A hybrid Kriging-based reliability method for small failure probabilities

Weidong Chen, Chunlong Xu, Yaqin Shi, Jingxin Ma and Shengzhuo Lu

Reliability Engineering and System Safety, 2019, vol. 189, issue C, 31-41

Abstract: The main goal of structural reliability is to determine the failure probability of a structure by considering the randomness of the inputs. When the failure probability is small, the simulation methods may have high computational costs, especially for complicated and time-consuming numerical models. In this paper, a modified algorithm based on Monte Carlo simulations and the Kriging metamodel (AK-MCS) is proposed. The strategy is to replace the initial population with two or more populations. The next best point is identified by the iterative approach based on a point not in the original populations. There are enough candidate points near the performance function, which is important for refining the Kriging model. The modification can deal with multiple failure regions that are characterized by complex, high non-linear limit states. Five examples are provided to illustrate the efficiency of methodology. With reference to five case studies in the literature, satisfactory results and efficiency are obtained by the proposed algorithm.

Keywords: Metamodel; Active Kriging; Importance sampling; Monte Carlo simulations; small failure probabilities (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (13)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:189:y:2019:i:c:p:31-41

DOI: 10.1016/j.ress.2019.04.003

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