An efficient method for solving system failure probability functions based on subset simulation and probability reanalysis techniques

Hao Wang, Luyi Li, Junchao Liu and Xiukai Yuan

Reliability Engineering and System Safety, 2025, vol. 262, issue C

Abstract: Estimating the system failure probability function (FPF) is critical in reliability-based system design and optimization. However, multiple failure modes in a system challenge the estimation process. The probability reanalysis (PRA) method can estimate failure probabilities under various distribution parameters using only a single set of input-output samples. However, combining it with efficient numerical simulation methods can improve its computational efficiency. This paper combines the importance sampling subset simulation (SS-IS) method with the PRA method to propose the SS-IS-PRA method for estimating the system FPF. The proposed method transforms the system FPF into a product of a series of conditional FPFs. Then, a single set of input-output samples is used to solve conditional FPFs layer by layer based on the PRA approach. Furthermore, this paper introduces an IS center selection strategy based on mixed sampling and K-means clustering to enhance the applicability of the SS-IS-PRA method in multi-failure mode problems without additional computational cost. Finally, an adaptive Kriging surrogate model is embedded within the SS-IS-PRA method to enhance the computational efficiency of SS-IS-PRA and better suit real engineering structure analysis. Hence, the SS-IS-PRA-AK method is obtained. The effectiveness and efficiency of the proposed method are validated through four examples.

Keywords: Reliability analysis; System failure probability function; Probability reanalysis; Subset simulation; K-means; Adaptive Kriging model (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:262:y:2025:i:c:s0951832025004491

DOI: 10.1016/j.ress.2025.111248

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