Reliability-oriented sensitivity analysis in presence of data-driven epistemic uncertainty

Gabriel Sarazin, Morio, Jérôme, Lagnoux, Agnès, Mathieu Balesdent and Brevault, Loïc

Reliability Engineering and System Safety, 2021, vol. 215, issue C

Abstract: Reliability assessment in presence of epistemic uncertainty leads to consider the failure probability as a quantity depending on the state of knowledge about uncertain input parameters. The input joint distribution is often learnt from a small-sized dataset provided by operating experience. The computed failure probability depends on the estimated marginal distributions and the estimated copula distribution. This paper develops a reliability-oriented sensitivity analysis procedure in order to measure the influence exerted by the data-driven modeling of both the margins and the copula. The proposed methodology is validated for both deterministic and stochastic reliability methods through an extensive simulation study including several analytical performance functions as well as a real-life simulation code dealing with the buckling of a laminated composite plate.

Keywords: Sensitivity analysis; Rare-event simulation; Dependence modeling; Data-driven modeling (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (12)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:215:y:2021:i:c:s0951832021002672

DOI: 10.1016/j.ress.2021.107733

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