size of the drill bit.

Numerical simulation in the wind action analyses in silos with a windbreak

2024-12-16T18:46:25+00:00

A windbreak, by definition, is the planting of single or multiple rows of trees to reduce the wind speed to leeward. In this work, was analyzed the efficiency of windbreaks in attenuating the external pressure coefficients of wind action in silos. The methodology was validated using the Ansys Workbench software, considering a height/diameter ratio equal to 0.5. In other applications was studied the influence of the neighborhood on the external pressure coefficients and streamlines between geometrically identical silos. The significant reduction in external pressure coefficients was verified, highlighting windbreaks as an option to protect silos in open areas with high wind loads.

Parametric Study of Pile Installation Using a Numerical Approach with Material Point Method

2024-12-16T18:49:03+00:00

In engineering, problems dealing with rigid structures that penetrate the ground are common. A better understanding of the installation process of these bodies can be obtained through numerical studies. Each technique has its own advantages and challenges, and the choice of the appropriate method depends on the specific geotechnical conditions. The main objective of this work is to conduct a parametric study of pile installation by impact driving using a prototype numerical model in order to analyze the behavior of these structures when penetrating the soil. This will enable the construction of more complex numerical models that simulate impact problems, such as driving a conductor casing in oil well projects or installing monopiles in the construction of wind turbines. To achieve the established objectives, the Anura3D is employed, an open source simulator based on Material Point Method (MPM). The parametric study is carried out considering a non-cohesive soil, modeled by Mohr-Coulomb. Additionally, the pile is treated as a rigid body. The parametric study conducted in this work provides valuable insights into optimizing engineering projects, enhancing its efficiency and effectiveness .

Partially encased composite steel and concrete columns: a systematic approach to the literature

2024-12-16T18:52:55+00:00

Partially encased composite columns emerge as a promising solution in structural engineering, combining the versatility of steel with the durability of concrete. This article explores their characteristics and advantages, highlighting the construction efficiency and resource savings they offer compared to traditional reinforced concrete structures. While steel provides strength and speed in construction, concrete offers protection against fire and compression. The study consisted of two stages: the systematic literature review, in which the most relevant bibliography for the objective of the article was selected, and the meta-analysis stage. The studies indicated a decrease in the initial stiffness, maximum load and ultimate strength of the columns, with an increase in eccentricity, as well as an increase in the peak axial load and final moment of resistance in high-strength concrete, especially in slender columns which present reduced peak axial load due to the increase in the slenderness index. Furthermore, partially encased columns demonstrated superior compressive strength to steel at high temperatures. Therefore, these columns represent a promising option, subject to additional considerations and specific studies.

Practical Design of Cold-Formed Steel Sections by the Direct Strength Method

2024-12-16T18:55:13+00:00

Cold-formed steel are among the most widely used in steel construction, being extensively employed in roofing and lightweight structures in general. Despite their popularity from a construction perspective, due to the existing manufacturing and utilization facilities, they prove to be quite complex from a design standpoint, as verifying these components involves extensive and complex calculation procedures due to the various global and local instability phenomena that may occur. Among the three design methods presented by the Brazilian standard NBR 7190, this study applies the Direct Strength Method in the development of a computational application that allows for the practical design of cold-formed steel subjected to oblique composite bending. This addresses the vast majority of calculation situations encountered in practice. The application has been tested in various design scenarios, and the results have been compared with those provided by other methods recommended by NBR 7190, showing a highly satisfactory performance.

Pre-processing for isogeometric analysis of laminated composites

2024-12-16T19:03:34+00:00

Composites are materials resulting from the mixture of two or more components, usually a polymer matrix reinforced with synthetic fibers, used to build stronger structures capable of withstanding heavy loads and unfavorable environmental conditions. Laminated shells are made of layers of fiber-reinforced composite material, stacked in a specific sequence to ensure good structural performance. The analysis of these structures is predominantly done using the Finite Element Method, a conventional approach used to solve these problems, approximating both the displacements and the geometry of the structure using polynomial functions. A more recent alternative is Isogeometric Analysis (IGA), which uses rational functions to approximate the displacements and geometry of the structure. This ensures that the geometry of the problem is exact, regardless of the level of discretization used. The aim of this work is to study the use of NURBS surfaces in the context of isogeometric analysis of laminated structures. The theoretical and practical aspects of these representations will be studied, with emphasis on the pre-processing stage of the numerical analysis. In this context, the pre-processing of the numerical model of the composite material structure is carried out in the academic software FEMEP (Finite Element Method Educational Computer Program), written in the Python language. The software's graphical interface has been extended to handle models of laminated composite plates. The numerical model is processed using the FAST tool, where the pre-processing program writing routines have been implemented. In the post-processing stage, the simulation results are visualized using the Nlpos tool. The system developed was used in examples of laminated plates, demonstrating the system's capabilities.

Reinterpretation of the Cross Method: Gauss-Seidel approximation for the solution of transverse dislocation

2024-12-16T19:05:58+00:00

The Cross Method was very used for analysis of structures, this was to the agility of the method. But he lose his use by the limitations of metho, such as transversal dislocations. So, a general method was proposed, able of analyzing structures with transversal dislocations and have the classical method as a particular case. The methods found to get these objective was to use displacement method and Gauss-Seidel approximation together and compare with the classical method. The results showed the Gauss-Seidel approximation was able to obtain an approximate solution to for structures with transverse dislocations maintaining part of the agility of the traditional method. With these results, can be concluded that Cross's reinterpretation is able to analysis of structures with transverse dislocation more easily than the classical method.

Reliability-Based Boundary Element Models for plane linear elasticity

2024-12-16T19:07:59+00:00

In Structural Engineering, one of the main objectives is to find robust solutions that ensure structural safety without sacrificing cost-effectiveness. To achieve this goal, one strategy involves considering the uncertainties inherent in projects, taking into account the variability of design parameters, rather than relying solely on characteristic values provided by semi-probabilistic approaches. This probabilistic paradigm allows for estimating the probability of failure of structural elements and systems, providing robustness to design, contributing to decision-making process, and reducing risks associated with both overly conservative and expensive projects, and economical yet unsafe projects. This study aims to implement the coupling between mechanical and reliability models to analyze the structural behavior of plates in linear regime. Mechanical models based on the Boundary Element Method (BEM) and reliability models based on Monte Carlo Simulation (MCS) and First Order Reliability Method (FORM) will be developed and validated, by using Python language. The random variables considered may include mechanical parameters such as elasticity modulus and Poisson's ratio, dimensions of structural elements, as well as applied loads. The objective is to evaluate the probability of occurrence of usual limit states in structural analysis, such as the violation of allowable displacement and stress values.

Space truss finite elements applied to actuated structures and origami implementation and discussions

2024-12-16T19:10:05+00:00

In the various branches of engineering, dynamic analysis of structures is always a relevant topic and the training of future professionals and researchers in this area is always important. Nowadays, with the evolution of materials and topological dispositions, structural elements and structures are becoming increasingly lighter and slender, increasing the amplitude of movements in such a way that nonlinear geometric analysis is necessary. regarding actuated structures or origami mechanisms, there is a natural mobility between planes defined by the relative rotation in the creases that makes it possible to create foldable devices of great interest such as the production of retractable roofs, retractable antennas, wheels for light vehicles, biomechanical devices , among others. This work introduces the presence of actuators in spatial structures by directly controlling the initial length of truss elements (actuation). At the same time, to define origami or flat 3D structures, it is necessary to introduce the strain energy associated with the folds at the junction between flat panels (creases). To introduce this energy, vectors orthogonal to the adjacent origamic planes are defined and fictitious spring elements are introduced to oppose the change in the angle
between the planes. Illustrative examples and discussions of future work are presented.

Surrogate Based Optimization of Functionally Graded Plates

2024-12-16T19:12:40+00:00

Functionally Graded Materials (FGM) are composites, usually made of ceramic and metal, in which the volume fraction of their constituents varies smoothly along an interest direction. These materials were initially proposed as a solution for the development of thermal barriers, but are currently used in different applications. The variation in composition results in a gradual change in their properties, improving the performance of structures subjected to thermal and mechanical loads, but making structural analysis more complex. Plates, on the other hand, are three-dimensional flat structures in which the thickness is much smaller than their other two dimensions. For projects involving functionally graded plates, both the choice of their constituents and the definition of the distribution of volume fractions are necessary. Computational methods, which simulate the behavior of these structures, and optimization techniques, which explore the design space, are used to obtain a more efficient solution. However, the computational cost of structural analyses can be a limiting factor in the optimization process, since bioinspired algorithms require the analysis of a large number of trial solutions to find the optimal design. Thus, this work addresses the use of surrogate models capable of efficiently approximating the results of numerical simulations. These models are an alternative to reduce the computational cost of the design optimization of complex structures. Surrogates have been incorporated into an optimization methodology known as Sequential Approximate Optimization (SAO), where the approximate response surface is continuously updated and improved by the insertion of new points, enhancing the model approximation. The proposed methodology will be used in the design optimization functionally graded plates considering buckling and free vibration. The results will be evaluated in terms of accuracy and efficiency based on a set of benchmarks.

Surrogate model for predicting stresses of concrete slabs subjected to real vehicle loading using multilayer perceptron neural network

2024-12-16T19:15:12+00:00

This work proposes an innovative method that uses machine learning with computational finite element simulations to optimize the design of concrete slabs for rigid pavements subjected to moving loads of different speeds. The objective is to create a surrogate model that takes into account the uncertainties of weight, shape and speed of vehicle loading on the concrete slabs, together with the uncertainties of the pavement temperatures, to predict the displacements and stresses in the concrete slabs. Realistic finite element models consider the three-dimensionality of the multilayer problem as well as the inertial effects due to moving loading at different speeds. Based on the results of finite element analyses, machine learning techniques are used to train and validate a surrogate model. This model allows the analysis and quantification of the uncertainties of displacements and stresses in concrete slabs under different conditions of vehicle speed, vehicle load and pavement temperatures. Based on these analyses, it is possible to optimize the shape and thickness of concrete slabs to cope with the effects of uncertainties, thus ensuring adequate performance of the structure under a wide range of operating conditions. This approach allows for a more precise and efficient optimization of concrete slabs, taking into account the dynamic and stochastic variables involved in the process.

Top of cement influence on APB mitigation in high pressure and high temperature oil wells

2024-12-16T19:17:12+00:00

This work presents a study on the influence of Top of Cement (TOC) in mitigating Annular Pressure Build-Up (APB) in wells subjected to high pressure and high temperature (HPHT) conditions. Oil and gas exploration in HPHT wells poses significant engineering challenges, including an increased occurrence of APB. Under extreme circumstances, APB can compromise casing integrity, leading to oil leakage into the marine environment and jeopardizing safety and operational continuity. The objective of this study is to comprehend how TOC height influences APB behavior. Additionally, in cases where the cement top does not cover the previous casing shoe (open shoe), the study examines how fluid leak-off affects APB response. The methodology consists of four main stages: i) literature review on characterizing and modeling APB in HPHT wells; ii) implementation of a semi-analytical model proposed in the literature to calculate APB considering cement effects and formation leak-off; iii) modeling scenarios with varying TOC heights; and iv) analyzing results to observe the relationship between APB, TOC heights and casing safety factors. These results are compared with those from widely used commercial software in the industry. The results obtained with the implemented model demonstrate that positioning the TOC below the previous casing shoe effectively reduces APB. However, caution is warranted when reducing TOC height, as it is crucial for wellbore stability. Thus, this study contributes to developing a methodology for evaluating the impact of TOC height and leak-off on APB, providing guidance for future research and practical applications in the industry, and enhancing safety and operational efficiency in HPHT wells.

