Structural reliability analysis using the dp-rs-sim method

Abstract eng:
Classical reliability methods such as First- and Second-Order Reliability Methods (FORM and SORM) have been real breakthroughs toward feasible and reliable methods for integrating probabilistic information and uncertainty analysis into advanced design methods and modern design codes. Nevertheless, caution should be used in their applications since limits and shortcomings in terms of applicability and accuracy are known and documented, e.g., (1) existence of multiple design points (DPs), (2) nonlinearity of the limit-state surface (LSS) due to non-Gaussianess of the input process for random vibration problems, (3) nonlinearity of the LSS due to nonlinearity in the system. Current research trends highlight the importance of structural reliability analysis methodologies able to provide improved failure probability estimates without excessive increase in computational cost compared to ordinary FORM/SORM analyses. The newly developed Design Point – Response Surface – Simulation (DP-RS-Sim) method can be used for both time-invariant and time-variant structural reliability analysis. The DP-RS-Sim method combines in an innovative way the DP search used in FORM/SORM analyses with the Response Surface (RS) method and appropriate simulation techniques. In this paper, two application examples illustrate the DP-RS-Sim method: (1) a time-invariant reliability analysis of a reinforced concrete frame structure subjected to horizontal pushover loads, and (2) a time-variant reliability analysis of a single-degree-of-freedom inelastic system with force-displacement response characterized by the Menegotto-Pinto constitutive model. DP-RS-Sim-based estimations of the probability of limit-state exceedance by the benchmark structures are compared with FORM, SORM, crude Monte Carlo and Importance Sampling results in terms of accuracy and computational cost. It is shown that the DP-RS-Sim method can provide significantly more accurate failure probability estimates compared to other classical structural reliability methods.

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