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A computational method for probabilistic safety assessment of I&C systems and human operators in nuclear power plants

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  • Kim, Man Cheol
  • Seong, Poong Hyun

Abstract

To make probabilistic safety assessment (PSA) more realistic, the improvements of human reliability analysis (HRA) are essential. But, current HRA methods have many limitations including the lack of considerations on the interdependency between instrumentation and control (I&C) systems and human operators, and lack of theoretical basis for situation assessment of human operators. To overcome these limitations, we propose a new method for the quantitative safety assessment of I&C systems and human operators. The proposed method is developed based on the computational models for the knowledge-driven monitoring and the situation assessment of human operators, with the consideration of the interdependency between I&C systems and human operators. The application of the proposed method to an example situation demonstrates that the quantitative description by the proposed method for a probable scenario well matches with the qualitative description of the scenario. It is also demonstrated that the proposed method can probabilistically consider all possible scenarios and the proposed method can be used to quantitatively evaluate the effects of various context factor on the safety of nuclear power plants. In our opinion, the proposed method can be used as the basis for the development of advanced HRA methods.

Suggested Citation

  • Kim, Man Cheol & Seong, Poong Hyun, 2006. "A computational method for probabilistic safety assessment of I&C systems and human operators in nuclear power plants," Reliability Engineering and System Safety, Elsevier, vol. 91(5), pages 580-593.
    • Handle: RePEc:eee:reensy:v:91:y:2006:i:5:p:580-593
    DOI: 10.1016/j.ress.2005.04.006
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    Citations

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    Cited by:

    1. Mkrtchyan, L. & Podofillini, L. & Dang, V.N., 2015. "Bayesian belief networks for human reliability analysis: A review of applications and gaps," Reliability Engineering and System Safety, Elsevier, vol. 139(C), pages 1-16.
    2. Lee, Seung Jun & Kim, Man Cheol & Seong, Poong Hyun, 2008. "An analytical approach to quantitative effect estimation of operation advisory system based on human cognitive process using the Bayesian belief network," Reliability Engineering and System Safety, Elsevier, vol. 93(4), pages 567-577.
    3. Park, Jinkyun & Jung, Wondea & Yang, Joon-Eon, 2012. "Investigating the effect of communication characteristics on crew performance under the simulated emergency condition of nuclear power plants," Reliability Engineering and System Safety, Elsevier, vol. 101(C), pages 1-13.
    4. Sýkora, Miroslav & Marková, Jana & Diamantidis, Dimitris, 2018. "Bayesian network application for the risk assessment of existing energy production units," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 312-320.
    5. You, Qidong & Guo, Jianbin & Zeng, Shengkui & Che, Haiyang, 2024. "A dynamic Bayesian network based reliability assessment method for short-term multi-round situation awareness considering round dependencies," Reliability Engineering and System Safety, Elsevier, vol. 243(C).

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