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

Time-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.