Efficient surrogate models for reliability analysis of systems with multiple failure modes

Barron J. Bichon, John M. McFarland and Sankaran Mahadevan

Reliability Engineering and System Safety, 2011, vol. 96, issue 10, 1386-1395

Abstract: Despite many advances in the field of computational reliability analysis, the efficient estimation of the reliability of a system with multiple failure modes remains a persistent challenge. Various sampling and analytical methods are available, but they typically require accepting a tradeoff between accuracy and computational efficiency. In this work, a surrogate-based approach is presented that simultaneously addresses the issues of accuracy, efficiency, and unimportant failure modes. The method is based on the creation of Gaussian process surrogate models that are required to be locally accurate only in the regions of the component limit states that contribute to system failure. This approach to constructing surrogate models is demonstrated to be both an efficient and accurate method for system-level reliability analysis.

Keywords: System reliability; Surrogate models; Reliability analysis; Gaussian process models (search for similar items in EconPapers)
Date: 2011
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Citations: View citations in EconPapers (47)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:96:y:2011:i:10:p:1386-1395

DOI: 10.1016/j.ress.2011.05.008

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