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Common cause failure model updating for risk monitoring in nuclear power plants based on alpha factor model

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  • Min Zhang
  • Zhijian Zhang
  • Ali Mosleh
  • Sijuan Chen

Abstract

Common cause failure model updating (both qualitatively and quantitatively) is a key factor in risk monitoring for nuclear power plants when configuration changes (e.g. components become unavailable) occur among a redundant configuration. This research focuses on the common cause failure updating based on the alpha factor model method, which is commonly used in the living probabilistic safety assessment models for nuclear power plant risk monitoring. This article first discusses the common cause failure model updating in an ideal condition, which evaluates the common cause failure model parameters for the configurationally changed system in different ways, based on the causes of the detected failures. Then, two alternative updating processes are proposed considering the difficulty to identify failure causes immediately during plant operation: one is to update the common cause failure models with the assumption that the failures detected are independent failures and the other is to update the common cause failure models with the parameters as expectations of the values for all possible failure causes. Finally, a case study is given to illustrate the common cause failure updating process and to compare these two alternative processes. The results show that (1) common cause failures can be reevaluated automatically by the methods proposed in this article and (2) the second process is more conservative and reasonable but with more data requirements compared with the first approach. Considering limitations in accessibility of the data, the first strategy is suggested currently. More future work on data acquisition is demanded for better assessment of common cause failures during nuclear power plant risk monitoring.

Suggested Citation

  • Min Zhang & Zhijian Zhang & Ali Mosleh & Sijuan Chen, 2017. "Common cause failure model updating for risk monitoring in nuclear power plants based on alpha factor model," Journal of Risk and Reliability, , vol. 231(3), pages 209-220, June.
  • Handle: RePEc:sae:risrel:v:231:y:2017:i:3:p:209-220
    DOI: 10.1177/1748006X16689542
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    References listed on IDEAS

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    1. Torres-Echeverría, A.C. & Martorell, S. & Thompson, H.A., 2011. "Modeling safety instrumented systems with MooN voting architectures addressing system reconfiguration for testing," Reliability Engineering and System Safety, Elsevier, vol. 96(5), pages 545-563.
    2. Rahimi, Maryam & Rausand, Marvin, 2013. "Monitoring human and organizational factors influencing common-cause failures of safety-instrumented system during the operational phase," Reliability Engineering and System Safety, Elsevier, vol. 120(C), pages 10-17.
    3. Vaurio, Jussi K., 2005. "Uncertainties and quantification of common cause failure rates and probabilities for system analyses," Reliability Engineering and System Safety, Elsevier, vol. 90(2), pages 186-195.
    4. Troffaes, Matthias C.M. & Walter, Gero & Kelly, Dana, 2014. "A robust Bayesian approach to modeling epistemic uncertainty in common-cause failure models," Reliability Engineering and System Safety, Elsevier, vol. 125(C), pages 13-21.
    5. KanÄ ev, DuÅ¡ko & ÄŒepin, Marko, 2012. "A new method for explicit modelling of single failure event within different common cause failure groups," Reliability Engineering and System Safety, Elsevier, vol. 103(C), pages 84-93.
    6. Rajagopal, 2014. "The Human Factors," Palgrave Macmillan Books, in: Architecting Enterprise, chapter 9, pages 225-249, Palgrave Macmillan.
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    Cited by:

    1. Sakurahara, Tatsuya & Schumock, Grant & Reihani, Seyed & Kee, Ernie & Mohaghegh, Zahra, 2019. "Simulation-Informed Probabilistic Methodology for Common Cause Failure Analysis," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 84-99.
    2. Le Duy, Tu Duong & Vasseur, Dominique, 2018. "A practical methodology for modeling and estimation of common cause failure parameters in multi-unit nuclear PSA model," Reliability Engineering and System Safety, Elsevier, vol. 170(C), pages 159-174.

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