A single-loop Kriging coupled with subset simulation for time-dependent reliability analysis

Dapeng Wang, Haobo Qiu, Liang Gao and Chen Jiang

Reliability Engineering and System Safety, 2021, vol. 216, issue C

Abstract: Time-dependent reliability analysis (TRA) plays an important role in improving the validity and practicability of product reliability evaluation over an interested life interval. Conventional TRA for high-reliability product, however, requires tackling two main challenges: (1) the inaccurate analysis of small failure probability problem and (2) the computationally expensive time-variant performance function. In this paper, a single-loop Kriging coupled with subset simulation (SLK-co-SS) method is proposed to address these challenges. By introducing time-dependent intermediate failure events, the estimation of small failure probability is first converted into a product of larger condition probabilities, which can be estimated by a proposed most probable extreme value method based on the trained Kriging model. We then develop an improved maximum error-guided adaptive sampling strategy to sequentially train and update the Kriging model in every intermediate failure event. To make more training samples located at the high potential region of time-dependent limit state surface, the error-tolerance threshold of updating stopping criterion varies with the intermediate failure events. The comparison results on four examples demonstrate the good capability and applicability of proposed SLK-co-SS method.

Keywords: Time-dependent reliability analysis; Active learning Kriging; Subset simulation; Most probable extreme response; Estimation error of small failure probability (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (14)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:216:y:2021:i:c:s0951832021004476

DOI: 10.1016/j.ress.2021.107931

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