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A Bayesian Network Approach for Modeling Dependent Seismic Failures in a Nuclear Power Plant Probabilistic Risk Assessment

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  • DeJesus Segarra, Jonathan
  • Bensi, Michelle
  • Modarres, Mohammad

Abstract

The importance of modeling dependency between seismic failures of multiple components in a nuclear power plant (NPP) probabilistic risk assessment (PRA) has been discussed since the 1980s. In NUREG/CR-7237, Budnitz et al. found the Reed-McCann method to be the most promising method for modeling dependent seismic failures in NPP PRA. However, there are issues with the Reed-McCann method's quantification of the seismic fragility of a system of multiple components. To address this issue and to facilitate an overall realism increase in modeling dependencies in seismic PRA, this paper proposes a Bayesian network (BN) approach to model dependent seismic failures. To illustrate the proposed approach, we calculate the fragility of a parallel system and a series system using the Reed-McCann method, the BN approach, the First-Order Reliability Method (FORM) and Monte Carlo simulation (MCS). Then, we compare the system fragility results from these four approaches/methods to the lower and upper bounds of the system fragility. We found that the BN approach performed better than the Reed-McCann method with respect to providing results that stay within the lower and upper bounds of the system fragility. Further, the BN approach gives similar results to FORM and MCS. This paper proposes a BN approach because, in combination with our previous work about extending a probabilistic seismic hazard analysis to account for the spatial variability of ground motion at an NPP hard-rock site, it can be used to simultaneously and realistically account for dependent seismic failures and spatial variability of ground motion in both single-unit and multi-unit seismic PRAs.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:reensy:v:213:y:2021:i:c:s0951832021002167
    DOI: 10.1016/j.ress.2021.107678
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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. 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. Bensi, Michelle & Kiureghian, Armen Der & Straub, Daniel, 2013. "Efficient Bayesian network modeling of systems," Reliability Engineering and System Safety, Elsevier, vol. 112(C), pages 200-213.
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    Cited by:

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    4. Bodenmann, Lukas & Reuland, Yves & Stojadinović, Božidar, 2023. "Dynamic post-earthquake updating of regional damage estimates using Gaussian Processes," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
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    6. Yoon, Jae Young & Kim, Dong-San, 2022. "Estimating the adverse effects of inter-unit radioactive release on operator actions at a multi-unit site," Reliability Engineering and System Safety, Elsevier, vol. 228(C).

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