Multi-state physics systems (MSPS) modeling framework incorporates multi-state models that describes the systems degradation/maintenance process through transitions among discrete states, and physics-based models that describe the degradation process within the states by using physics knowledge and equations. In previous works, piecewise-deterministic Markov process (PDMP) has been adopted to treat the system dynamics and the degradation dependence in MSPS. For reliability assessment, Monte Carlo simulation and finite-volume method are two widely used numerical approaches to solve PDMP. In the present work, a comparative study considering different evaluation criteria of the two approaches is conducted on two representative case studies. We provide clear guidelines for the selection of the two approaches.

A comparison between Monte Carlo simulation and finite-volume scheme for reliability assessment of multi-state physics systems

Zio, Enrico
2018-01-01

Abstract

Multi-state physics systems (MSPS) modeling framework incorporates multi-state models that describes the systems degradation/maintenance process through transitions among discrete states, and physics-based models that describe the degradation process within the states by using physics knowledge and equations. In previous works, piecewise-deterministic Markov process (PDMP) has been adopted to treat the system dynamics and the degradation dependence in MSPS. For reliability assessment, Monte Carlo simulation and finite-volume method are two widely used numerical approaches to solve PDMP. In the present work, a comparative study considering different evaluation criteria of the two approaches is conducted on two representative case studies. We provide clear guidelines for the selection of the two approaches.
2018
Dependent degradation processes; Finite-volume scheme; Monte Carlo simulation method; Multi-state model; Physics-based model; Piecewise-deterministic Markov process; Safety, Risk, Reliability and Quality; Industrial and Manufacturing Engineering
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1077959
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