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Toward improvement of sampling-based seismic probabilistic safety assessment method for nuclear facilities using composite distribution and adaptive discretization

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  • Kwag, Shinyoung
  • Choi, Eujeong
  • Eem, Seunghyun
  • Ha, Jeong-Gon
  • Hahm, Daegi

Abstract

As a seismic probabilistic safety assessment (SPSA) method for nuclear facilities, direct quantification of fault tree using the Monte Carlo simulation (DQFM) was developed to accurately consider the partial dependency between components. However, since this is a sampling-based method, there is a disadvantage in that a large number of samples must be extracted for accurate seismic risk estimation. Accordingly, this study develops an efficient SPSA method by improving the existing DQFM method. We replace the method of extracting samples from both seismic response and capacity at each component by that of taking samples only from a single response distribution with a composite deviation. Also, a method of adaptive discretization for seismic intensity (ADSI) is devised by linking the seismic intensity subdivision with the convergence of the final seismic risk. The Monte-Carlo sampling technique is replaced by the Latin hypercube sampling. As an application result to nuclear facilities, the proposed method requires only half samples for every seismic intensity than the existing DQFM method, while the accuracy of results was almost similar. Besides, through the ADSI method, the proposed method was able to secure approximately three times efficiency more than the existing DQFM method, without losing the accuracy of the results.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:reensy:v:215:y:2021:i:c:s095183202100332x
    DOI: 10.1016/j.ress.2021.107809
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    References listed on IDEAS

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    1. Kwag, Shinyoung & Gupta, Abhinav & Dinh, Nam, 2018. "Probabilistic risk assessment based model validation method using Bayesian network," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 380-393.
    2. 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).
    3. 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.
    4. Shinyoung Kwag & Daegi Hahm, 2020. "Multi-objective-based seismic fragility relocation for a Korean nuclear power plant," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 103(3), pages 3633-3659, September.
    5. Shinyoung Kwag & Jeong Gon Ha & Min Kyu Kim & Jung Han Kim, 2019. "Development of Efficient External Multi-Hazard Risk Quantification Methodology for Nuclear Facilities," Energies, MDPI, vol. 12(20), pages 1-25, October.
    6. Hakata, Tadakuni, 2007. "Seismic PSA method for multiple nuclear power plants in a site," Reliability Engineering and System Safety, Elsevier, vol. 92(7), pages 883-894.
    7. Eujeong Choi & Shinyoung Kwag & Jeong-Gon Ha & Daegi Hahm, 2021. "Development of a Two-Stage DQFM to Improve Efficiency of Single- and Multi-Hazard Risk Quantification for Nuclear Facilities," Energies, MDPI, vol. 14(4), pages 1-21, February.
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