A Kriging-assisted sampling method for reliability analysis of structures with hybrid uncertainties

Mi Xiao, Jinhao Zhang and Liang Gao

Reliability Engineering and System Safety, 2021, vol. 210, issue C

Abstract: In this paper, subset simulation importance sampling (SSIS) method is extended for reliability analysis of structures with mixed random and interval variables. To improve its efficiency in cases with computationally expensive performance functions, an efficient Kriging-assisted SSIS method is proposed. In this method, Kriging metamodel is employed to substitute the actual performance function to decrease the number of its evaluations. Furthermore, it is determined that only the samples in the last level of SSIS are involved in the calculation of failure probability bounds. Then, from these samples, an update strategy based on measuring the possibility of correctly predicting the sign of performance function is developed to obtain update points, which are employed in the sequential refinement of Kriging metamodel. Additionally, metamodel uncertainty of Kriging is quantified and then considered in the termination criteria of Kriging update. The computational efficiency, accuracy and robustness of the proposed method is elucidated by its comparison with some existing methods in implementing the reliability analysis of six examples.

Keywords: Subset simulation importance sampling; Kriging metamodel; Hybrid uncertainties (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:210:y:2021:i:c:s0951832021001071

DOI: 10.1016/j.ress.2021.107552

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