Stochastic Modeling of Deterioration Processes through Dynamic Bayesian Networks

This paper proposes a generic framework for stochastic modeling of deterioration processes, 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 2 applications to probabilistic modeling of fatigue crack growth.

  • Availability:
  • Supplemental Notes:
    • Abstract reprinted with permission from ASCE
  • Authors:
    • Straub, Daniel
  • Publication Date: 2009-10

Language

  • English

Media Info

Subject/Index Terms

Filing Info

  • Accession Number: 01141929
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Oct 2 2009 6:26PM