Probabilistic Performance Assessment of Recycled Concrete Blocks Using Compressive Rheometry

Resumo

According to the Brazilian Association of Public Cleaning and Special Waste Companies (2024), the Northeast region of Brazil stands out as one of the country's leading producers of construction and demolition waste (CDW). Using this waste as recycled aggregate offers the potential for sustainable disposal while generating new materials for the construction sector. Accordingly, the Brazilian standard NBR 15116 (2021) establishes the basic requirements for using these aggregates in cementitious materials. In this context, Brazilian standards for concrete blocks consider compressive strength a key factor in structural design. Therefore, it is important to take into account the uncertainties inherent to the block production process. To this end, a probabilistic analysis is proposed, based on the parameters of test specimens, totaling 96 samples. Data were collected on dry density, height, and compressive strength. The samples encompass different compositions – in terms of both natural and recycled aggregates (coarse and fine), as well as moisture content ranging from 6% to 12%. The specimens are produced using the compressive rheometry technique, which simulates the behavior of dry concrete used in block manufacturing, reproducing the compressive deformation conditions characteristic of the vibropress process. A calibrated experimental parameter (α) is proposed to correlate the compressive strengths of the test specimens with those of the blocks, enabling a structural reliability analysis using the First-Order Reliability Method (FORM) and Monte Carlo simulation. The study aims to contribute to the discussion on the variability of block performance compared to the strength values established by standards. Furthermore, it will be possible to identify the random variables that most significantly influence the probabilistic response of the problem.Based on experimental measurements and tests, data were obtained for the statistical characterization of dry density, height, and compressive strength. A reliability analysis was then conducted to evaluate the probabilistic performance of blocks under compression, using the First-Order Reliability Method (FORM) and Monte Carlo simulation.