Efficient reliability analysis coupling importance sampling using adaptive subset simulation and PGD model reduction

• Published in: Proceedings in applied mathematics and mechanics Vol. 19; no. 1
• Main Authors: Robens-Radermacher, Annika, Unger, Jörg F.
• Format: Journal Article
• Language: English
• Published: Berlin WILEY‐VCH Verlag 01.11.2019
• ISSN: 1617-7061; 1617-7061
• DOI: 10.1002/pamm.201900169

One of the most important goals in civil engineering is to guaranty the safety of constructions. National standards prescribe a required failure probability in the order of 10−6 (e.g. DIN EN 199:2010‐12). The estimation of these failure probabilities is the key point of structural reliability analysis. Generally, it is not possible to compute the failure probability analytically. Therefore, simulation‐based methods as well as methods based on surrogate modeling or response surface methods have been developed. Nevertheless, these methods still require a few thousand evaluations of the structure, usually with finite element (FE) simulations, making reliability analysis computationally expensive for relevant applications. The aim of this contribution is to increase the efficiency of structural reliability analysis by using the advantages of model reduction techniques. Model reduction is a popular concept to decrease the computational effort of complex numerical simulations while maintaining a reasonable accuracy. Coupling a reduced model with an efficient variance reducing sampling algorithm significantly reduces the computational cost of the reliability analysis without a relevant loss of accuracy.