Topology optimization of spatial frames

2024-12-16T19:21:30+00:00

The pursuit of improving projects, such as optimizing resources and material usage, has led to an increased interest in structural optimization techniques. Among the various options available in the literature, the topology optimization stands out, allowing the design of structures with extreme behavior and significant material reduction, while adhering to constraints on the mechanical behavior of the structure. This study aims at implementing the topology optimization for spatial frames, with the goal of reducing volume with stress and displacement constraints. The mathematical formulation and computational implementation were developed by the authors and are available on github. The results show significant reduction on material usage while respecting the functional constraints

Translational joint in a Finite Element Analysis program of 2D frames with straight and curved elements

2024-12-16T19:23:39+00:00

This paper describes the development of an algorithm for the structural analysis of bidimensional frames with straight and curved elements that include a translational joint which can be set to any specified angle. The code was written in Fortran following a Finite Element Method-based structure. Three elements were considered: a circumferential arc-shaped; a straight bar with cross-sectional height varying according to a linear polynomial function; and the traditional straight element with constant inertia. All Stiffness matrices and load vectors were derived from the inversion of their corresponding Flexibility matrices obtained using the Force Method. In a few cases, a Gaussian Quadrature was needed in order to calculate the integral. The resulting program was validated against solutions found in the scientific literature in addition to structures created and solved by the authors using the Virtual Work Method, and it is shown to give very accurate predictions for displacements and rotations as well as reactions and internal forces (axial, shear and bending).

Use of Computational Fluid Dynamics to investigate heat exchanges in Floating Solar Plate Systems

2024-12-16T19:26:34+00:00

This study aims to investigate the temperature gradient between floating and non-floating solar panels, with the purpose of comparing results and enhancing the efficiency of solar energy production by reducing the temperature of the solar modules. This modeling is crucial to inform future development and implementation of more effective and sustainable solar systems, as well as to pursue the implications caused by these installations.

Thermal analyses between floating and non-floating solar modules were conducted using Computational Fluid Dynamics (CFD) via the Finite Volume Method to obtain the variables of interest. These finite volumes are interconnected by points called nodes. The set of all these elements and nodes is called a mesh, produced by the discretization of the geometry. All stages of this simulation were performed by entirely open-source software, from geometry and mesh generation to result visualization.

The simulation revealed a significant difference between the temperatures of the floating and non-floating panels, approximately 6 K (6°C), considering only one photovoltaic module. This discrepancy tends to have a positive impact on energy production, as the temperature of the solar cell affects its electrical current. Thus, reducing the temperature of the solar cells, as observed in the floating panel, results in an improvement in energy production. However, it is important to note that the increase in temperature resulting from the installation of a photovoltaic array on a large scale may lead to an increase in water temperature.

In summary, the experimental data presented by the simulation, corroborated by previous experiments, highlights the relevance of research in the field of solar energy, emphasizing the potential of innovative solutions, such as solar panel floating, to boost the efficiency and sustainability of photovoltaic energy generation. All of this supports our results and encourages us to continue investigating innovative solutions in the field, with the learning and improvement of simulations via computational methods and the perpetuation of the use of open-source tools.

Validation of an in-house developed acquisition system using a commercial acquisition system and the theoretical model of a clamped beam

2024-12-16T19:29:23+00:00

Vibration analysis is a technique that allows understanding through visualization of the frequency spectrum the propagation of vibrations in which a body is receiving from external forces. At a laboratory, the type of study allows the students to learn the concepts of this invisible force that is present in all the bodies and it also helps to understand how the material characteristics and the sample specimens geometry behave in these situations. Therefore, the objective of this project is the development of a didactic kit that allows the study of modal vibrations in test specimen such as beams, without the need of a vibration analysis equipment available in the market, that, in addition to the high cost, these equipments have reserved construction characteristics, that requires specialized training to understand how it works. For this acquisition system, it developed an accelerometer, analogical low-pass filters and an esp 32 microcontroller with A/D converter. The data processing was performed with a program developed in MatLab. A clamped beam was used to validade the project, in which a frequency analysis was performed. For this validation process, the kit results were compared against the mathematical model of the beam, whose first natural frequency is around 7Hz, and a commercial hardware available in the market. With these results, it was possible to evaluate the reliability and accuracy of the acquisition system in relation to computational models. Therefore, after extensive testing, this project can be manufactured by other institutions, bringing to the students in the educational environment the capacity to understand the structure and working of the equipment, besides learning how structures behave when submitted to many different vibration modes.

Visual Analysis of Anomalous Behavior Patterns in Oil Wells Using Dimensionality Reduction with t-SNE Projection

2024-12-16T19:33:12+00:00

Anomaly detection in production processes, especially in the oil industry, is of paramount importance due to the complexity and criticality of these systems. Producing oil wells are subject to a series of dynamic and interdependent variables, which can be monitored using sensors installed along the well. Precise analysis of these sensor records is essential for early identification of possible anomalies, as any deviation from the normal pattern can result in serious consequences, from operational failures to environmental and safety risks. Given the multidimensionality and variability of this data, the use of machine learning techniques becomes indispensable for analyzing and classifying the well's situation. However, even for computational software, anomaly identification remains a significant challenge, given the oscillatory behavior and scale disparity of the variables analyzed throughout the well's productive life. To mitigate these challenges, dimensional reduction techniques can be implemented, as they can bring some advantages, such as reducing computational cost, noise reduction, and improving classifier accuracy. A widely used tool for dimensional reduction, especially for visualization, is Distributed Stochastic Neighbor Embedding (t-SNE), which seeks to project high-dimensional data into a low-dimensional space preserving clusters, bringing similar data together by affinity through a t-distribution. For this approach, real records of pressure and temperature sensors from oil wells are used. These sensors are located at eight distinct points in the well, totaling eight dimensions that will be reduced to a two-dimensional plane. Therefore, this study aims to identify behavior patterns in multivariate data from producing oil wells visually using the t-SNE dimensionality reduction method. It is expected that through visualization, it will be possible to identify behavior patterns before and after the occurrence of anomalies and enable the development of appropriate artificial intelligence algorithms for this anomaly detection problem.

A numerical study on the critical bending moment for distortional buckling of cold-formed lipped C-sections

2024-12-02T13:20:39+00:00

Applications of cold-formed profiles have become more common in the civil construction industry. In particular, the cold-formed lipped C-sections are frequently used. Mostly, these channels are submitted to bend about the major principal axis and, consequently, they get subjected to compression stresses that, due to their considerable local slenderness, can provoke instability. Particularly complex, the distortional buckling is one of those failure modes and may occur in cold-formed lipped C-sections causing translation of the edges. Thus, this article intends to evaluate theoretical design procedures, from the perspective of accuracy and implementation, when used to calculate the critical bending moment of distortional buckling. Four formulae were selected and, for comparison, two computational approaches were employed to determine, numerically, the critical moments in different lipped C-sections: the finite element method (FEM) and the finite strip method (FSM). The Hancocks and Schafers formulations proved to be highly precise when confronted with the numerical data. An adapted procedure presented by AISI, based primarily on local buckling designs, showed itself imprecise, returning both unsafe and conservative results depending on the cross-section. The last one was the simplified method, also available on AISI standard, and as expected, it was conservative when predicting the distortional buckling moment. Conclusions regarding the critical moment and buckling modes with changes in geometrical parameters were also extracted. Thickness increase led the critical moment to grow, as expected, due to the reduction of local slenderness provided. Likewise, as the lip width gets larger, the critical moment rises, however the profile tends to fail by local buckling mode, evidencing the need for attention when using channels with too narrow or too wide lips.

Assessment of the Dynamic Structural Behaviour of Steel Wind Towers when Subjected to Wind Loadings

2024-12-02T13:37:20+00:00

This research work investigates the structural response of a steel tower supported by an octagonal reinforced concrete foundation designed to accommodate a 2 MW wind turbine. The wind tower finite element model was developed based on the use of the Finite Element Method (FEM), utilising the ANSYS computational program, and considering the wind loadings on the rotor and tower, and the soil-structure interaction effect, aiming to obtain a realistic representation of the structure dynamic behaviour. In this investigation, given the stochastic nature of wind load modelling, a statistical analysis of the structures dynamic response was conducted in order to determine maximum values for displacement and stresses. Initially, the static and dynamic analyses have demonstrated that, incorporating geometric nonlinearities leads to a minor increase in the structural response concerning to the translational horizontal displacements and von Mises stresses. Additionally, a parametric study was performed, considering wind loads obtained through several basic wind velocities, with the objective of assessing the dynamic structural behaviour of the steel tower based on the of horizontal displacements, von Mises stresses, and also the fatigue service life. The results revealed that within the operational limit of the turbine, the investigated wind tower complies with the limit states specified in current wind tower design standards. However, for higher basic wind velocities, the steel wind tower structural design no longer meets these requirements.

Assessment of the Human Comfort of Pedestrian Footbridges Utilising Probabilistic Response Spectra

2024-12-02T13:43:40+00:00

Nowadays, the design of pedestrian footbridges is associated to light weight structures with low natural frequencies and low structural damping rates. These facts have generated slender footbridges, sensitive to human dynamic excitations, and consequently changed the serviceability limit states associated to the design. Thus, the current design codes and technical guides recommend the use of deterministic models to assess the dynamic structural behaviour of footbridges. On the other hand, the pedestrian walking is related to a stochastic phenomenon and the dynamic force generated at each step depends of the weight, the step frequency and the step length of each pedestrian. This way, this investigation aims to develop a probabilistic approach to assess the steel and steel-concrete composite footbridges dynamic behaviour, based on the use of design response spectra. To do this, the developed analysis methodology has considered the stochastic nature of the pedestrians walking, in order to evaluating the structural response having in mind excessive vibrations that may cause human discomfort. Based on the use of probabilistic methods, it becomes possible to determine the probability of the footbridges peak acceleration values exceeding or not the human comfort criteria. The results obtained in this research work reveal that the peak acceleration values calculated through the deterministic methods can be overestimated in project situations.

Assessment of the Structural Response of Transmission Lines Steel Towers when Subjected to Nondeterministic Wind Loadings

2024-12-02T14:10:45+00:00

The lattice steel towers have been widely used as supports for power transmission lines. In the current project practise, the structures dynamic behaviour usually is not considered. However, the main loading to consider in structural analysis of these steel towers is produced by wind loadings. Considering that many accidents associated to this kind of structural system occur even for wind velocities below that specified in project, its possible that most of these accidents have been produced by dynamic actions. This way, this investigation proposes an analysis methodology that can accurately simulate the coupled behaviour between the transmission line cables and the towers, when subjected to wind nondeterministic loadings, having in mind the assessment of the displacements and forces maximum values that occur in the steel towers. In this work, the investigated transmission line system, including the steel towers, conductors and shield wire types, presents two spans of 450 m associated to a main suspension tower in the centre with total height of 32.86 and other two towers at the ends. The conclusions of this research work pointed ou to relevant quantitative differences associated to the structural response, when was calculated based on a static linear analysis and compared to the results determined based on a geometric nonlinear and nondeterministic dynamic analysis.

Assessment of the Tall Buildings Dynamic Response Considering the Geometric Nonlinearity and the Aerodynamic Damping

2024-12-02T14:20:07+00:00

This research work aims to evaluate the dynamic structural behaviour of tall buildings when subjected to wind loads considering the effect of the geometric nonlinearity and also the aerodynamic damping, due to the relative movement between the structure and the wind action. This way, the project associated to a steel-concrete composite building with 48 floors and 172.8 m height is investigated, when subjected to wind nondeterministic dynamic actions. The composite building finite element model was developed based on the use of the Finite Element Method (FEM), utilising the ANSYS computational program, and considering the soil-structure interaction effect, aiming to obtain a realistic representation of the dynamic behaviour. The building dynamic response was obtained based on the displacements and accelerations values, determined having in mind a wind velocity range between 5 m/s [18 km/h] and 45 m/s [162 km/h]. The conclusions of this investigation pointed out to the fact that when the geometric nonlinearity effect was considered in the analysis the investigated building dynamic response presented relevant differences, with maximum differences up to 30% to horizontal translational displacements and up to 45% to accelerations. On the other hand, when the aerodynamic damping was considered the contribution was not significant to the structure dynamic response, with maximum differences up to 5% for the displacements and up to 10% for the accelerations.

