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Application of Bayesian network to the probabilistic risk assessment of nuclear waste disposal

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  • Lee, Chang-Ju
  • Lee, Kun Jai

Abstract

The scenario in a risk analysis can be defined as the propagating feature of specific initiating event which can go to a wide range of undesirable consequences. If we take various scenarios into consideration, the risk analysis becomes more complex than do without them. A lot of risk analyses have been performed to actually estimate a risk profile under both uncertain future states of hazard sources and undesirable scenarios. Unfortunately, in case of considering specific systems such as a radioactive waste disposal facility, since the behaviour of future scenarios is hardly predicted without special reasoning process, we cannot estimate their risk only with a traditional risk analysis methodology. Moreover, we believe that the sources of uncertainty at future states can be reduced pertinently by setting up dependency relationships interrelating geological, hydrological, and ecological aspects of the site with all the scenarios. It is then required current methodology of uncertainty analysis of the waste disposal facility be revisited under this belief.

Suggested Citation

  • Lee, Chang-Ju & Lee, Kun Jai, 2006. "Application of Bayesian network to the probabilistic risk assessment of nuclear waste disposal," Reliability Engineering and System Safety, Elsevier, vol. 91(5), pages 515-532.
  • Handle: RePEc:eee:reensy:v:91:y:2006:i:5:p:515-532
    DOI: 10.1016/j.ress.2005.03.011
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    1. Tan, Tu Guang & Jang, Sunghyon & Yamaguchi, Akira, 2019. "A novel method for risk-informed decision-making under non-ideal Instrumentation and Control conditions through the application of Bayes’ Theorem," Reliability Engineering and System Safety, Elsevier, vol. 188(C), pages 463-472.
    2. François Diaz-Maurin & Rodney C. Ewing, 2018. "Mission Impossible? Socio-Technical Integration of Nuclear Waste Geological Disposal Systems," Sustainability, MDPI, vol. 10(12), pages 1-39, November.
    3. Dabić-Ostojić, Svetlana & Miljuš, Momčilo & Bojović, Nebojša & Glišović, Nataša & Milenković, Miloš, 2014. "Applying a mathematical approach to improve the tire retreading process," Resources, Conservation & Recycling, Elsevier, vol. 86(C), pages 107-117.
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    7. Borrett, Stuart R. & Sheble, Laura & Moody, James & Anway, Evan C., 2018. "Bibliometric review of ecological network analysis: 2010–2016," Ecological Modelling, Elsevier, vol. 382(C), pages 63-82.
    8. H Chraibi & S Pierlot, 2010. "Approach to assess the occurrence probability of a long-term evolution scenario of a long-lived nuclear waste repository," Journal of Risk and Reliability, , vol. 224(3), pages 217-224, September.
    9. Mojgan Aalipour & Yonas Zewdu Ayele & Abbas Barabadi, 2016. "Human reliability assessment (HRA) in maintenance of production process: a case study," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 7(2), pages 229-238, June.
    10. Edoardo Tosoni & Ahti Salo & Enrico Zio, 2018. "Scenario Analysis for the Safety Assessment of Nuclear Waste Repositories: A Critical Review," Risk Analysis, John Wiley & Sons, vol. 38(4), pages 755-776, April.
    11. Maokuan Zheng & Xinguo Ming & Miao Li & Lina He, 2015. "A framework for Industrial Product–Service Systems risk management," Journal of Risk and Reliability, , vol. 229(6), pages 501-516, December.
    12. Tang, P.Z. & Liu, J.Z. & Lu, H.W. & Wang, Z. & He, L., 2017. "Information-based Network Environ Analysis for Ecological Risk Assessment of heavy metals in soils," Ecological Modelling, Elsevier, vol. 344(C), pages 17-28.
    13. Norrington, Lisa & Quigley, John & Russell, Ashley & Van der Meer, Robert, 2008. "Modelling the reliability of search and rescue operations with Bayesian Belief Networks," Reliability Engineering and System Safety, Elsevier, vol. 93(7), pages 940-949.
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