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.
Type de document :
Communication dans un congrès
Lambda-Mu 19, Oct 2014, Dijion, France. Actes du Congrès Lambda Mu 19
https://hal-supelec.archives-ouvertes.fr/hal-01090194
Contributeur : Yanfu Li
<>
Soumis le : mercredi 3 décembre 2014 - 10:40:10
Dernière modification le : jeudi 5 avril 2018 - 12:30:14
Document(s) archivé(s) le : samedi 15 avril 2017 - 01:44:19
Yan-Hui Lin, Yanfu Li, Enrico Zio. MODELING MULTIPLE DEPENDENT COMPETING DEGRADATIONS UNDER EPISTEMIC UNCERTAINTY VIA PDMP. Lambda-Mu 19, Oct 2014, Dijion, France. Actes du Congrès Lambda Mu 19. 〈hal-01090194〉
