An efficient method for estimating time‐dependent failure possibility by combining adaptive Kriging with adaptive truncated fuzzy simulation

Abstract

AbstractTime‐dependent failure possibility (TDFP) can measure the structural safety level for a time interval of interest under fuzzy uncertainty, but its calculational cost is unaffordable by using fuzzy simulation (FS) due to a required large size of FS candidate sampling pool (CSP). Although time‐dependent adaptive Kriging model (T‐AK) combined with FS (T‐AK‐FS) was presented to reduce the number of calling performance function, a large FS CSP still makes training T‐AK time‐consuming. To improve its efficiency, an adaptive truncated FS (ATFS) with T‐AK (T‐AK‐ATFS) is proposed by CSP size reduction approach. By T‐AK‐ATFS, the largest safety hypercube in fuzzy standard space is adaptively searched, in which the samples are in safety states and can be removed from the FS CSP. Moreover, T‐AK is adaptively trained to search the largest safety hypercube and estimate TDFP simultaneously. In adaptively searching process, the FS CSP is divided into several sub‐CSPs, on which training T‐AK is more time‐saving. Overall, strategies of T‐AK‐ATFS include proposing ATFS to reduce the FS CSP, adaptively searching the largest safety hypercube, estimating the TDFP with the same T‐AK and training T‐AK in the sub‐CSPs sequentially. Verified by examples, these strategies make T‐AK‐ATFS more efficient than existing FS and T‐AK‐FS.