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An improved multi-unit nuclear plant seismic probabilistic risk assessment approach

Author

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  • Zhou, Taotao
  • Modarres, Mohammad
  • Droguett, Enrique López

Abstract

This paper proposes an improved approach to external event probabilistic risk assessment for multi-unit sites. It considers unit-to-unit dependencies based on the integration of the copula notion, importance sampling, and parallel Monte Carlo simulation, including their implementation on standard PRA software tools. The multi-unit probabilistic risk assessment (MUPRA) approach and issues related to the current methods for seismic dependencies modeling are discussed. The seismic risk quantification is discussed in the context of two typical numerical schemes: the discretization-based scheme and simulation-based scheme. The issues related to the current discretization-based scheme are also highlighted. To address these issues and to quantify the seismic risk at the site level, an improved approach is developed to quantify the site-level fragilities. The approach is based on a hybrid scheme that involves the simulation-based method to account for the dependencies among the multi-unit structures, systems and components (SSCs) at the group level of dependent SSCs, and the discretization-based scheme. Finally, a case study is developed for the seismic-induced Small Loss of Coolant Accident (SLOCA) for a hypothetical nuclear plant site consisting of two identical advanced (GEN-III) reactor units. The results from this case study summarize the effects of correlation across multiple reactor units on the site-level core damage frequency (CDF). Three multi-unit CDF metrics (site, concurrent and marginal) were calculated for this case study. It is concluded that based on correlations between the SSCs, the total site CDF metric would be the most appropriate multi-unit CDF metric for seismic risk.

Suggested Citation

  • Zhou, Taotao & Modarres, Mohammad & Droguett, Enrique López, 2018. "An improved multi-unit nuclear plant seismic probabilistic risk assessment approach," Reliability Engineering and System Safety, Elsevier, vol. 171(C), pages 34-47.
    • Handle: RePEc:eee:reensy:v:171:y:2018:i:c:p:34-47
    DOI: 10.1016/j.ress.2017.11.015
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    Citations

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    Cited by:

    1. Kwag, Shinyoung & Park, Junhee & Choi, In-Kil, 2020. "Development of efficient complete-sampling-based seismic PSA method for nuclear power plant," Reliability Engineering and System Safety, Elsevier, vol. 197(C).
    2. Heo, Yunyeong & Lee, Seung Jun, 2021. "Development of a multi-unit seismic conditional core damage probability model with uncertainty analysis," Reliability Engineering and System Safety, Elsevier, vol. 207(C).
    3. Xiaohui Chen & Lin Zhang & Ze Zhang, 2020. "An integrated model for maintenance policies and production scheduling based on immune–culture algorithm," Journal of Risk and Reliability, , vol. 234(5), pages 651-663, October.
    4. 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).
    5. 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).
    6. Zhou, Taotao & Droguett, Enrique López & Modarres, Mohammad, 2020. "A common cause failure model for components under age-related degradation," Reliability Engineering and System Safety, Elsevier, vol. 195(C).
    7. DeJesus Segarra, Jonathan & Bensi, Michelle & Modarres, Mohammad, 2023. "Multi-unit seismic probabilistic risk assessment: A Bayesian network perspective," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    8. Zhou, Taotao & Modarres, Mohammad & Droguett, Enrique López, 2019. "Multi-unit risk aggregation with consideration of uncertainty and bias in risk metrics," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 473-482.
    9. Zhang, Lin & Chen, Xiaohui & Khatab, Abdelhakim & An, Youjun, 2022. "Optimizing imperfect preventive maintenance in multi-component repairable systems under s-dependent competing risks," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
    10. Kwag, Shinyoung & Choi, Eujeong & Eem, Seunghyun & Ha, Jeong-Gon & Hahm, Daegi, 2021. "Toward improvement of sampling-based seismic probabilistic safety assessment method for nuclear facilities using composite distribution and adaptive discretization," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    11. Cai, Yinan & Golay, Michael W., 2020. "Formulation of A Risk Assessment Framework Capable of Analyzing Nuclear Power Multiunit Accident Scenarios," Reliability Engineering and System Safety, Elsevier, vol. 202(C).
    12. DeJesus Segarra, Jonathan & Bensi, Michelle & Modarres, Mohammad, 2021. "A Bayesian Network Approach for Modeling Dependent Seismic Failures in a Nuclear Power Plant Probabilistic Risk Assessment," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
    13. 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.
    14. Woo Sik Jung, 2021. "A Method to Avoid Underestimated Risks in Seismic SUPSA and MUPSA for Nuclear Power Plants Caused by Partitioning Events," Energies, MDPI, vol. 14(8), pages 1-13, April.

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