A Single-Loop Fuzzy Simulation-Based Adaptive Kriging Method for Estimating Time-Dependent Failure Possibility

Abstract

To improve the efficiency of the double-loop fuzzy simulation (DLFS) for estimating the time-dependent failure possibility (TDFP), a single-loop fuzzy simulation (SLFS) is proposed in this paper. In the SLFS, an equivalent transformation formula of TDFP is put forward for the first time, then the estimation of TDFP is transformed into a single-loop fuzzy simulation procedure where the fuzzy inputs and time parameter are sampled in the same level. As only single-loop sampling is needed in the SLFS, the computational complexity and cost of the proposed method are both reduced compared to the DLFS. Subsequently, a single-loop Kriging model based SLFS (ASLK-SLFS) is developed to enhance the performance of the SLFS. Based on the candidate sampling pool of SLFS to sample the fuzzy inputs and the time parameter in the same level, a single Kriging can be more efficiently constructed and updated. To further improve the efficiency of ASLK-SLFS, an improved version is then developed by using a candidate sampling pool reduction strategy. Finally, three examples are employed to illustrate the advantages of the proposed methods. Through the proposed ASLK-SLFS, the safety degree of the time-dependent structure with fuzzy uncertainty can be efficiently evaluated.