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A Multi-state Physics Model of Component Degradation based on Stochastic Petri Nets and Simulation

Abstract : Multi-state physics modeling (MSPM) of degradation processes is an approach proposed for estimating the failure probability of components and systems. This approach integrates multi-state modeling, which describes the degradation process through transitions among discrete states (e.g. initial, micro-crack, rupture, etc), and physics modeling by (physics) equations that describe the degradation process within the states. In reality, the degradation process is non-Markovian, its transition rates are time-dependent, and the degradation is possibly influenced by uncertain external factors such as temperature and stress. Under these conditions, it is in general difficult to derive the state probabilities analytically. In this paper, we overcome this difficulty by building a simulation model supported by a stochastic Petri net representing the multi-state degradation process. The proposed modeling approach is applied to the problem of a nuclear component undergoing stress corrosion cracking. The results are compared with those derived from the state-space enrichment Markov chain approximation method applied in a previous work of literature.
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Submitted on : Tuesday, October 2, 2012 - 1:05:49 PM
Last modification on : Saturday, May 8, 2021 - 3:26:59 AM
Long-term archiving on: : Thursday, January 3, 2013 - 4:30:22 AM


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Yan-Fu Li, Enrico Zio, Yan-Hui Lin. A Multi-state Physics Model of Component Degradation based on Stochastic Petri Nets and Simulation. IEEE Transactions on Reliability, Institute of Electrical and Electronics Engineers, 2012, 61 (4), pp.921-931. ⟨hal-00737618⟩



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