Abstract
Multistate physics modeling (MSPM) of degradation processes is an approach proposed for estimating the failure probability of components and systems. This approach integrates multistate modeling, which describes the degradation process through transitions among discrete states (e.g., initial, microcrack, 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 multistate 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.
| Original language | English |
|---|---|
| Article number | 6327635 |
| Pages (from-to) | 921-931 |
| Number of pages | 11 |
| Journal | IEEE Transactions on Reliability |
| Volume | 61 |
| Issue number | 4 |
| DOIs | |
| State | Published - 2012 |
| Externally published | Yes |
Keywords
- Component degradation
- Monte Carlo simulation
- multistate physics model
- nonhomogeneous Markov process
- stochastic Petri net
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