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- Title
AOK‐ES: Adaptive optimized Kriging combining efficient sampling for structural reliability analysis.
- Authors
Huang, Ying; Zhang, Jianguo; Wang, Bowei; Song, Lukai; Gong, Qi; Wei, Yanxu
- Abstract
The pivotal problem in reliability analysis is how to use as few actual assessments as possible to obtain an accurate failure probability. Although adaptive Kriging provides a viable method to address this problem, unsatisfied Kriging surrogate accuracy and reliability modeling samples often lead to an unacceptable computing burden. In this paper, an adaptive optimized Kriging combining efficient sampling (AOK‐ES) is proposed: first, to enhance the Kriging approximation ability, a high‐fidelity optimized Kriging model (OKM) is established; further, to ensure the samples quality of OKM modeling and reliability calculation, an improved Latin hypercube sampling method and an optimized importance sampling approach are developed correspondingly. Six different types of case studies demonstrate the superiority of the proposed AOK‐ES. The analysis results demonstrate that the proposed AOK‐ES holds the potential to reduce computing cost while ensuring accuracy.
- Subjects
ADAPTIVE sampling (Statistics); KRIGING; STRUCTURAL reliability; LATIN hypercube sampling
- Publication
Quality & Reliability Engineering International, 2024, Vol 40, Issue 4, p1502
- ISSN
0748-8017
- Publication type
Article
- DOI
10.1002/qre.3493