Abstract
A generic framework for stochastic modeling of deterioration processes is proposed, based on dynamic Bayesian networks. The framework facilitates computationally efficient and robust reliability analysis and, in particular, Bayesian updating of the model with measurements, monitoring, and inspection results. These properties make it ideally suited for near-real time applications in asset integrity management and deterioration control. The framework is demonstrated and investigated through two applications to probabilistic modeling of fatigue crack growth.
Original language | English |
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Pages (from-to) | 1089-1099 |
Number of pages | 11 |
Journal | Journal of Engineering Mechanics |
Volume | 135 |
Issue number | 10 |
DOIs | |
State | Published - 2009 |
Keywords
- Bayesian analysis
- Cracking
- Deterioration
- Fatigue
- Inspection
- Markov process
- Monitoring
- Stochastic processes