Aircraft Structures Life-cycle Simulation through Digital Twins and Model Updating Techniques

Resumo

Numerical modeling tools have become essential in the realm of aircraft structural design and assess-
ment. These tools allow for the analysis of intricate structural parts, incorporating diverse material properties and

loading scenarios while minimizing the need for extensive experimental testing. However, the current models face
limitations in accurately capturing the nuanced real-world behavior of aircraft structures. Challenges arise due
to factors such as material property scatter, manufacturing-induced geometric deviations and residual stress, and
other effects that can only be estimated or fully captured during service.
This work aims to evaluate and discuss the potential impact of digital twins on addressing these limitations

and enhancing the reliability of numerical models through model updating techniques. Digital twins, virtual repli-
cas of physical assets or systems, can improve the solutions to overcome the gaps between numerical models and

real-world behavior. By integrating and processing data from sensors, operational inputs and historical data, digital
twins provide a more comprehensive understanding of the structural behavior throughout an aircraft’s life cycle.

With the exploitation of machine learning techniques, new methods for model calibration and validation are possi-
ble, combining experimental inputs with simulation models. By leveraging these techniques, digital twins can be

continuously updated and refined, allowing for more accurate predictions of structural behavior and performance.
These models can enable real-time monitoring and more precise damage assessment, supporting the decision
making in diverse contexts. In addition, integrating sensor data and model updating techniques, digital twins
have the potential to improve the design and maintenance operations. They can provide valuable insights into the
structural health, safety, and reliability of aircraft structures, leading to more efficient and safer operations.