MODELING MULTIPLE DEPENDENT COMPETING DEGRADATIONS UNDER EPISTEMIC UNCERTAINTY VIA PDMP - CentraleSupélec Access content directly
Conference Papers Year : 2014

MODELING MULTIPLE DEPENDENT COMPETING DEGRADATIONS UNDER EPISTEMIC UNCERTAINTY VIA PDMP

Abstract

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.

Domains

Electric power
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Dates and versions

hal-01090194 , version 1 (03-12-2014)

Identifiers

  • HAL Id : hal-01090194 , version 1

Cite

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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