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Development of a Software Tool for Seismic Probabilistic Safety Assessment Quantification with a Sufficiently Large Number of Bins for Enhanced Accuracy

Author

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  • Ji Suk Kim

    (Department of Energy Systems Engineering, Chung-Ang University, Seoul 06974, Korea)

  • Man Cheol Kim

    (Department of Energy Systems Engineering, Chung-Ang University, Seoul 06974, Korea)

Abstract

Quantification in seismic probabilistic safety assessment (PSA) includes the convolution of hazard and fragility curves. Because it is difficult to find the closed-form integration for the convolution of two curves, numerical methods are widely used in practice. In practical applications, the number of ground motion level bins in numerical methods is limited, and it is not clear whether the limited number of bins leads to conservative or optimistic results. In this study, the effect of the number of bins on the quantification results with simplified assumptions is investigated. It is found that the quantification results mostly decrease as the number of bins increases. To enhance accuracy in the quantification results of seismic PSA, a method and a software tool that enable a sufficiently large number of bins to be used for the quantification of seismic PSA models are developed. The application of the developed software tool to an example seismic PSA model demonstrates how the quantification results approach accurate results as the number of bins increases. The software tool developed in this study is expected to enhance the accuracy of seismic PSA quantification results.

Suggested Citation

  • Ji Suk Kim & Man Cheol Kim, 2021. "Development of a Software Tool for Seismic Probabilistic Safety Assessment Quantification with a Sufficiently Large Number of Bins for Enhanced Accuracy," Energies, MDPI, vol. 14(6), pages 1-14, March.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:6:p:1677-:d:519250
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    References listed on IDEAS

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    1. Jung, Woo Sik, 2015. "A method to improve cutset probability calculation in probabilistic safety assessment of nuclear power plants," Reliability Engineering and System Safety, Elsevier, vol. 134(C), pages 134-142.
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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.

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