Acknowledgement
This research was supported by a grant(2020-MOIS35-002) from the Development of Preparedness and Mitigation Technologies Linked to the Countermeasures on Natural Disasters funded by the Ministry of Interior and Safety (MOIS, Korea).
References
- Nuclear Regulatory Commission (NRC), Risk Methods Insights Gained from Fire Incidents, NUREG/CR-6738, Washington, D.C, 2001.
- International Atomic Energy Agency (IAEA), Experience Gained from Fires in Nuclear Power Plants: Lessons Learned, IAEA, Vienna, 2004. IAEA-TECDOC-1421.
- Nuclear Regulatory Commission (NRC), A Short History of Fire Safety Research Sponsored by the US, NUREG/BR-0364, Nuclear Regulatory Commission, Washington, DC, 2009a, pp. 1975-2008.
- Organization for Economic Cooperation and Development/Nuclear Energy Agency, Report on Fukushima Daiichi NPP Precursor Events, 1, NEA/CNRA/R.(OECD/NEA), 2014a.
- K. Hukki, J.E. Holmberg, Development of Management of Nuclear Power Plant Fire Situations, Probabilistic Safety Assessment and Management, 2004, pp. 376-382, https://doi.org/10.1007/978-0-85729-410-4_61.
- M. Schneider, An Account of Events in Nuclear Power Plants since the Chernobyl Accident in 1986, Greens in the European Parliament, 2007.
- Organization for Economic Cooperation and Development (OECD), CNRA Summary Report on Operating Experience Feedback Related to Fire Events and Fire Protection Programmes (Safety Analysis of Fire Operating Events), 3, NEA/CNRA/R, 2009.
- H.S. Han, J.O. Lee, C.H. Hwang, J.S. Kim, S.K. Lee, Assessment of the habitability for a cabinet fire in the main control room of nuclear power plant using sensitivity analysis, Fire Sci. Eng. 31 (2) (2017) 52-60, https://doi.org/10.7731/KIFSE.2017.31.2.052.
- Organization for Economic Cooperation and Development/Nuclear Energy Agency, CSNI Technical Opinion Paper # 17- Fire Probabilistic Safety Assessments for Nuclear Power Plants, OECD/NEA, 2019. Update: 2019.
- National Fire Protection Association (NFPA), Performance-Based Standard for Fire Protection for Light Water Reactor Electric Generating Plants, 805, NFPA, Quincy, Mass, 2006.
- Nuclear Regulatory Commission (NRC), EPRI/NRC-RES Fire PRA Methodology for Nuclear Power Facilities, 2, NUREG/CR-6850, Washington, D.C, 2005. Detailed Methodology.
- Nuclear Regulatory Commission (NRC), Fire Probabilistic Risk Assessment Methods Enhancements. Supplement, NUREG/CR-6850 and EPRI 1011989, NUREG/CR-6850 Supplement 1, Washington, DC, 2010, p. 1.
- S.H. Kim, S. Lee, Probabilistic non-suppression model of electrical fire in nuclear power plant using maximum likelihood estimation method, J. Korean Soc. Hazard Mitig. 20 (5) (2020) 123-134, https://doi.org/10.9798/KOSHAM.2020.20.5.123.
- Electric Power Research Institute (EPRI), Fire PRA Implementation Guide, EPRI/TR-105928, Palo Alto, 1995.
- Nuclear Regulatory Commission (NRC), Nuclear Power Plant Fire Ignition Frequency and Non-suppression Probability Estimation Using the Updated Fire Events Database, NUREG-2169, Washington, D.C, 2015.
- S.H. Kim, S. Lee, Maximum likelihood estimation of probabilistic nonsuppression model for OECD NPP electrical fire applying non-negative continuous distribution, Fire Saf. J. 122 (2021) 1-7, https://doi.org/10.1016/j.firesaf.2021.103323.
- J. Neville, U. Farradj, K. Zee, A. Lindeman, Insights gained from a review of fire PRA risk contribution by ignition frequency bins, in: Asian Symposium on Risk Assessment and Management, Paper, Ida., 2017. ASRAM2017-1102.
- Nuclear Regulatory Commission (NRC), Fire Protection for Nuclear Power Plant. Regulatory Guide 1.189, 2009. Washington, DC.
- Nuclear Regulatory Commission (NRC), Perspectives Gained from the Individual Plant Examination of External Events (IPEEE) Program - Final Report, NUREG, Washington, DC, 2002.
- Nuclear Energy Institute (NEI), Road Map for Attaining Realism on Fire PRAs, 2010. Washington, D.C.