Comparison between different sets of interpolation functions for Timoshenko frame elements

2024-12-02T18:06:21+00:00

The objective of this paper is to discuss, in the context of a second-order geometric non-linear analysis, the differences in results considering different sets of interpolation functions for frame elements. The usual way to obtain interpolation functions for Timoshenko frame elements is using cubic Hermitian polynomials since they are the solution for the fourth-order differential equation which represents the bending behavior of the infinitesimal element. When dealing with more complex problems (geometrical and/or physical nonlinearities), the usual strategy is to subdivide the elements, which circumvents the limitation of the interpolation functions. Since discretization can sometimes be unwanted, especially for undergraduate students who still do not grasp this concept, a solution which overcomes this is interesting from a didactic point of view. This work proposes the use of different sets of shape functions to interpolate displacements, rotations and bending moments along the elements length, to account for the nonlinearities that arise from the change in geometry during loading. Shape functions obtained directly from the solution of the differential equation of an axially loaded deformed infinitesimal element and traditional Hermitian polynomials are used. Comparisons were made against analytical and numerical solutions using the two-cycle approach. Initial results indicate the ability of the formulation to capture the nonlinear behavior without the need to over discretize the domain.

Contributions to the analysis of prestressed steel and concrete composite beams using machine learning algorithms

2024-12-02T18:09:49+00:00

In the practice of civil construction, one of the structural alternatives used so that beams can withstand the required loads in a more efficient and economical way are the prestressed composite beams, especially steel and reinforced concrete. Posttensioned composite steel-concrete beams (PSCCB) have a greater range of elastic behavior, as well as yield and ultimate load values. In continuous beams, there is a reduction of cracking in the hogging moment region. They may also have better fatigue performance and employ lighter steel sections. The present paper aims to create a large database for the analysis of PSCCB, based on a previously developed nonlinear finite element model, which performs static non-linear analysis of PSCCBs, considering the partial interaction between steel and concrete. With a database developed from a variation of the parameters in the numerical models, three Machine Learning models are developed and trained with the objective of predicting the beam ultimate load, deflection, and final tendon force. The implemented procedures is compared, whenever possible, with experimental and numerical results available in classic literature, mainly as a reference of test data to evaluate the success of Machine Learning algorithms.

Determination of deflection in composite slabs considering concrete creep

2024-12-02T18:19:33+00:00

The analysis of the behavior and resistance of composite steel and concrete slabs covers several parameters. Among these parameters, concrete creep plays an important role in checking deflection. Regarding the calculation of the deflection, generally, technical standards recommend that the moment of inertia of the composite section be given by the simple average of the moments of inertia of the uncracked and cracked sections. However, experimental investigations have shown that this procedure, inadequately characterizes the behavior of the composite slab, resulting in an underestimated effective moment of inertia and smaller deflection, especially when subjected to higher loads. Using research results, this work aims to present a proposal for determining the effective moment of inertia in composite slabs that considers the concrete creep representing the behavior during the loading phase until collapse.

Dynamic Analysis of Plates Subjected to Explosive Loading: Comparison Between SDOF and FEM Models

2024-12-02T18:30:11+00:00

With the global increase in explosive events, arising from armed conflicts and/or accidental occurrences, a thorough analysis of the dynamic behavior of structures under this type of load becomes important. The explosive phenomenon causes an overpressure (positive) wave with a subsequent underpressure (negative) phase, which is often disregarded. Moreover, recent studies have highlighted that this negative phase can generate displacements and stresses as relevant as the ones from the positive phase only. This work investigates simply supported plates subjected to explosive loading considering the membrane effect (laterally immovable condition) which introduces nonlinearities in the model. Due to the problems mathematical complexity, these nonlinear dynamic analyses are usually performed using complicated finite element models. In this way, a software called DYNAblast was developed using a simpler approach based on a Single Degree of Freedom (SDOF) analytical model which incorporates the von Karman plate theory. Dynamic analyses were carried out in DYNAblast to understand the influence of the positive and negative phases of the blast loads, as well as the contribution of the membrane energy of the plate. Numerical models implemented in ABAQUS software were used for the validation of DYNAblast results, with excellent agreement.

Dynamic Structural Analysis of Steel-Concrete Composite Highway Bridges Based on Monte Carlo Simulations

2024-12-02T18:42:08+00:00

The highway bridges are subjected to several random dynamic loadings of different intensities, among which the vehicles traffic is one of the most present. This type of loading generates displacements and stresses amplitudes that vary in intensity along the time, causing stress cycles on the bridge structural elements. When a structural element is subjected to these stress ranges, serious problems related to the fatigue phenomenon can occur. It is well known that an efficient analysis methodology to assess the fatigue service life caused by the road traffic is based on a dynamic analysis considering a coupled vehicle-pavement-bridge system. This way, this research work proposes an analysis methodology based on Monte Carlo simulations aiming to determine the fatigue service life of steel-concrete composite high way bridges. The main characteristics of the bridge and the vehicle are defined as random variables and the vehicle-pavement-bridge dynamic interaction effect is considered. Furthermore, the simulations are carried out considering two levels associated to the pavement degradation. The dynamic response of a typical simply supported steel-concrete composite highway bridge with straight axis and spanning 40 m is investigated. After that, the results calculated through the proposed analysis methodology, considering a large sample of the vehicle-pavement-bridge combinations, make it possible to assess which parameters of the vehicle-pavement-bridge system presented the most relevant influence on the fatigue service life of the investigated highway bridge.

Geometric nonlinear analysis of planar frames constituted of nonprismatic Timoshenko-like elements referred to their noncentroidal axis

2024-12-03T11:23:45+00:00

This paper proposes a geometric nonlinear formulation to solve 2D frames modeled with Timoshenko-like elements defined by their noncentroidal axis. The kinematics of deformation of the element and the cross-sectional constitutive relationships are referenced to any given axis. Thus, the element axes may be any simple straight-line segments intersecting the element's cross-sections at any position. Knowing the element's centroidal axis is of no relevance. As a consequence, the interaction between axial and flexural effects must be consistently taken into consideration. The methodology consists of using a flexibility-type method based on the principle of virtual forces to determine the structural property coefficients. Such a method is convenient for determining the exact solutions of nonprismatic Timoshenko beams because they avoid solving awkward differential equations governing the frame elements. In addition, the exact Timoshenkos shape functions (TSFs) for nonprismatic elements result as a by-product of the formulation. Thus, the exact deformed shape of the element may be determined at any load level in the nonlinear analysis. Polynomials of different orders may be used to interpolate the variable rigidities along the element length. Moreover, we adopt boundary integrals to compute the cross-sectional rigidities along the element, which facilitates the modeling of cross sections of complex shapes. Regular, low-order Gauss-Legendre quadratures are required to evaluate all integrals involved in the analyses. The proposed formulation is validated by comparing our responses with the ones determined by using highly refined 3D ANSYS models. Nonlinear equilibrium paths, stresses, and internal forces are observed in the comparison of results.

Multiobjective Optimization of Steel and Concrete Composite Slabs via NSGA algorithm

2024-12-03T11:30:11+00:00

With the expansion of the civil construction sector, composite steel and concrete slabs with incorporated shapes have become increasingly common due to their ease of execution and the elimination of shoring. However, optimization studies focusing on this type of structural element are still limited. The objective of this study is to propose a formulation for the multi-objective optimization of composite steel and concrete slabs, considering both the phases before and after concrete curing. Objective functions will be established to minimize CO2 emissions and slab costs, as well as to maximize the load-bearing capacity of the slab for a given span. To address this optimization problem, the NSGA algorithm implemented in the Matlab platform will be used. Comparative analyses will be conducted between examples from the literature utilizing single-objective optimization and those employing multi-objective optimization to validate the proposed formulation. Additionally, new problem instances will be examined to identify the key factors that influence the final solution.

Numerical formulation for advanced analysis of semi-rigid steel-concrete composite frames

2024-12-03T11:34:10+00:00

The present work aims at the implementation and validation of a displacement-based two-dimensional numerical formulation including several sources of non-linearities in steel-concrete composite frames, such as second-order effects, plasticity and beam-to-column semi-rigid connections. The co-rotational-based approach is used to describe the finite element formulation, allowing large displacements and rotations in the numerical model. Two rotational pseudo-springs in series are positioned in the finite elements ends. One of them are used to include the gradual loss of stiffness determined by the cross-sectional plastification. The limiting of the uncracked, elastic and plastic regimes is defined in the Normal Force-Bending Moment diagram. In the cross-sectional analysis, the Strain Compatibility Method (SCM) is used to capture the axial strains in the section components. In this way, the constitutive models of the materials are described by continuous functions. The cracked effect is considered by the effective moment of inertia of the concrete cross-section. The other spring include the effects of the semi-rigid beam-to-column connections through the moment-rotation relationship. A multi-linear model for beam-to-column connections is used. To validate the proposed numerical formulation, the results obtained are compared with numerical and experimental data available in the literature. Since the model proposed here starts with the concentrated simulation of nonlinear effects, an examination of the finite element mesh refinement is also carried out. These comparisons indicated for the validation of the numerical procedure proposed and implemented here, highlighting the precision of the formulation in both the pre- and post-critical structures behavior.

Reliability of cold-formed sections with web holes susceptible to failure by web crippling due to concentrated force

2024-12-03T11:39:11+00:00

Cold-formed steel (CFS) are structural elements widely used in the construction industry and, in many situations, holes in the web is a design necessity, because it facilitates the passage of ducts, wiring and piping. This study evaluates the reliability of cold-formed sections with web holes subjected to concentrated force in sections without transverse stiffeners susceptible to web crippling failure. FOSM (Second Moment and First Order Method) and FORM (First Order Reliability Method) methods were used. A database was created with experimental results extracted from the literature, covering the four loading cases (end-one-flange loading EOF, interior-one-flange loading IOF, end-two-flange loading ETF, interior-two-flange loading ITF) presented in the standards used as reference, North American specification AISI S100 (2016), Brazilian standard NBR 14762 (2010) and European code EN1993-1-3 (2006). To obtain statistical data on the professional factor, one of the variables of the reliability problem, experimental results were compared with theoretical ones obtained by norm equations. Only AISI S100 (2016) standard has a criterion for considering web holes by considering a specified reduction factor for EOF and IOF. The results showed that the web holes significantly reduce the resistance of sections when subjected to the EOF loading case, while they reduce to a lesser extent in sections exposed to the IOF loading case. Analyzing the specimens subjected to the IOF loading, the results showed that another condition that influences the resistance is the fixation of the flanges to the supports. Very similar specimens groups reached the target reliability index when connected to the supports during the tests and did not reach when not connected.

Study of the influence of geometric imperfections and residual stresses on the stability of steel columns subjected to axial compression

2024-12-03T11:43:04+00:00

Steel columns are known to provide strength, durability, flexibility, and greater speed of construction. Although being industrially produced under rigorous quality control, steel columns usually present small geometric imperfections and residual stresses that arise during the manufacturing process. These imperfections and residual stresses play a major role on the columns` final compressive strength. Acknowledging the complexities and high cost involved in experimental investigation of these effects, this research was geared towards assessing the influence of the geometric imperfections and residual stresses on the strength of steel columns subjected to axial compression. For this purpose, computational models of I-beam steel columns were developed and analyzed using the Finite Element Method. Initially, a linearized elastic buckling analysis was carried out to determine the critical loads (eigenvalues) and buckling modes (eigenvectors). Following this, nonlinear analyses were conducted considering materially and geometrically nonlinear effects to evaluate the columns strength considering the geometric imperfections with different amplitudes and the shape of the first buckling mode. The elastoplastic model without hardening was adopted to represent the material nonlinearity. Finally, nonlinear analyses were carried out considering different levels of residual stresses for each geometric imperfection amplitude. The results show that the geometric imperfections and residual stresses have a strong influence on the load carrying capacity steel columns leading to a column curve close to the curve adopted by NBR 8800:2008. Therefore, both geometric imperfections and residual stresses should be properly considered in advanced analysis procedures for steel structures.

A hybrid FEM-Kriging approach for fatigue assessment of a steel pipe riser from field-measured motions

2024-12-04T11:10:06+00:00

The establishment of monitoring systems for Floating Production Units motions provides an important input needed for real-time assessment of riser fatigue through Finite Element Method analysis. Standard practice relies on these simulations to obtain the loads required to calculate fatigue life along the riser, however, it is a CPU-intensive approach which makes it difficult to achieve results in real-time. Since interest often lies on few critical points on the riser, such as 1st weld and TDP, the number of outputs of is vastly reduced, making surrogate models an interesting and cost-effective alternative. Previous work such as DAMASCENO (2020) has shown Kriging to be a good choice for time series prediction, yielding adherent results for outputs such as forces and moments by having vessel motions as inputs. This method requires a short FEM simulation (~600 s) to train the models that will expand the output time-series to full 3,600 s duration, which will be shown to be far less CPU intensive. A case study for a SCR connected to a semi-submersible platform is presented, evaluating fatigue life from 5715 hours worth of data from the year of 2018 through both methods. Analysis of the obtained results yields additional tools which correlate damage to vessel motions, which are then used to prioritize sea states and evaluate the most cost-effective FEM and Kriging combination.

