Stochastic Modeling of Deterioration Processes through Dynamic Bayesian Networks
Publication: Journal of Engineering Mechanics
Volume 135, Issue 10
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.
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Acknowledgments
This work was supported by the Swiss National Science Foundation (SNF) through Grant No. UNSPECIFIEDPA002-111428.
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© 2009 ASCE.
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Received: May 29, 2008
Accepted: Jan 23, 2009
Published online: Mar 6, 2009
Published in print: Oct 2009
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