Stochastic analysis and reliability assessment of critical RC structural components considering material properties uncertainty

Abstract

The unavoidable heterogeneity in the mechanical characteristics of concrete is widely acknowledged. Although it is widely considered as either perfectly correlated or entirely independent random variables in engineering practice; however, such treatment is illogical, and the outcomes may be deceptive. In high-rise buildings comprised of multiple structural components, it is crucial to consider the material properties’ spatial variability (MPSV) to obtain a reliable structural response and avoid damage to these structures. To this end, three main components, including column, rectangular shear wall, and U-shaped shear wall, are considered herein to investigate their stochastic response. The MPSV is represented by a covariance matrix decomposition-based random field generator combined with a GF-discrepancy-based point selection strategy to generate samples efficiently. A simplified strategy is developed to represent the random field for the U-shaped wall. Moreover, the probability density evolution method combined with the extreme value event is employed to obtain the failure probability of the studied components, where failure probabilities of 18%, 23%, and 32% are recorded for the studied RC column, rectangular shear wall, and U-shaped shear wall, respectively. Furthermore, different failure modes were identified and could not be determined through the deterministic analysis, highlighting the importance of accounting for material uncertainty. The proposed framework proved that the stochastic response and non-linear behavior of the considered components could be well captured and provide full perspective about the uncertainty quantification and reliability assessment and can be further implemented to capture the stochastic response and safety assessment of high-rise buildings.