An Analytical Frame for Predicting Residual Contact Pressure for Mechanically Lined Pipe using von Mises Criterion and Finite Strain Theory

2024-12-04T11:15:05+00:00

Mechanically Lined Pipe (MLP) is a bi-metallic pipe consists of an external carbon steel pipe internally coated with a thin Corrosion Resistant Alloy (CRA) lining. This CRA layer acts as a barrier against corrosive substance present in the production fluid from offshore Oil & Gas fields, while the high-strength, low-carbon steel outer pipe bears the external loads. Hydroforming expansion stands as the primary method for bonding the liner onto the external carrier pipe. The pursuit of precise and reliable theoretical models is ongoing to improve fabrication efficiency and establish a standard for subsequent failure analysis. The Tresca criterion is traditionally utilized in stress-strain analysis of MLP fabrication due to its mathematical formulation. However, it tends to provide conservative estimations of metallic structure yielding. And comparing the results of theoretical models employing the Tresca yield criterion with the mainstream numerical simulation software relying the von Mises yield criterion poses another difficulty. Hence, its suitability for analyzing MLP fabrication is subject to debate. To enhance accuracy, nonlinear theoretical analysis of MLP incorporating the finite strain theory and the von Mises yield criterion has been performed. Analytical prediction of residual contact pressure is achieved through the circumferential strain compatibility. An axisymmetric Finite Element Model (FEM) is constructed to compare against the theoretical models. Furthermore, the investigation delves into the impact of introducing an appropriate level of carrier pipe plastification on residual contact pressure.

An investigation on the collapse pressure prediction of subsea pipelines with realistic corrosion defects

2024-12-04T11:18:45+00:00

Subsea pipelines are widely used for oil and gas transportation, but they are susceptible to failure due to corrosion. Corrosion in pipelines typically results in defects of varying depths and complex shapes. The computational simulation through the finite element (FE) method is one of the most efficient and accurate tools for assessing the integrity of corroded subsea pipes by allowing the simulation of the nonlinear behavior and assessing the hydrostatic collapse. This paper evaluates the collapse response of subsea pipelines with realistic corrosion defects. The study uses the PIPEFLAW system - developed by the PADMEC (High-Performance Processing on Computational Mechanics) research group from UFPE - which integrates reliable tools for automatic FE model generation and performs nonlinear analyses. After validation based on the experimental tests available in the literature, the effect of realistic corrosion defects on the collapse pressure of subsea pipelines is analyzed in detail. The results are compared to results obtained using a semi-empirical method and numerical results obtained considering idealized FE models, i.e., constant-depth and elliptical-shaped corrosion defects. It is observed that the non-uniformity of defects is an important factor affecting the collapse response of pipes. In addition, the idealized geometry of the corrosion defects, especially when considering constant depth, leads to an excessively conservative prediction of the hydrostatic collapse.

Analysis in Mooring Chain Links Tensioned on Curved Surface

2024-12-04T11:22:30+00:00

The development of offshore energy resources, specifically oil and gas, is increasing. Consequently, there is an increasing demand for state-of-the-art technologies and concepts to enhance productivity in this sector. One critical component of deep and ultra-deep water floating platforms is the mooring system, which requires rigorous design considerations. The motivation behind this lies in the substantial repair costs associated with unexpected failures. Structural failure in anchor chain links is primarily attributed to fatigue damage. While extensive studies have explored this phenomenon, the impact of mooring equipment with curved surfaces responsible for guiding or restricting the upper end of mooring lines on chain link behavior remains somewhat overlooked. In this study, we investigate the effects of ungrooved curved surfaces on the fatigue life of tensioned offshore mooring chain links. Using Finite Element Analysis (FEA), we analyze the behavior of mooring chain links when subjected to tension on curved surfaces. Our findings identify stress hotspots and calculate the corresponding Stress Concentration Factors (SCFs). Notably, the presence of curved surfaces significantly influences stress distribution and fatigue life. Additionally, we explore the effects of varying nominal stress levels applied during assembly and changes in the radius of the curved surface. These results have important implications for the design of mooring systems used in oil and gas exploration and production.

Analysis of Inertial Influence and Damping of Mooring Lines on Fatigue Damage

2024-12-04T11:27:54+00:00

The high demand for oil has driven its exploration into increasingly deeper water depths, which required significant scientific and technological advancements. In this context, the floating production and offshore system is a type of platform, based on ship, anchored by mooring lines arranged by chains/steel cables and polyester cables with the objective to restrict the platforms movements in a design region. Offshore platforms are exposed to environmental loads of waves, wind, and currents, which are responsible for generating hull motions and tension variation in the mooring lines. This tension history, in turn, is directly associated with fatigue failure of the lines. Despite efforts to estimate the fatigue life of mooring lines to ensure their integrity throughout the platforms operation, premature failures in the mooring system have been observed over the past decades. This serves as an alert that the fatigue damage estimated during the design phase may be less than the actual damage occurring in the field. Several factors influence the initial estimation of fatigue life, for instance, the analysis method used to represent the lines behavior, such as quasi-static and dynamic analysis. The first one, that ignore the inertial and damping effects, was widely used in design of mooring lines in the 90s and the beginning of this century due its low computational cost, while the dynamic analysis, that represents rigorously the mooring line dynamic behavior, is used increasingly nowadays. The use of these two different approaches can affect the fatigue damage. Therefore, the present work aims to evaluate the influence of the inertia and damping of moorings in the fatigue damage, comparing the quasi-static and dynamic approaches studied with a floating unit numerical model, with 910m water depth, that uses a conventional catenary mooring system. In this way, a critical analysis is carried out based on the comparison between the fatigue life resulting from the two forms of analysis.

Artificial Neural Networks for Optimization procedures of Mooring System of Floating Platforms

2024-12-04T11:31:46+00:00

Floating production systems (FPS) are widely used for oil exploitation by offshore industry. Installation of these systems have been advanced to deep and ultra-deep water subject to both extreme and operational environmental conditions. Under these conditions, mooring systems assume a fundamental role of keeping the FPS on the location and thus ensuring the integrity of other systems. Numerical model of these systems requires rigorous nonlinear static and dynamic analysis in the time domain using Finite Element Method (FEM) which have high computational costs. Therefore, an optimization process that may requires hundreds or thousands of analyses of the candidate solutions can take a long time. Thus, this work aims to optimize a mooring system of a floating production system, changing the evaluation of the objective function and the associated constraints from Finite Element Procedure by an Artificial Neural Network, in order to reduce the computational costs. Such reduction of time consuming may favor the accomplishment of several studies of the system in question. Case study presents a real-world scenario and the optimization tool employs the Particle Swarm Optimization (PSO) method. From the results we can see that the replacement of the FEM analyses by ANN meta-model has a high level of accuracy and presents low computational cost.

Assessing the feasibility of suspended BOP transportation and its impact on fatigue life

2024-12-04T11:35:30+00:00

The sailing of the drilling rig along with its subsea equipment, such as, the drilling riser and the blowout preventer (BOP), from one well to another using traditional methods is a time-consuming operation. Typically, this process involves lowering and retrieving the BOP after drilling, followed by moving the rig to another well to be drilled, and again lowering the BOP and subsequently retrieving it. This method becomes even more time-consuming in ultra-deep waters, where recent oil field discoveries have taken place, as the deeper the water depths, the more time is required for such operations. Considering the high costs associated with renting and operating drilling rigs, operators are looking for ways to make these processes more efficient. One promising alternative is the method of navigation with the BOP suspended at a certain distance from the seabed, eliminating the need to retrieve the entire drilling riser and BOP, resulting in significant optimization of the process of transferring the drilling rig and its subsea equipment between wells.
During the navigation of the BOP, hydrodynamic and inertial forces are exerted on the suspended riser column and the subsea BOP. In this present work, analyses of fatigue resulting from the effects of waves and vortex-induced vibration resulting from current speed and navigation, will be conducted for different lengths of the riser column. The results of these analyses will be presented, and the software used to obtain these results will be Orcaflex and Shear7.

Comparison of Soil Modeling Strategies with Springs in Free-Span Submarine Pipelines

2024-12-04T11:38:41+00:00

The fatigue life of submarine pipelines is significantly influenced by structural parameters and environmental conditions to which they are exposed. Numerous studies have focused on modeling this issue using the Finite Element Method to determine frequencies and natural modes of vibration. The models consist of pipeline sections, with some segments in free spans and others supported by soils that can be represented by contact surfaces or sets of springs constituting an elastic foundation. This work aims to evaluate different strategies for representing soil stiffness using springs in a finite element model. Additionally, we investigate the incorporation of the solution for a semi-infinite beam on an elastic foundation to calculate the stiffness of the modeled endpoints. We analyze different element lengths in a free-spanning pipeline model to quantify the influence of various approaches on frequencies and natural modes of vibration. Therefore, this work emphasizes the relevance of parametric studies in modeling submarine pipelines, with particular emphasis on accounting for soil stiffness.

Cost-Optimized Mooring Systems integrating Load Reduction Device for 15 MW FOWT

2024-12-04T11:41:58+00:00

The wind energy sector is shifting towards larger turbines to reduce energy costs, posing challenges for installations in shallow and intermediate waters (60-150 meters) that require smaller platforms and mooring systems. Previous research utilized a multi-objective optimization (MO) framework, employing tools like NSGA2 and OpenFast with MoorDyn, to design systems compatible with synthetic lines. Incorporating load reduction devices (LDRs) in mooring systems offers significant benefits by reducing loads on anchors and mooring lines, allowing for smaller, lighter anchors, and mitigating fatigue damage. LDRs, such as ballasted pendulums, polymer springs, and hydraulic dampers, feature unique non-linear stiffness curves crucial for performance. This study advances the MO framework by assessing a mooring system with spring polymer LDRs and conducting a sensitivity analysis of key design variables using the design of experiments (DOE) approach. It integrates the Pymoo optimization library with industrial software like OrcaFlex and OrcaWave, promoting broader industry adoption. The findings indicate significant reductions in mooring system costs, particularly for smaller mooring radii, and a 22% decrease in computational costs with fewer design variables, enhancing the mooring design process for any floating platform in any water depth.

Coupled in-line and cross-flow vortex-induced vibration responses of a fluid-conveying riser with variable tension in shear flow

2024-12-04T12:14:54+00:00

When seawater streams around risers, it causes vortex-induced vibrations (VIV), which occur in two forms: in-line (IL) and cross-flow (CF). Accurate prediction of coupled IL and CF VIV behaviors is essential for designing risers. To investigate the VIV of marine risers used in deep-sea oil and gas transportation, this study analyzed the coupled CF and IL VIV characteristics of the riser with axially time-varying tension under the combined effects of internal flow and oceanic linear shear flow. The work established the vibration control equation for the riser considering internal flow velocity, axial top tension, and bending stiffness, which is based on Euler-Bernoulli beam theory. The double Van der Pol diffusion wake oscillator model was used to simulate the vortex-induced forces from the ocean currents, and the internal fluid was considered as a single-phase incompressible liquid. Using the Generalized Integral Transform Technique (GITT), the coupled system of nonlinear partial differential equations was further transformed into a system of nonlinear ordinary differential equations for numerical solution. A parametric study was conducted to analyze the impact of current velocity, internal flow velocity, and diffusion term on the VIV responses, including structural displacement, structural frequency, displacement envelope, and displacement evolution. Numerical results indicate that the vibration modes of the riser are influenced by both CF and IL directions, and the effect of IL can not be ignored. The diffusion term has a significant impact on the vibrations of the riser. The number of vibration modes of the riser is mainly influenced by the increasing current velocity, and for a given current velocity, the vibration of the riser becomes chaotic when the dimensionless internal fluid velocity increased within a certain range.

