Unification of Common Cause Failures-Parametric Models Using a Generic Markovian Model

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• 作者：Mourad Chebila (1)
  Fares Innal (1)
  
• 关键词：Common cause failures ; Parametric models ; Unified Markov model ; MooN architectures
• 刊名：Journal of Failure Analysis and Prevention
• 出版年：2014
• 出版时间：June 2014
• 年：2014
• 卷：14
• 期：3
• 页码：426-434
• 全文大小：
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  21. U.S. Nuclear Regulatory Commission (2012), CCF Parameter Estimations (2010)
  
• 作者单位：Mourad Chebila (1)
  Fares Innal (1)
  
  1. IHSI-LRPI, Batna University, 05 Avenue Chahid Mohamed Boukhlouf, 05000, Batna, Algeria
  
• ISSN：1864-1245

文摘

The main objective of this paper is to provide a unified Markov model which could implement any parametric models devoted to the treatment of common cause failures (CCFs), namely: beta factor, multiple greek letter, alpha factor, multiple beta factor, and binomial failure rate. The choice of the Markovian representation is motivated by the fact that classical reliability approaches (e.g., Fault trees) are not able to catch the dynamic aspect induced by CCF events. The proposed Markovian model is also capable of dealing with any M-out-of-N configuration. It is illustrated on the basis of a system made up of four identical components (N?=?4) in order to quantitatively examine the differences between the first four mentioned parametric models. For that purpose, the considered performance indicators are the average unavailability (U avg) and the average unconditional failure intensity (i.e., failure frequency) (w avg).