An innovative adaptive Kriging-based parallel system reliability method under error stopping criterion for efficiently analyzing the global reliability sensitivity index

Wanying Yun, Shutong Zhang, Fengyuan Li, Xiangming Chen, Zhe Wang, Kaixuan Feng

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Global reliability sensitivity index measures the effect of uncertainty of model input on model failure probability, which is critical for simplifying analysis model and the reliability-based design optimization model. For efficiently estimating the global reliability sensitivity index of each model input, this paper transforms it into estimating an unconditional failure probability and a two failure modes-based parallel system failure probability from the perspective of single-loop estimation method. Furthermore, the relationship of computational accuracy among the global reliability sensitivity index, the unconditional failure probability, and the two failure modes-based system failure probability is constructed, on which the error stopping criterion-based sequentially adaptive Kriging model approach is developed to significantly decrease the number of calls to the actual limit state functions and the corresponding computational time under the sufficient accuracy. Results of three case studies covering explicit and implicit limit state functions demonstrate the accuracy and efficiency of the proposed method.

Original languageEnglish
Article number51
JournalStructural and Multidisciplinary Optimization
Volume67
Issue number4
DOIs
StatePublished - Apr 2024

Keywords

  • Error propagation analysis
  • Error stopping criterion
  • Global reliability sensitivity index
  • Sequential adaptive Kriging model
  • Single-loop estimation process

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