Design of mooring systems for offshore structures through an optimization approach

2024-12-04T12:19:42+00:00

The design of mooring systems for offshore structures is crucial for ensuring the safe and efficient operation of floating production systems (FPS) within the oil and gas industry. This activity is renowned for its demanding resource requirements, in terms of technical challenges, design criteria, computational cost and extensive hours of work from highly skilled professionals. In this context, structural optimization emerges as a potential solution to mitigate the use of some of these resources, introducing a design approach reliant on optimization algorithms capable of translating technical criteria into mathematical functions and proposing valid and optimized solutions. However, this optimization approach presents its own set of challenges, notably the need of evaluating thousands of structural models, which directly depend on time-consuming numerical simulations. This work aims to treat the optimization challenges by proposing strategies to expedite the computation of numerical models and to support the designing professional in determining optimized designs suitable for direct industrial application.

Dynamic Analysis of Fixed Offshore Structures for Wind Turbines

2024-12-04T12:25:30+00:00

Offshore wind power presents itself as an alternative for complementing and diversifying the Brazilian energy matrix. In this context, fixed jacket-type platforms, widely used by the oil industry, are alternatives for supporting offshore wind turbine towers. However, the unique characteristics of these structures, such as their large dimensions, high centers of mass, and eccentricities of assemblies, as well as the random nature of the loads acting simultaneously on the structure, such as ocean waves, winds, and currents, are challenging components for the engineering of structures built in the marine environment. This article presents some of the main computational models for dynamic structural analysis of fixed offshore wind turbines. In the applied methodology, the sea state is modeled based on second-order Stokes wave theory, where fluid kinematics are calculated from the analysis of random waves in the frequency domain, using the Pierson-Moskowitz spectrum. The aeroelastic-dynamic forces and interactions acting above the free surface were simplified through the adoption of values prescribed in the literature. Finally, structural analysis is carried out using the finite element method, with the jacket bars modeled using plane frame elements. The results obtained in terms of dynamic properties, as well as structural responses, were compared with those extracted from recent works, thus confirming the validity of the chosen methods and consolidating the results for the development of future work.

Influence of velocity on conductor casing driving via Material Point Method

2024-12-04T12:30:20+00:00

The conductor is the first casing settled in an oil well and it has important functions regarding the initial phase of well construction. Some of its functions are to bear loads from the wellhead, bear the surface casing during its cementation, and insulate unconsolidated formations. The soil response to the conductor settlement is an important factor, for a poor settlement may cause excessive wear on the wellhead equipment or even the loss of the well. Therefore, a simulation of the self-weight phase of a conductor driving was conducted to enhance knowledge about the soils state during this process. The soil was modeled as soft clay, and the mechanical behavior was described by the Mohr-Coulomb model. As the conductor driving results in large displacements in a short period, the traditional Finite Element Method (FEM) is unable to model this system. Therefore, the Material Point Method (MPM), which is a modification of FEM, was used to model the conductor-soil system. Three conductor velocities were simulated and the resultant force in the casing outer surface was analyzed. The soils stress state, displacement, and velocities were studied.

Modeling Operational Parameters to Support Evaluation of Subsea-to-Shore Production System Implementation

2024-12-04T12:36:18+00:00

The subsea-to-shore system represents an alternative approach to traditional offshore oil production, emphasizing environmental improvements by reducing carbon emissions through alternative energy sources like hydroelectric power. This system incorporates an onshore processing unit, eliminating the need for a Stationary Production Unit (SPU), thereby reducing costs, offshore personnel exposure, and its associated occupational risks. Additionally, terrestrial processing units offer greater flexibility for expansion and installation of new modules compared to SPUs, which are constrained by limited space. This paper aims to establish critical parameter limits essential for implementing the subsea-to-shore system based on a representative production field. Key parameters include distance to the coastline and various export pipeline diameters suitable for specific water depths, ensuring optimal operational performance. These studies utilized multiphase flow simulation software, leveraging data approximations from Norway's Ormen Lange Field, one of the largest gas fields, as a foundational basis. Results derived from the applied model and variables provide preliminary insights into the feasibility of implementing such systems, prompting further discussion within the scientific community regarding advancements in oil and gas production systems.

Monetary risk analysis of operating corroded offshore pipelines

2024-12-04T12:39:34+00:00

The offshore oil and gas exploration activity involves a high degree of complexity, being characterized by high extraction costs and long distance to the coastline, turning the use of pipeline essential to guarantee the flow of production. However, one of the main mechanisms of pipeline degradation is corrosion, which results in compromising the integrity of the structure. Therefore, risk analysis is necessary to avoid the consequences of pipeline failure, which could lead to environmental and human tragedies. The objective of this study is to quantify and analyze the risks of operating corroded offshore pipelines, assisting in the decision-making process. To this end, it is important to predict the mechanical behavior of the pipe, to reduce the probability of failure and ensure continuity of operations. A case of study is carried out and presented to verify the operating condition of a corroded pipeline, using semi-empirical methods, finite elements and new methods, obtaining effective answers to assist pipeline operators in decision making.

On the collapse propagation of thick-walled dented submarine pipelines

2024-12-04T12:42:58+00:00

Subsea pipelines are susceptible to structural instabilities. Particularly in deep waters, where pressures are very high, collapse is the most critical instability and can be rapidly propagated, damaging kilometers of the pipeline, with catastrophic impacts. In addition to high pressures, any damage that may occur due to impact, excessive bending, corrosion, and other causes during pipeline transport, installation and operation, can dramatically reduce the collapse and propagation pressure of the structure. Static buckling of pipelines under external pressure is a well-established subject in the literature and classical theories such as Timoshenko's provide reasonable estimates of the buckling threshold under some conditions. The accuracy of these predictions is particularly good for long, thin tubes, but when it comes to damaged thick-walled pipelines, there is a gap of knowledge and a lack of information regarding the post-buckling behavior of such pipes. Thus, this work aims to present a comprehensive study on the collapse propagation of thick-walled dented submarine pipelines based on experimental analysis, numerical models and a parametric study in order to cover several scenarios of interest.

Probabilistic Approach for Lateral Buckling Analysis in Virtual Anchor Spacing (VAS) Models of Rigid Flowlines Subjected to High Pressures and High Temperatures (HP/HT)

2024-12-04T12:45:49+00:00

This study deals with the main topics related to the phenomenon of thermomechanical buckling of rigid flowlines laid on the seabed. It focuses on the latest versions of DNV-ST-F101 [1] and DNV-RP-F110 [2]. Additionally, the study presents a probabilistic approach for lateral buckling analyses in Virtual Anchor Spacing (VAS) of rigid flowlines exposed on the seabed, subjected to High Pressures and High Temperatures (HP/HT) in deep-water environments. The methodology includes determining the probability curves of the parameters with the greatest influence on the analysis: Pipe-Soil Interaction (PSI), friction between the pipe and sleeper (buckling mitigator), and geometric imperfections (lateral out-of-straightness). This is followed by a Design of Experiment (DoE) analysis to create a matrix composed of a representative set of load cases to be simulated using the Finite Element Method (FEM). These simulations are performed using Abaqus to obtain the probability distributions of the effective Critical Buckling Force (CBF) and Post-Buckling Force (PBF). The tolerable VAS is determined through FEM analyses applied to a dedicated load case matrix to identify the most critical failure criteria. The results are post-processed to generate response surfaces and failure probabilities for each of these criteria using the Monte Carlo Method. Finally, a case study is performed to illustrate the probabilistic approach, which requires more simulation time than a deterministic method but offers more detailed probability ranges for lateral buckling responses, potentially reducing a project's overall cost. It can be used to assess the reliability of lateral buckling responses during the detailed design phase of subsea pipelines susceptible to lateral buckling.

Reliability Analysis of the Collapse of Corroded Submarine Pipelines Subjected to Bending Moment

2024-12-04T12:48:48+00:00

With the increasing development of oil exploration in the oceans, the demand for submarine pipelines has risen considerably, which implies significant environmental risks in the event of structural failure, resulting in oil leaks and consequent billion-dollar environmental damage. The integrity of these structures is primarily compromised by external pressures and bending moments, especially in areas of high curvature between platforms and extraction points. These bending moments, as identified in the investigations of Bjørset (2000), decrease the pipelines resistance to collapse due to the progressive ovalization of the sections, reducing the moment of inertia. Additionally, corrosion defects, which decrease the thickness of the pipeline walls, are prevalent and significantly impact the resistance to collapse, requiring precise evaluation in simulations (CABRAL, 2007). For the modeling of this mechanical phenomenon, the Finite Element Method (FEM) has shown promising results, being chosen to calculate the collapse pressures by combining the effects of bending moments and corrosion defects (MOTTA, 2020). However, the simulation process faces challenges due to uncertainties associated with measurement errors, equipment calibration, and manufacturing faults. These uncertainties are generally overlooked in traditional deterministic methods but can be addressed through reliability analyses that use statistical concepts to establish failure functions and assess failure probability, resulting in a more robust and reliable analysis (MOTTA, 2020). These analyses are rarely discussed in the existing literature, suggesting a need for more well-founded and detailed approaches. The results of this study, with the application of reliability techniques, are expected to provide safer insights into the influence of bending moments on the resistance of submarine pipelines. Furthermore, it is intended to compare deterministic equations with simulation results, proposing, if possible, adjustments to these equations to optimize the accuracy of the provided results.

Stability analysis of a seabed under combined action of waves and seismic loading

2024-12-04T12:51:34+00:00

The stability analysis of a seabed under wave and seismic loading is conducted within the framework of yield design theory using the pseudo-static method. The strength properties of the constitutive material are modeled by means of a purely cohesive condition. The loading associated with water waves is modeled through the linear wave theory, whereas the inertial forces induced by the passage of seismic waves is addressed in the framework of pseudo-static method. The material cohesion that increases linearly with dept is adopted in the analysis. A sufficient stability condition is obtained through the static approach of limit analysis, while a necessary condition is determined from the kinematic approach. The effects of seafloor surface inclination, as well as seismic intensity, are analyzed through pseudo-static coefficients. The determination of the limit load obtained through the pseudo-static approach is based on existing literature, particularly when seismic coefficients are not considered.

Three-dimensional finite element analysis of vortex-induced vibrations in deepwater steel catenary risers with large deformation

2024-12-04T12:53:55+00:00

Vortex-induced vibration (VIV) is an important phenomenon in fluid-structure interaction and one of the main challenges faced by slender offshore structures. Under the influence of ocean currents, long steel catenary risers (SCR) may exhibit nonlinear VIV dynamic response with various modes and frequencies, which occur simultaneously in three-dimensional space. These nonlinear dynamic response can lead to critical bending and longitudinal stresses, ultimately resulting in significant fatigue damage to offshore risers over time. This paper presents a large-deformation three-dimensional dynamic model for the SCR, which accounts for VIV and actual ocean loads, offering significant advantages over traditional small deformation beam or catenary theories. The model thoroughly considered the bending stiffness of the riser and the nonlinear effects of large deflections on the loads. It uses two Van der Pol wake oscillator equations to model the fluid dynamic impact of vortex shedding in both crossflow (CF) and in-line (IL) directions. Moreover, the model addresses the pipeline-soil interaction at the touchdown zone (TDZ). Employing the finite element method (FEM), each node was endowed with six degrees of freedom, enabling descriptions of vibrations in lateral, axial, and torsional directions for the riser. The structural dynamics and wake oscillator equations were solved using the Newmark-β and Runge-Kutta methods, respectively. The numerical model has been validated with published results and further simulations have been conducted to determine the dynamic behavior of the SCR. Subsequent comprehensive parameter analysis examined the effects of motion amplitude, current flow loads and the touchdown zone on the three-dimensional VIV responses of the SCR, which are crucial for understanding the dynamic behavior of the riser.

