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Development of a multi-unit seismic conditional core damage probability model with uncertainty analysis

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  • Heo, Yunyeong
  • Lee, Seung Jun

Abstract

Various studies about multi-unit probabilistic safety assessment (PSA) have been conducted following the Fukushima accident. In this paper, an intuitive and simple model is developed to supplement the disadvantages of huge models that integrate all units in the same site. Through this framework, pre-assessment can be made for multi-unit events, the results of which can assist risk-informed decision making in a relatively short time. The model deducts multi-unit seismic conditional core damage probability (MUSCCDP) with a Bayesian belief network, and by including seismic inter-unit correlation factors, the model can also represent the extent of simultaneous and identical core damage in multiple units at the same site due to an earthquake. The outcome of the model confirms the impact that seismic intensity and seismic correlation have on MUSCCDP. Moreover, it provides an importance analysis of the components in the units and represents which components are the most vulnerable in multiple units. As the uncertainty analysis of the input data for the model is conducted by changing the distribution of the variables, the results raise the necessity for further uncertainty analyses in multi-unit seismic PSA before accepting the PSA results.

Suggested Citation

  • 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).
  • Handle: RePEc:eee:reensy:v:207:y:2021:i:c:s0951832020308449
    DOI: 10.1016/j.ress.2020.107353
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    References listed on IDEAS

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    1. 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.
    2. Trucco, P. & Cagno, E. & Ruggeri, F. & Grande, O., 2008. "A Bayesian Belief Network modelling of organisational factors in risk analysis: A case study in maritime transportation," Reliability Engineering and System Safety, Elsevier, vol. 93(6), pages 845-856.
    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).
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    Citations

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    Cited by:

    1. 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).
    2. Pang, Rui & Zai, Dezhi & Xu, Bin & Liu, Jun & Zhao, Chunfeng & Fan, Qunying & Chen, Yuting, 2023. "Stochastic dynamic and reliability analysis of AP1000 nuclear power plants via DPIM subjected to mainshock-aftershock sequences," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    3. 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).
    4. Yoo, Heejong & Heo, Gyunyoung, 2023. "Analysis of site operating state contributions for multi-unit PSA with Korean NPP Sites," Reliability Engineering and System Safety, Elsevier, vol. 236(C).
    5. Kim, Man Cheol, 2022. "Systematic approach and mathematical development for conditional core damage probabilities under station blackout of a nuclear power plant," Reliability Engineering and System Safety, Elsevier, vol. 217(C).

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