Dynamic Bayesian network modeling of reliability of subsea blowout preventer stack in presence of common cause failures

  • Liu Z
  • Liu Y
  • Cai B
 et al. 
  • 29


    Mendeley users who have this article in their library.
  • 12


    Citations of this article.


A subsea blowout preventer (BOP) stack is used to seal, control and monitor oil and gas wells. It can be regarded as a series-parallel system consisting of several subsystems. This paper develops the dynamic Bayesian network (DBN) of a parallel system with n components, taking account of common cause failures and imperfect coverage. Multiple error shock model is used to model common cause failures. Based on the proposed generic model, DBNs of the two commonly used stack types, namely the conventional BOP and modern BOP are developed. In order to evaluate the effects of the failure rates and coverage factor on the reliability and availability of the stacks, sensitivity analysis is performed.

Author-supplied keywords

  • Common cause failures
  • Dynamic bayesian network
  • Imperfect coverage
  • Reliability
  • Subsea blowout preventer

Get free article suggestions today

Mendeley saves you time finding and organizing research

Sign up here
Already have an account ?Sign in

Find this document


Cite this document

Choose a citation style from the tabs below

Save time finding and organizing research with Mendeley

Sign up for free