Transport Studies of the Innovative Vertical Buoy Supported Risers System

2024-12-04T12:57:59+00:00

The current expansion of offshore oil and gas exploration in increasingly deeper water depths leads to an option of utilization of hybrid riser systems. These systems are characterized by the combination of flexible jumpers and Steel Catenary Risers (SCRs), interconnected by a floating submerged structure. Among the offered types of hybrid riser systems, one of them employs a Buoy Supported Risers (BSR) as an intermediate element between the flexible jumpers and the SCRs. Although the hybrid riser system utilizing the BSR manages the advantages associated with both types of risers, providing a very effective ultradeep waters riser system, the use of the BSR entails high costs, complexity, and considerable risk during the transportation and installation stages of the buoy. In this way, new alternatives regarding the use of hybrid risers are welcome. In this context, this work presents the innovative proposal of a Vertical Buoy Supported Risers (VBSR) that may offer greater viability when compared to the traditional horizontal concepts, resulting in benefits for hybrid riser systems and, consequently, for oil and gas exploration activities in deepwater environments. The benefits of vertical configuration of the BSR, in relation to the conventional horizontal one, are more focused on transport and installation risks reduction, although also presents vantages in operational phase. In this work, the presented study is focused on the transport stage of the VBSR. Therefore, an evaluation of the VBSRs static and dynamic responses during transportation in intact and damage scenario are presented here.

A positional FEM approach for free vibrations of orthotropic laminated shells

2024-12-16T20:14:32+00:00

This paper presents a positional formulation of the Finite Element Method (FEM) for free vibration analysis of laminated shells with cross-ply and angle-ply fibers. The starting point of this formulation is the use of positions and generalized vectors as degrees of freedom, i.e., three coordinates and three vector components per node in the 3D space. The formulation is more general than Reissner-Mindlin by introducing an additional parameter which allows linear deformation in the three directions, avoiding locking effects. The material layers are orthotropic according to the Saint-Venant Kirchhoff law, in which the constitutive tensor regarding the shell reference axes is obtained with a second-order tensor transformation matrix. The numerical solution uses Hammer quadrature on the shell reference surface and Gauss-Legendre to integrate along the thickness, while the free vibration problem is solved as a standard eigenvalue and eigenvector problem. Two examples are discussed. The results are compared with papers in the open literature, which demonstrates good accuracy and efficiency of the present formulation.

Evaluating Design Methods for Cellular Steel Beams Through Parametric Modelling

2024-12-16T20:17:14+00:00

Under some design conditions, cellular beams can be a better structural solution than I-section beams due to their enhanced strength-to-weight ratio, allowing for more lightweight and cost-effective constructions. However, their varying cross-sections lead to additional failure mechanisms, which require further research due to the lack of specific standardized design procedures covering this topic in Brazil. This paper evaluates five different design methods, as proposed by Annex N (1998), Veríssimo et al. (2013), Fares et al. (2016) and Grilo et al. (2018). Using a parametric approach, this paper investigates the geometric variations in cellular beams with the mentioned design methods, in comparison to shell finite element models already validated in a previous work of Benincá and Morsch (2020). The results reveal that while the design methods are generally conservative for longer spans, they might underperform in terms of safety for shorter spans. The Ward (1990) method was the most effective in identifying failure modes based on Formation of Vierendeel Mechanism (FMV) and Web-Post Buckling (WPB). In contrast, the adaptation of the Veríssimo et al. (2013) method, combined with the WPB check from the Grilo et al. (2018) method, was more sensitive in evaluating the WPB failure load. Finally, the findings confirm that cellular beams offer more significant benefits when used across longer spans.

Finite element analysis of steel shear frames with composite reinforced concrete infill walls and welded bolts as shear connectors

2024-12-16T20:19:52+00:00

In the composite walls stiffness system of reinforced concrete walls with composite boundary members, boundary members resist most of the moment due to seismic loading. In contrast, the reinforced concrete (RC) wall provides shear resistance. The SRCW system comprises partially restrained steel frames with reinforced concrete infill walls. The steel columns and beams act as boundary members to resist gravity loads and most of the overturning moment due to seismic loading, while the reinforced concrete (RC) infill wall acts as shear-resisting web. The RC infills increase the lateral stiffness dramatically compared to a bare steel frame, thus avoiding excessive drift and reducing the seismic demands on the steel frames. In that way, why not use just steel shear frames instead of partially restrained steel frames with reinforced concrete infill walls?
This paper presents a numerical study of the behavior of a composite structural system consisting of steel shear frames with reinforced concrete infill walls (SFRCW). The composite interaction is achieved using welded bolts as shear connectors along the steel frameinfill interfaces. Welded bolts were used as shear connectors because they are frequently used in Colombia due to their ease of installation.
The SFRCW system may be particularly appropriate for low-to-moderate-height structures. In addition, the steel shear frame will support gravity loads at the construction stage, allowing progress in height. The system can also be used to strengthen existing steel buildings. The relatively light steel frame constructed using shear connections maximizes the system's economy.
This study compared the behavior of the SFRCW with columns acting in their weak and strong axes and with different numbers of shear connectors. It also compared the behavior of the bare steel moment frame, bare steel shear frame, and reinforced concrete wall. The numerical models show interesting results.

Nonlinear finite element analysis of steel-concrete composite beams with cellular I-section under hogging moment

2024-12-17T12:27:41+00:00

Adopting hybrid cellular I-sections can favor optimizing steel consumption, as the higher steel grade is localized only in the compression tee. In addition, continuous steel-concrete composite cellular beams allow the construction of longer spans due to the combination of higher bending stiffness of the cellular I-section and its connection with the concrete slab, further the continuous of the beam, which provides a better distribution of the bending moment diagram. However, due to the hogging moment on the support regions, the steel-concrete composite beam can present lateral instability of the compression flange accompanied by web distortion, named Lateral-Distortional

Buckling (LDB). No investigations have evaluated the behavior of steel-concrete composite beams with hybrid cellular I-section under hogging moment. This way, the present study aims to assess the behavior of the structure in question using a nonlinear finite element model via ABAQUS software. The investigation consists of verifying the beams' failure mode, considering plastic behavior or LDB, and the effects
of different combinations of steel grades for the hybrid I-section, and further comparing the use of hybrid and homogeneous steel profiles on the composite beams.

Study of the behavior and resistance of the U shear connector consisting of cold formed profile

2024-12-17T12:32:39+00:00

The use of composite beams leads to economical solutions for use in building and bridge structures, for example, due to the combined action between the steel beam and the concrete slab, providing greater stiffness and flexural resistance than when considering the work isolated from materials. However, as they are two materials with different behaviors, mechanical devices are needed that are capable of ensuring that their elements work together. Such devices are called shear connectors, whose function is to resist the horizontal forces that develop at the steel-concrete interface, avoiding the physical separation of these components and ensuring their joint action. The U shear connector made up of a cold-formed profile is a low-cost alternative connector, however, more studies to understand its mechanical behavior need to be developed. The analysis of the mechanical behavior of a shear connector is carried out by carrying out the push-out test, standardized by Eurocode-4 (2004). Another possibility is the use of numerical modeling. Numerous researchers have used numerical modeling to study the behavior of shear connectors and obtained satisfactory results. The numerical model, which must be calibrated and validated by the experimental model, presents as its main advantage the possibility of carrying out a parametric variation for the analysis of the connector without the need to spend time and materials, that is, numerous parameters can be varied in the test, such as thickness of the connector profile or its properties, among other test parameters, only with the computational cost involved, which proves to be advantageous when compared with the experimental cost related to the push-out test. In this sense, this work aims to numerically simulate the mechanical behavior of U-shaped shear connectors consisting of a cold-formed profile. The developed numerical model will be calibrated and validated, and applied for a parametric analysis to evaluate the connector resistance, where the thickness and length of the connector, in addition to the concrete resistance, will be the main parameters studied.

The influence of high-strength steel on the failure modes of steel-concrete composite cellular beams

2024-12-17T12:35:36+00:00

The use of steel-concrete composite cellular beams expands the options in civil construction projects, as it results in greater strength capacity when compared to components acting separately, as well as greater steel savings when compared to full-span beams. In this respect, it is interesting to study the influence of high-strength steel on the failure modes and strength capacity of composite cellular beams. Therefore, this study aims to contribute to the study of composite cellular beams under positive moment, with the replacement of ordinary steel by high-strength steel, identifying the influence of this parameter on their failure modes and on the strength capacity of the composite cellular beam. In this way, using ABAQUS software, a numerical model was developed and validated using experimental results from the literature, to obtain the original behavior and then parametric analysis focused on replacing ordinary steel with high-strength steel. The study resulted in four numerically validated cellular composite beam models and three variations of each, modifying the yield strength of the steel and realizing that, as expected, the strength capacity of the beam increased considerably.

The use of normative models under combined compression and bending for verification of concrete-filled steel tubes with high strength materials

2024-12-17T12:42:36+00:00

Buildings have been demanding increasingly slender pillars from projects, consequently increasing the demand for efficient and economical solutions. One of the solutions adopted is the use of high-strength concrete and steel and the optimization of sections for filled mixed tubular pillars, which has been widespread in European, American, and Asian countries; however, there is little application in Brazil's constructions. Verification of mixed pillars under flexo-compression can be done by simplified methods or analytical methods such as the method of deformation compatibility. The draft revision of ABNT NBR 8800:2023 introduces three simplified calculation models for flexo-compression verification, with limitations in its application for concrete with characteristic compression strength below 50 MPa and steel profile with yield strength below 450 MPa, as well as proposing polygonal lines to trace interaction curves. In this article, the simplified calculation models from the draft revision of ABNT NBR 8800:2023 are compared with experimental results from the literature of prototypes of circular tubular filled mixed pillar sections with concrete strength above 50 MPa and steel profile with yield strength above 450 MPa. For this purpose, a computational tool was developed in MATLAB that traces the interaction curves of the draft revision project of ABNT NBR 8800:2023. The suitability and conservatism of simplified methods were verified when using high-strength materials outside the normative range.

A micromechanical approach for homogenization of elastic multiphase periodic composites

2024-12-03T12:38:21+00:00

This work presents a micromechanical model for the linear elastic homogenization of composites with periodic microstructures. The model is constructed for composites with an arbitrary number of phases and geometric shapes of the inclusions, differently from the most homogenization approaches available in the literature. In addition, no restriction is made with respect to the mismatch between the properties of the constituent phases and volume fractions of the inclusions. The model formulation is based on the Eshelby equivalent inclusion method and corresponds to an extension of a procedure originally derived to evaluate the effective elastic moduli of periodic composites with only two constituent phases. The fluctuating elastic fields within of the repeating unit cell (RUC) are represented by Fourier series, resulting in Lippmann-Schwinger integral equations involving the unknown eigenstrain fields of the inclusions. These integral equations are solved by using a straightforward approach that employs a scheme of partition of the domain of each inclusion. Applications to composites with different arrays of coated fibers and constituent materials are presented to show the efficiency of the model.

A proposal for a unified high-order quasi-3D kinematic model coupled with zigzag function to model laminated composite beams

2024-12-03T13:06:06+00:00

Laminated composite materials have become increasingly prevalent in various engineering applications due to their remarkable stiffness/mass ratio and ease of manufacture. However, the classical theory fails to address certain limitations in modeling laminated composite beams, such as the absence of shear stress at the top and bottom edges, the non-uniform distribution of the shear stress field, and the zigzag effect in the field axial displacement. This study presents a newly proposed unified high-order quasi-3D kinematic model, which is coupled with a novel zigzag function to overcome the limitations encountered when it uses classical beam theory. This approach eliminates the need for correction factors required in Timoshenko beam theory and accurately captures the cross-section warping and transverse normal deformation resulting from the incorporated quasi-3D effect. Finally, the results were validated by comparing the displacement fields, normal stresses, transverse normal stress, and shear stress with reference values in the literature.

Analytical formulae for the higher-order effective coefficients of periodic laminated elastic composites with imperfect contact

2024-12-03T13:10:47+00:00

Analytical formulae are derived for the effective coefficients of linear elastic second-order laminate composite materials made of any finite number of linear elastic first-order layers. Imperfect contact conditions are considered at the interfaces, and small strains are assumed at the micro and macro scales. The micro-macro homogenization procedure used here is reported in Continuum Mech. Thermodyn. (2020) 32:1251-1270 wherein only numerical studies are presented. Asymptotic homogenization method results at the micro-scale level are combined with the macro-scale parameters based on the equivalence of the stored energies on the periodic cell (i.e., the energy-averaging theorem known as the Hill-Mandel condition). Some comparisons are considered for validation. To the best of our knowledge, the fully analytical application of this methodology to the case of laminate media has not been reported previously, that is, with the analytical solution of the local problems. The formulas obtained could be useful to control numerical codes in more complex periodic cells.