- Organization for Economic Cooperation and Development/Nuclear Energy Agency, OECD/NEA), Use of OECD/Nea Data Project Products in Probabilistic Safety Assessment, Nea/CSNI/R(2014), 2014b.
- Korea Nuclear International Cooperation Foundation (KNICF), OECD/NEA Research Cooperation Survey Analysis, 2019.
- H. Shalabi, G. Hadjisophocleous, CANDU fire database. Review, CNL Nucl. Rev. 8 (2) (2019) 179-189, https://doi.org/10.12943/CNR.2017.00019.
- The Society of Fire Protection Engineers (SFPE), SFPE Handbook of Fire Protection Engineering, fifth ed., Springer, 2016.
- Nuclear Regulatory Commission (NRC), Guidance on the Treatment of Uncertainties Associated with PRAs in Risk-Informed Decision-Making, NUREG, Washington, DC, 2017.
- Electric Power Research Institute (EPRI), A Practical Approach for Addressing Uncertainty in Fire Probabilistic Risk Assessment Modeling, EPRI/TR-3002018268, Palo Alto, 2020.
- W.R. Gilks, S. Richardson, D.J. Spiegelhalter, Markov Chain Monte Carlo in Practice, Chapman & Hall, 1996.
- A. Gelman, J.B. Carlin, H.S. Stern, D.B. Dunson, A. Vehtari, D.B. Rubin, Bayesian Data Analysis, third ed., Chapman & Hall, 2013.
- G. Koop, Bayesian Econometrics, Wiley, 2003.
- D.S. Reis, J.R. Stedinger, Bayesian MCMC flood frequency analysis with historical information, J. Hydrol. 313 (1-2) (2005) 97-116, https://doi.org/10.1016/j.jhydrol.2005.02.028.
- Nuclear Regulatory Commission (NRC), Handbook of Parameter Estimation for Probabilistic Risk Assessment, NUREG/CR-6823, Washington, D.C, 2003.
- Y.M. Seo, K.B. Park, Uncertainty analysis for parameters of probability distribution in rainfall frequency analysis by bayesian MCMC and Metropolis Hastings algorithm, J. Environ. Sci. 20 (3) (2011) 329-340, https://doi.org/10.5322/JES.2011.20.3.329.
- C.P. Robert, G. Casella, Monte Carlo Statistical Methods, Springer Verlag, 1999.
- N. Metropolis, A.W. Rosenbluth, M.N. Rosenbluth, A.H. Teller, E. Teller, Equations of state calculations by fast computing machines, J. Chem. Phys. 21 (6) (1953) 1087-1092. https://doi.org/10.1063/1.1699114
- W.K. Hastings, Monte Carlo sampling methods using Markov chains and their applications, Biometrika 57 (1) (1970) 97-109. https://doi.org/10.1093/biomet/57.1.97
- Organization for Economic Cooperation and Development/Nuclear Energy Agency, Collection and Analysis of Fire Events (2010-2013)-Extensions in the Database and Applications, 14, NEA/CSNI/R. (OECD/NEA), 2015.
- B.B. Anjullo, T.T. Haile, A bayesian binary logistic regression approach in identifying factors associated with exclusive breastfeeding practices at arba minch town, south Ethiopia, Adv. Res. 17 (5) (2018) 1-14, https://doi.org/10.9734/AIR/2018/46020.
- I. Ntzoufras, Bayesian Modeling Using WinBUGS, John Wiley & Sons, 2009, https://doi.org/10.1002/9780470434567.
- M.S. Oh, Bayesian Data Analysis Using JAGS, Free academy, Paju, 2019.
- A. Gelman, D.B. Rubin, Inference from iterative simulation using multiple sequences, Stat. Sci. 7 (4) (1992) 457-472, https://doi.org/10.1214/ss/1177011136.
- S.P. Brooks, A. Gelman, General methods for monitoring convergence of iterative simulations, J. Comput. Graph Stat. 7 (4) (1998) 434-455, https://doi.org/10.1080/10618600.1998.10474787.
- M.K. Cowles, B.P. Carlin, Markov chain Monte Carlo convergence diagnostics: a comparative review, J. Am. Stat. Assoc. 91 (434) (1996) 883-904, https://doi.org/10.1080/01621459.1996.10476956.
- Y. He, A Probabilistic Model of Benefit-Cost Analysis for Highway Construction Projects, Purdue University Master Of Science Dissertation, West, Lafayette, Ind, 2015.
- Nuclear Regulatory Commission (NRC), Refining and Characterizing Heat Release Rates from Electrical Enclosures during Fire (RACHELLE-FIRE): 1, Peak Heat Release Rates and Effect of Obstructed Plume, NUREG-2178, Washington, DC, 2016.