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

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

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.

Suggested Citation

  • Sarazin, Gabriel & Morio, Jérôme & Lagnoux, Agnès & Balesdent, Mathieu & Brevault, Loïc, 2021. "Reliability-oriented sensitivity analysis in presence of data-driven epistemic uncertainty," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
  • Handle: RePEc:eee:reensy:v:215:y:2021:i:c:s0951832021002672
    DOI: 10.1016/j.ress.2021.107733
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    5. Zhiwei Bai & Hongkui Wei & Yingying Xiao & Shufang Song & Sergei Kucherenko, 2021. "A Vine Copula-Based Global Sensitivity Analysis Method for Structures with Multidimensional Dependent Variables," Mathematics, MDPI, vol. 9(19), pages 1-20, October.
    6. Meng, Zeng & Zhao, Jingyu & Chen, Guohai & Yang, Dixiong, 2022. "Hybrid uncertainty propagation and reliability analysis using direct probability integral method and exponential convex model," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    7. Li, He & Guedes Soares, C, 2022. "Assessment of failure rates and reliability of floating offshore wind turbines," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    8. Moglen, Rachel L. & Barth, Julius & Gupta, Shagun & Kawai, Eiji & Klise, Katherine & Leibowicz, Benjamin D., 2023. "A nexus approach to infrastructure resilience planning under uncertainty," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    9. Ajenjo, Antoine & Ardillon, Emmanuel & Chabridon, Vincent & Cogan, Scott & Sadoulet-Reboul, Emeline, 2023. "Robustness evaluation of the reliability of penstocks combining line sampling and neural networks," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    10. Zaitseva, Elena & Levashenko, Vitaly & Rabcan, Jan, 2023. "A new method for analysis of Multi-State systems based on Multi-valued decision diagram under epistemic uncertainty," Reliability Engineering and System Safety, Elsevier, vol. 229(C).

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