Projects PAPIIT DGAPA UNAM IN101822, Mexico, and CNPq Universal Nº 402857/2021-6, Brazil, are gratefully acknowledged. CAPES Brazil Program (PRAPG) Edital No 14/2023 is also recognized.

Asymptotic Homogenization Method with fictitious multilayers applied to the mesoscale characterization of concrete beams

2024-12-03T13:15:26+00:00

The escalating complexity of engineering challenges necessitates the utilization of increasingly efficient materials, often met through the adoption of composite materials as a viable solution. Concrete stands out as one of the most prevalent composite materials in civil engineering, evolving through alterations in its constituent components as researchers pursue enhanced durability, workability, and sustainability. However, traditional theories treating concrete as a homogenous isotropic material prove inadequate for predicting the mechanical properties of these innovative concretes, primarily due to the excessive costs associated with experimental analyses. Consequently, this study introduces a high-order zig-zag multilayer theory incorporating the asymptotic homogenization method. The variational formulation of a unified beam kinematics was used to carry out a multiscale analysis through the asymptotic expansion of the unknown variables. This methodology facilitates the transformation of a beam composed of heterogeneous materials into an equivalent homogeneous. The findings of the formulation proposed agree with established numerical and experimental formulations documented in the literature, even when employing a one-dimensional beam theory.

Asymptotic homogenization of a mechanical equilibrium problem of a functionally-graded Euler-Bernoulli beam with non-periodic microstructure

2024-12-03T13:20:07+00:00

To the best of our knowledge, the few classical applications of Keller's two-space method of non-periodic asymptotic homogenization are related to the effective behavior of heterogeneous media in the context of poroelasticity considering fluid flow and saturation. We believe that this is due to the alternative common approach of approximating random or non-periodic microstructures via the periodic replication of a representative volume element, as periodic structures are, generally speaking, much more tractable mathematically and computationally. However, more than 40 years later, a number of preliminary results of applications of the two-space method has arisen on various areas, namely, effective behavior of composite or functionally-graded bars, approximate solution of the electroencephalogram forward problem for neural imaging activity, and modeling of atmospheric pollutant dispersion. These recent applications deal with second-order elliptic or parabolic equations. In this contribution, we present the application of the two-space method to a mechanical equilibrium problem of a functionally-graded Euler-Bernoulli beam with non-periodic microstructure, which relies on a fourth-order elliptic equation. To the best of our knowledge, homogenization of fourth-order equations has been considered only in the periodic case.

Asymptotic homogenization of energy-limited nonlinear microperiodic composites with imperfect interfaces to model failure of masonry structures under uniaxial compression

2024-12-03T13:23:51+00:00

In this work, a masonry prismatic structure made of alternating layers of mortar and bricks is modeled as a periodic two-phase elastic composite with one-dimensional heterogeneity along the layering direction. The prediction of its mechanical behavior (failure mainly) is important to estimate the allowable stress and stiffness used in the masonry design. At the mortar-brick interfaces, both ideally perfect contact and spring-type imperfect contact are considered. In order to model both classical and failure behaviors simultaneously, a nonlinear constitutive relation, which results from limiting the classical Hookean energy by inserting it into the so-called softening hyperelasticity energy representation, is adopted. The model is a two-point boundary value problem, which is stated by subjecting the resulting mechanical equilibrium nonlinear differential equation to the contact conditions at the interfaces and the mixed boundary conditions corresponding to uniaxial compression in the layering direction. The masonry structure exhibits separation of scales, as its size is generally much greater than the size of the mortar-brick periodicity cell, so its mechanical properties are rapidly oscillating, and also the equivalent homogeneity is guaranteed, justifying the application of the asymptotic homogenization method. Here, the effective law, that is, the constitutive relation of the equivalent homogeneous structure, is obtained via the asymptotic homogenization method. Finally, comparisons with experimental results from the literature are provided, which show qualitative agreement and that the model with imperfect contact is more accurate than the one with perfect contact.

Asymptotic homogenization, domain decomposition and finite elements combined for calculating effective elastic properties of periodic fiber-reinforced composites with imperfect interfaces

2024-12-03T13:27:17+00:00

A methodology is presented for calculating the effective elastic properties of periodic multi-phase composites made of an anisotropic linear elastic matrix reinforced with a periodical distribution of unidirectional fibers and exhibiting spring-type imperfect contacts at the interfaces. The periodicity cell contains any finite number of parallel fibers and exhibits arbitrary cross-section. Fibers also exhibit arbitrary cross-sections and are made of a different anisotropic linear elastic material each. The methodology uses asymptotic homogenization (AH) to obtain the mathematical expressions of the effective properties and to formulate the so-called local problems on the periodicity cell on whose solutions the effective properties depend on. In order to deal with the discontinuities arising from the spring-type interfaces, the local problems are then restated via domain decomposition (DD) in a way allowing for an iterative resolution scheme in which the solution of the problem to be solve in each iteration is obtained via finite elements (FE). Results in the examples are obtained via a computational implementation of the methodology based on the FreeFEM open-source software, which allows for the variational formulation of the iteration problem to be dealt with directly.

Computational homogenization of masonry using the finite-volume direct averaging micromechanics theory

2024-12-03T13:31:07+00:00

This paper presents a study focused on determining effective elastic properties of masonry made up of bricks and mortar joints arranged in periodic arrays. The brick and mortar are treated as linear elastic materials, with a bond pattern consisting of stacked bond and running bond. The overall effective elastic moduli are evaluated by a computational unit cell-based micromechanical procedure. The formulation employs a discretization of the masonry unit cell which is examined using the finite-volume direct averaging micromechanics theory (FVDAM). The homogenization approaches are carried out considering plane stress (PS) and generalized plane strain (GPS) states, as well as a tridimensional version of the FVDAM theory (3D-FVDAM). The results provided by these three conditions of analysis (PS, GPS, 3D-FVDAM) are compared in order to verify their limitations and applicability in the elastic homogenization of periodic masonry with different geometric features.

Elastostatic analysis using the boundary element method and the Aifantis gradient elasticity theory

2024-12-03T13:33:44+00:00

The increasing use of micro and nano-scale structures has sparked interest in theories incorporating the effect of scale since the classical continuum theory has limitations in capturing effects that depend on size. Therefore, three-dimensional elastostatic microstructure modeling is carried out in this work using the boundary element method (BEM).To account for microstructural effects, the simplified gradient theory proposed by Aifantis, a particularization of Mindlin's general theory, was employed. A variational argument was established to determine the governing equations and boundary conditions for the problem. This argument explains the fundamental solution of gradient elasticity, and the integral contour representation is constructed with the aid of the reciprocal identity. Curved triangular elements of Proriol spectral functions were used to approximate the geometry and the physical parameters for the discretization of the BEM. The presented formulation yielded results consistent with other analyses in the literature.

Mechanical Characterization of Natural Fiber Ropes

2024-12-03T13:38:15+00:00

In this work the mechanical characterization of natural fiber rope is studied. For this, the festuca dolichophylla fibers are used to manufacture ropes, which are used to build a 28m span historical hanging bridge, with ancient Inka technology called Qeswachaka at the district of Quehue, department of Cusco in Peru.
Twenty-four tests were performed on samples made by various diameters, varying from 30mm up to 130mm, in order to quantify its material constants using the hyperelastic theory, specifically the Neo-Hookean and MooneyRivlin models as well as fitting a polynomic curve. The findings showed that the initial part of the strength-strain curve fit very close to hyperelastic material behavior and can be applied to future modelling of real structures.

Modifying the refined zigzag theory to incorporate functional gradation into the bending analysis of laminated beams

2024-12-03T13:43:24+00:00

Extensive research has been conducted in the field of composite materials, particularly in laminated composites. However, laminated composites often face challenges such as stress concentration at interfaces due to the sharp differences in properties between layers. This study proposes an approach to mitigate stress concentrations in laminated composites using functionally graded materials (FGM). FGM is achieved by gradually varying properties across the thickness of each beam layer, employing the power law in conjunction with the rule of mixtures. The modeling is based on the refined zigzag theory (RZT), with an additional introduction of the sublayers to capture the functional gradient. The analysis involves deriving the zigzag function for FGM, which is referred to as modified RZT. Subsequently, the kinematic model is applied based on the principle of minimum total energy to derive the Euler equation and its associated boundary conditions. For analytical resolution, the Navier procedure is employed. The results obtained for displacement and tension fields are compared with other formulations from the literature, demonstrating alignment and validation of the proposed method.

Static Mechanical Analysis of Nanobeams Reinforced with Graphene Nanoplatelets Using Modified Couple Stress Theory

2024-12-03T13:47:45+00:00

Composite materials are fundamental in contemporary engineering, standing out for their ability to combine different raw materials to create new materials with superior properties. Graphene, characterized by its flat two-dimensional (2D) carbon monolayer structure with a thickness of 0.34 nm, has aroused considerable interest due to its remarkable mechanical, thermal, and electrical properties. In particular, graphene derivatives, such as graphene nanoplatelets (GNP) and carbon nanotubes (CNT), have been widely explored as reinforcements in composites. Compared to CNT, GNP offers a more economical alternative and a greater surface area, available in various sizes, from nanometers to micrometers. Micro- and nanoscale composites serve as models for assessing material performance in multiple industries, such as automobiles, aviation, medicine, and construction, especially in cases where experimental methods are costly. Modeling and simulation techniques are employed to mitigate the costs associated with experimentation, from quantum mechanics to continuum mechanics. This work proposes a variational formulation to model the static mechanical behavior of nanobeams reinforced with graphene nanoplatelets. The micromechanical constitutive model modified Couple Stress, coupled with high-order beam kinematics, is developed to obtain the governing equations and their boundary conditions. The Navier procedure is utilized to develop an analytical solution to the problem. The results are compared with the literature, and the proposed model is proven accurate.

Topology Optimization of Periodic Cellular Materials through the Progressive Directional Selection Method and Finite-Volume Theory

2024-12-03T13:54:11+00:00

This investigation presents the Progressive Directional Selection (PDS) method to optimize the topology of periodic cellular materials, achieving high performance and minimal weight. The homogenized elastic properties of cellular materials are determined using the homogenization method applied to periodic materials based on the unit cell concept as an intermediate step of the topology optimization procedure. The literature often constructs the design domain to conduct a finite element analysis. However, some problems are related to numerical issues, such as the checkerboard pattern and mesh dependence. The checkerboard effect is related to the assumptions of the finite element method, as the satisfaction of equilibrium and continuity conditions at the element nodes, particularly for linear triangular and quadrilateral discretizations in the absence of regularization schemes. This problem can be overcome by the Finite-Volume Theory (FVT), which satisfies the equilibrium equations at the subvolume level, and the compatibility conditions are established through the adjacent subvolume interfaces. The PDS method is inspired by natural selection processes found in biology and employs a strategy to meet the objective function of a discretized analyzed domain subject to a volume constraint. Population selection is based on performance criteria specific to the problem through an iterative process that concludes when the optimized topology ceases to evolve. Numerical examples of topology optimization for materials with periodic cellular microstructures are analyzed using PDS and FVT.

A low-cost space-time finite element for free-surface flows under total Lagrangian description

2024-12-11T12:27:07+00:00

In this work, we propose a position-based space-time finite element formulation for incompressible Newtonian flows under a total Lagrangian description. This formulation is suggested within the context of finite strain free-surface flows and differs from the traditional finite element approach for fluid dynamics by utilizing current nodal positions as the main variables instead of nodal velocities. In contrast to time-marching methods, space-time formulations involve applying the finite element technique not only to the spatial domain but also to the temporal domain. The proposed approach employs a finite element discretization that can be unstructured or structured in space, but is always structured in time. Thus, the space-time shape functions are expressed as a tensor product of linear shape functions in the spatial direction and specially designed quadratic shape functions in the temporal direction. Consequently, the space-time domain is divided into time slabs that are solved progressively, with the final velocities and positions from the previous time slab serving as initial conditions for the current one, thereby reducing the dimension of the discrete system of equations. The proposed shape functions in the temporal direction yield a system of equations of the same size as standard time-marching methods, but with advantages stemming from the space-time discretization: different stability and high-frequency dissipation can be achieved based on the selection of the time test functions. To solve the incompressible problem stably, we employ mixed equal-order position-pressure finite elements with Petrov-Galerkin/pressure stabilization (PSPG). This formulation possesses several significant features that justify its development: 1) the space-time formulation facilitates dynamic re-meshing by permitting the spatial discretization at the end of one time slab to differ entirely from the spatial discretization at its beginning, thus extending its applicability to flows with undefined distortion and topological changes; 2) by considering positions as variational parameters, it becomes straightforward to couple with Lagrangian hyper-elastic solid solvers, which may also be formulated in terms of positions or displacements in a monolithic way. Numerical examples conducted to validate the formulation demonstrate its robustness and efficiency for finite strain free surface flows, including phenomena such as dam breaks with smooth surfaces and sloshing.

