Improved Sequential Optimization and Reliability Assessment for Reliability-Based Design Optimization

Abstract

The sequential optimization and reliability assessment (SORA), which is a decoupled reliability-based design optimization (RBDO) method, is generally more efficient than conventional double-loop RBDO methods but less efficient than single-loop approaches because of the most probable point (MPP) search in the reliability assessment loop of SORA. This study presents improved SORA (ISORA) which is a single-loop version of SORA to further improve its efficiency. Simplified reliability assessment is performed at each iteration instead of the reliability assessment loop of SORA. The optimum with higher reliability than the deterministic optimum is searched by moving the limit state function toward the safe region utilizing a design shift vector in SORA which is approximated using the concept of the mean value method in ISORA. ISORA is divided into ISORAx and ISORAu in this study, according to the space used to define the approximated design shift vector. ISORAu is more effective than ISORAx because it does not need to approximate MPP and design point whereas ISORAx needs to approximate them for non-normal random variables. Numerical study shows that ISORAu is the most effective among RBDO methods tested in this study in terms of efficiency, accuracy and robustness.