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Sensitivity Study on the Correlation Level of Seismic Failures in Seismic Probabilistic Safety Assessments

Author

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  • Geon Gyu Choi

    (Quantum and Nuclear Engineering, Sejong University, 209 Neungdong-ro, Gwangjin-gu, Seoul 05006, Korea)

  • Woo Sik Jung

    (Quantum and Nuclear Engineering, Sejong University, 209 Neungdong-ro, Gwangjin-gu, Seoul 05006, Korea)

  • Seong Kyu Park

    (Quantum and Nuclear Engineering, Sejong University, 209 Neungdong-ro, Gwangjin-gu, Seoul 05006, Korea)

Abstract

It is popular that correlated seismic failures spread over the fault tree of a seismic probabilistic safety assessment (PSA) for a nuclear power plant (NPP). To avoid the calculational difficulty of core damage frequency (CDF), the fault tree has been simplified by replacing correlated seismic failures with one typical seismic failure by assuming a full correlation among the correlated seismic failures. Then, the approximate seismic CDF of a seismic single-unit PSA (SUPSA) has been calculated for decades with this simplified SUPSA fault tree. Furthermore, current seismic multi-unit PSAs (MUPSAs) have been performed with imperfect seismic MUPSA models that were generated by combining such imperfect seismic SUPSA fault trees. The authors of this study recently developed a method that can calculate an accurate seismic CDF by converting correlated seismic failures into seismic common cause failures (CCFs). In this study, accurate and imperfect MUPSA models were created and their seismic CDFs were compared. The results of this study show that the seismic CDFs in SUPSA and MUPSA are drastically distorted and safety margins are accordingly distorted when the full correlation assumption is employed. Thus, this study shows that very careful attention should be paid to calculating and interpreting seismic CDFs for the single-unit and multi-unit NPP regulations.

Suggested Citation

  • Geon Gyu Choi & Woo Sik Jung & Seong Kyu Park, 2021. "Sensitivity Study on the Correlation Level of Seismic Failures in Seismic Probabilistic Safety Assessments," Energies, MDPI, vol. 14(10), pages 1-20, May.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:10:p:2955-:d:558448
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    References listed on IDEAS

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    1. Schroer, Suzanne & Modarres, Mohammad, 2013. "An event classification schema for evaluating site risk in a multi-unit nuclear power plant probabilistic risk assessment," Reliability Engineering and System Safety, Elsevier, vol. 117(C), pages 40-51.
    2. 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.
    3. 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).
    4. Modarres, Mohammad & Zhou, Taotao & Massoud, Mahmoud, 2017. "Advances in multi-unit nuclear power plant probabilistic risk assessment," Reliability Engineering and System Safety, Elsevier, vol. 157(C), pages 87-100.
    5. 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).
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    Cited by:

    1. Gyunyoung Heo, 2022. "Advancements in Probabilistic Safety Assessment of Nuclear Energy for Sustainability," Energies, MDPI, vol. 15(2), pages 1-2, January.
    2. 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).

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