A NURBS-based isogeometric formulation for geometrically nonlinear analysis of shells

2024-12-11T12:31:36+00:00

Due to their high slenderness, shell structures are vulnerable to collapse caused by loss of stability, hence nonlinear analysis is crucial to ensure a safe design. The advantage of isogeometric analysis (IGA) to exactly describe the geometry of the problem independently of the degree of discretization and allow easy refinements has led to its increasing application in shell analysis. However, IGA does not remove the shear and membrane locking presented by fully integrated shell elements based on Reissner-Mindlin's theory. Thus, several alternatives have been proposed in the literature to solve the locking problem, such as mixed formulation and reduced integration. This work aims to study the effectiveness of different reduced integration schemes to eliminate or alleviate locking in the context of stability and geometrically nonlinear analysis of Reissner-Mindlin shells based on the degenerated solid approach. The proposed formulation is applied to the stability analysis of plates and shells, where critical loads and nonlinear equilibrium paths are evaluated and compared to solutions available in the literature or obtained by the Finite Element Method. Excellent results were obtained, demonstrating that a very accurate and efficient approach for nonlinear analysis of plates and shells can be achieved by using high regularity basis functions obtained by k-refinement and an appropriate reduced integration scheme. This approach not only avoids locking but also reduces the computational cost of nonlinear analysis of shells.

Airfoil lift finite element computations using H1 (Ω) and H(div,Ω) approximation spaces

2024-12-11T12:35:12+00:00

Computing the lift generated by an airfoil is crucial in aircraft design, especially for aircraft performance prediction, aircraft stability/control, and optimization of airfoil shape for improving efficiency. The problem of incompressible flow around an airfoil is studied herein as a weakly irrotational flow, resulting a div-curl problem in a 2D double-connected domain. The original div-curl problem is ill-posed because it is defined over a multiply-connected domain. Traditionally, a cut in the original domain and additional constrain for the velocity potential and velocity potential gradient at the cut are required for the numerical solution, which applies a rotational correction method based on Helmholtz decomposition of vector fields. The lift coefficient can be finally computed from the numerical solution of the problem. In the present work, the lift of an airfoil is computed from finite element solutions using different approximation spaces: The conventional H1 (Ω) potential-field space and a special class of H(div,Ω) velocity-field space, i.e., the divergence-free space. Accurate analysis using both approximations is performed with h-refinement strategies. The lift coefficient computed from the analysis is compared against available reference solutions. The computational performance and accuracy of the lift computation using the two different approaches are discussed. Finally, the difference in the velocity solution obtained using H1 (Ω) and H(div,Ω) spaces is presented, which can be interpreted as a new posteriori error estimator for the problem.

Analysis of crack propagation due to fatigue using the Stable Generalized Finite Element Method (SGFEM)

2024-12-11T12:39:21+00:00

This work aims to present a combination of the stable generalized finite element method (SGFEM) and of the displacement correlation method (DCM) for analyzing 2D crack propagation problems due to fatigue. The SGFEM allows to model fracture mechanics problems without excessive refinement and/or concern of the mesh-to-crack alignment. Additionally, this method maintains the numerical conditioning under control. The DCM, in turn, is computationally very efficient when compared to traditional energy based methods (like J integral) and herein is even improved by means of a linear least square extrapolation. The maximum circumferential tension criterion and well-known propagation laws available in literature are adopted for considering the crack propagation. Experimental and numerical benchmark examples are proposed and the obtained results are compared against results provided by a commercial software widely adopted in the aeronautics industry.

Ck-Generalized FEM with enhanced consistency: application to the static linear elastic rod deformation problem

2024-12-11T12:41:53+00:00

The Ck-Generalized Finite Element Method (Ck-GFEM) in its original version considers Partition of Unity (PoU) functions defined as Shepard ones, which delivers zeroth order consistency in the absence of uniform polynomial extrinsic enrichment of degree one, at least. Such a feature can make Ck-GFEM unfavorable against the conventional G/XFEM when comparing the degrees-of-freedom (dof) amount for a certain error level. This inconvenience can be overcome through intrinsic enrichment using the Moving Least Squares Method (MLSM), which allows the construction of PoU functions with enhanced polynomial reproducibility despite the cost of demanding the widening of the associated supports. In this context, the present work summarizes some results for the static rod deformation problem, for the linear elasticity, considering different classes of PoU functions and different extrinsic enrichment functions, through an approach that adjusts the k-order of continuity and the p-polynomial degree of the ansatz independently, for some kinds of loads distributions which leads to different classes of solutions.

Non-intrusive implementation of the Generalized Finite Element Method with Global-Local Enrichment for multi-domain analysis

2024-12-11T12:44:12+00:00

This work proposes a non-intrusive implementation of the Generalized Finite Element Method with Global-Local enrichment (GFEMgl-IGL) for multi-domain analysis. In GFEMgl-IGL, the global problem is initially discretized with a coarse mesh and without considering localized phenomena. The solution of this domain is obtained through the standard formulation of the Finite Element Method, using the commercial software Abaqus in this work. Following, mesoscales, as many as necessary, are defined as intermediate problems between the global and local domains (where localized phenomena of interest, such as cracks, are effectively represented). The global-local enrichment of the GFEMgl determines the association of each mesoscale with the respective local problem. The coupling of mesoscales with the global problem is established through the transfer of displacements and generalized forces, defining the non-intrusive strategy denominated Iterative Global-Local (IGL). Numerical simulations via GFEMgl are executed in the computational system INSANE (INteractive Structural ANalysis Enviroment - www.insane.dees.ufmg.br). The combination of solvers indicated in the solution methodology focuses on endorsing the application of algorithms developed in the academy as instruments with the capacity to solve complex models utilizing commercial software. This work proposes the expansion of the implementation of the non-intrusive strategy in INSANE, enabling the consideration of multiple local domains. A numerical example is presented to show the simulation's performance and to investigate the influence of the main parameters related to the proposed strategy.

Shell Analysis Using a Solid-Shell Approach

2024-12-11T12:47:50+00:00

Shells are curved three-dimensional structures whose thickness is much smaller than their other two dimensions. They can be found in various sectors, such as aerospace, energy, naval and civil engineering. There are several structural theories in the literature to deal with this type of structure, such as Kirchhoff-Love, Reissner-Mindlin and Higher-order theories. However, these theories are based on assumptions that require rotational degrees of freedom in their kinematic description, making the problem complex, especially for geometrically nonlinear analysis, since large 3D rotations are not additive. Furthermore, in shell theories, it is usually assumed that there is no thickness stretching. In other words, the normal transversal strain is neglected, so it is not possible to use full 3D constitutive models for the analysis. With this in mind, the structural modeling in this work will be based on the solid-shell approach, which uses a 3D mesh with only one element through the thickness and does not require rotational degrees of freedom in the kinematic description, like in solid elements, but with a lower computational cost. Its formulation considers the general stress state, so a complete 3D constitutive relation is assumed. The use of this theory in structural problems results in partial differential equations whose analytical solutions are very complex or impossible to obtain, thus requiring the use of numerical methods to obtain approximate results. The presented formulation can be applied to develop isoparametric and isogeometric solid-shell elements. The performance of linear and quadratic elements is assessed using numerical examples.

Virtual Element Method: An overview of formulations

2024-12-11T12:50:43+00:00

The virtual element method has been around for about a decade, and it has been through a lot of development during this period. The method generalizes the finite element method for polytopal elements, while retaining optimal convergence properties. This is achieved mainly by implicitly defined function spaces and the use of polynomial projections. This work presents an overview of the development of the method as formulated for elliptic problems in two and three dimensions, here represented by Poissons equations. The formulations covered are: its original formulation, the modified formulation enabling three-dimensional elements, the Serendipity formulation, and one of the formulations for self-stabilized elements.

Analytical Models for Railway Track Structural Analysis Based on Numerical and Experimental Data

2024-12-16T11:26:32+00:00

Since the 19th century, mechanistic models based on the theory of elasticity have been developed to structurally analyze the permanent way. In this context, the Winkler model considers the rail as a beam infinitely supported on an elastic base, from which the analytical solutions derived presented in this research were compared with numerical and experimental results, from operational data recorded in the Carajás Railway. The software Matlab and SAP 2000 were used to develop the analytical and numerical models, respectively. The comparison considered the loading scenarios for a wheel, with the bogie and the coupling region between wagons, and evaluating the influence of the superposition of effects. The results obtained in both the analytical and numerical models proved to be reliable in the real structural representation of the permanent way.

Determination of stresses in welded connections of railway bridges with the finite element method and global-local approach

2024-12-16T11:31:01+00:00

Steel bridges are used due to their large spans with reduced self-weight, and therefore, are widely used for expanding the Brazilian railway network. However, due to the cyclic loading acting on the structure, and their limited damping capacity, the dynamic effects must be evaluated. In addition, due to the cyclic loading, the effects of fatigue must be considered. In bridges, fatigue failures account for most of the damage and collapse of structures. Thus, techniques are proposed for assessing their service life, considering fatigue failure effects. Fatigue life assessment can be performed considering the history of stresses acting on the structure, and obtaining stress history data using the finite element method yields more accurate results compared to normative methods, but it requires an extremely refined mesh to obtain adequate stress values. Therefore, this study presents a strategy for obtaining stress histories with the passage of a vehicle on a railway bridge using the commercial software Ansys Mechanical APDL v. 2020R1 and Python routines to assess the fatigue life of connections. A global-local methodology is proposed, in which a model of a bridge span using shell and beam elements is developed and subjected to the passage of a vehicle. Its displacement results are then transferred to a local connection model developed with solid elements, to determine stresses for future use in assessment of fatigue life.

Influence of the train speed in the performance of a ballastless track in a transition zone

2024-12-16T11:49:49+00:00

The ballastless track is the most popular railway system nowadays. This is due to the associated reduced maintenance costs and operations. Indeed, in recent years there has been a shift from the ballasted track to the ballastless track, mostly in Asia, but also in Europe. Considering both railway structures, their performance in transition zones is a major concern of the Railway Infrastructure Managers. These areas are characterized by an abrupt change in the track stiffness, which leads to the development of differential settlements and the growth of dips and bumps, accelerating the degradation of the track. Thus, it is crucial to have a methodology able to accurately predict the performance of the ballastless tracks in transition zones, mostly in the scope of high-speed lines. This work presents a detailed analysis regarding the evaluation of the performance of a ballastless track in an embankment-tunnel transition zone considering the influence of the train speed. In this analysis six different train speeds were adopted: 220 km/h, 360 km/h, 500 km/h, and 600 km/h. Moreover, the influence of the critical speed is also evaluated. The adopted and developed methodology is a novel and hybrid approach that allows including short-term and long-term performance, through the development of a powerful 3D model combined with the implementation of a calibrated empirical permanent deformation model.

Vibrations induced by railway traffic: from environmental impact assessment to exploration in new railway projects

2024-12-16T11:53:39+00:00

Prediction and control of ground-borne vibrations are one of the largest environmental challenges for railway exploration in urban areas. Nowadays, there is a shift at global level, in which investment in rail transport takes precedence over other transportation options, in a final attempt to drastically reduce CO2 emission. The expansion and improvement of the railway network, associated with the high standards of comfort required by modern societies, requires the assessment and mitigation of the environmental impact induced by the implementation of such infrastructures in nearby buildings, more specifically in their inhabitants and in the operation of sensitive equipment. Using a recently completed railway line in Porto, Portugal, as a case study, this paper aims to provide insights into the numerical studies conducted during the environmental impact assessment phase concerning vibrations induced by railway traffic. Additionally, it discusses the results from the experimental measurement campaign carried out after the line's construction to validate the assumptions made during the design phase regarding expected vibration levels.