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Application of Chernoff bound to passive system reliability evaluation for probabilistic safety assessment of nuclear power plants

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초록

There is an increasing interest in passive safety systems to minimize the need for operator intervention or external power sources in nuclear power plants. Because a passive system has a weak driving force, there is greater uncertainty in the performance compared with an active system. In previous studies, several methods have been suggested to evaluate passive system reliability, and many of them estimated the failure probability using thermalehydraulic analyses and the Monte Carlo method. However, if the functional failure of a passive system is rare, it is difficult to estimate the failure probability using conventional methods owing to their high computational time. In this paper, a procedure for the application of the Chernoff bound to the evaluation of passive system reliability is proposed. A feasibility study of the procedure was conducted on a passive decay heat removal system of a micro modular reactor in its conceptual design phase, and it was demonstrated that the passive system reliability can be evaluated without performing a large number of thermalehydraulic analyses or Monte Carlo simulations when the system has a small failure probability. Accordingly, the advantages and constraints of applying the Chernoff bound for passive system reliability evaluation are discussed in this paper

Abstract

There is an increasing interest in passive safety systems to minimize the need for operator intervention or external power sources in nuclear power plants. Because a passive system has a weak driving force, there is greater uncertainty in the performance compared with an active system. In previous studies, several methods have been suggested to evaluate passive system reliability, and many of them estimated the failure probability using thermalehydraulic analyses and the Monte Carlo method. However, if the functional failure of a passive system is rare, it is difficult to estimate the failure probability using conventional methods owing to their high computational time. In this paper, a procedure for the application of the Chernoff bound to the evaluation of passive system reliability is proposed. A feasibility study of the procedure was conducted on a passive decay heat removal system of a micro modular reactor in its conceptual design phase, and it was demonstrated that the passive system reliability can be evaluated without performing a large number of thermalehydraulic analyses or Monte Carlo simulations when the system has a small failure probability. Accordingly, the advantages and constraints of applying the Chernoff bound for passive system reliability evaluation are discussed in this paper

참고문헌 (41)

  1. Progress in Methodologies for the Assessment of Passive Safety System Reliability in Advanced in Advanced Reactors, "IAEA", International Atomic Energy Agency, ~, pp.IAEA-TECDOC-1752 (2014)
  2. Arun Kumar Nayak, "review: passive safety system reliability analysis e accomplishments and unresolved issues", Front. Energy Res, 2, pp.1~14 (2014)[DOI]
  3. E. Zio, "How to effectively compute the reliability of a thermalhydraulic nuclear passive system", Nucl. Eng. Des, 241(1), pp.310~327 (2011)
  4. A. K. Nayak, "Passive system reliability analysis using the APSRA methodology", Nucl. Eng. Des, 238(6), pp.1430~1440 (2008)
  5. Best-estimate Calculations of Emergency Core Cooling System Performance, Regulatory Guide 1.157, "USNRC", U.S. Nuclear Regulatory Commission, ~ (1989)
  6. Andrej Prosek, "Review of best estimate plus uncertainty methods of thermal-hydraulic safety analysis", Proceedings of the International Conference Nuclear Energy for New Europe (2003)
  7. B. E. Boyack, "Quantifying the reactor safety margins part 1: an overview of the code scaling, applicability, and uncertainty evaluation methodology", Nucl. Eng. