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A practical methodology for modeling and estimation of common cause failure parameters in multi-unit nuclear PSA model

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  • Le Duy, Tu Duong
  • Vasseur, Dominique

Abstract

When assessing the risk related to Nuclear Power Plants in terms of impacts on the population health and on the environment, multi-unit issues should be taken into account. The specific aim of a Probabilistic Safety Assessment at site level is to deal with the dependencies existing between the units on that site. One of important dependency factors is the potential existence of the inter-unit common cause failures (CCF) that could affect identical systems (with or without interconnections) present in each unit. As they are identical this makes them potentially sensitive to "inter-unit" CCF, in addition to "intra-unit" CCF that are usually modeled for redundant systems.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:reensy:v:170:y:2018:i:c:p:159-174
    DOI: 10.1016/j.ress.2017.10.018
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    References listed on IDEAS

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    1. 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.
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    4. Kelly, Dana & Atwood, Corwin, 2011. "Finding a minimally informative Dirichlet prior distribution using least squares," Reliability Engineering and System Safety, Elsevier, vol. 96(3), pages 398-402.
    5. Le Duy, Tu Duong & Vasseur, Dominique & Serdet, Emmanuel, 2016. "Probabilistic Safety Assessment of twin-unit nuclear sites: Methodological elements," Reliability Engineering and System Safety, Elsevier, vol. 145(C), pages 250-261.
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    Citations

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    Cited by:

    1. Song, Wonjong & Park, Sunghyun & Seo, Yein & Jae, Moosung, 2020. "A source term binning methodology for multi-unit consequence analyses," Reliability Engineering and System Safety, Elsevier, vol. 202(C).
    2. Kim, Yongjin & Jang, Seunghyun & Jae, Moosung, 2022. "Evaluation of inter-unit dependency effect on site core damage frequency: Internal and seismic event," Reliability Engineering and System Safety, Elsevier, vol. 227(C).
    3. Jang, Seunghyun & Jae, Moosung, 2020. "A development of methodology for assessing the inter-unit common cause failure in multi-unit PSA model," Reliability Engineering and System Safety, Elsevier, vol. 203(C).
    4. Kim, Dong-San & Park, Jin Hee & Lim, Ho-Gon, 2020. "A pragmatic approach to modeling common cause failures in multi-unit PSA for nuclear power plant sites with a large number of units," Reliability Engineering and System Safety, Elsevier, vol. 195(C).
    5. Arigi, Awwal Mohammed & Park, Gayoung & Kim, Jonghyun, 2020. "Dependency analysis method for human failure events in multi-unit probabilistic safety assessments," Reliability Engineering and System Safety, Elsevier, vol. 203(C).
    6. Zhou, Taotao & Modarres, Mohammad & Droguett, Enrique López, 2021. "Multi-unit nuclear power plant probabilistic risk assessment: A comprehensive survey," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
    7. Mi, Jinhua & Beer, Michael & Li, Yan-Feng & Broggi, Matteo & Cheng, Yuhua, 2020. "Reliability and importance analysis of uncertain system with common cause failures based on survival signature," Reliability Engineering and System Safety, Elsevier, vol. 201(C).
    8. Zhang, Sai & Du, Mengyu & Tong, Jiejuan & Li, Yan-Fu, 2019. "Multi-objective optimization of maintenance program in multi-unit nuclear power plant sites," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 532-548.
    9. Soga, Shota & Higo, Eishiro & Miura, Hiromichi, 2021. "A systematic approach to estimate an inter-unit common-cause failure probability," Reliability Engineering and System Safety, Elsevier, vol. 215(C).

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