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MODELING MULTIPLE DEPENDENT COMPETING DEGRADATIONS UNDER EPISTEMIC UNCERTAINTY VIA PDMP

Résumé : Piecewise-deterministic Markov process (PDMP) modeling framework can handle the dependencies between physics-based models, between multi-state models and between these two types of models. Epistemic uncertainty can arise due to the incomplete or imprecise knowledge about the degradation processes and the governing parameters: to take into account this, we describe the parameters of the PDMP model as fuzzy numbers. In this paper, we extend the finite-volume (FV) method to quantify the (fuzzy) reliability of the system. The proposed method is tested on one subsystem of the residual heat removal system (RHRS) of a nuclear power plant, and a comparison is offered with a Monte Carlo (MC) simulation solution.
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https://hal-supelec.archives-ouvertes.fr/hal-01090194
Contributor : Yanfu Li <>
Submitted on : Wednesday, December 3, 2014 - 10:40:10 AM
Last modification on : Wednesday, July 15, 2020 - 10:00:02 AM
Long-term archiving on: : Saturday, April 15, 2017 - 1:44:19 AM

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  • HAL Id : hal-01090194, version 1

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Yan-Hui Lin, Yanfu Li, Enrico Zio. MODELING MULTIPLE DEPENDENT COMPETING DEGRADATIONS UNDER EPISTEMIC UNCERTAINTY VIA PDMP. Lambda-Mu 19, Oct 2014, Dijion, France. ⟨hal-01090194⟩

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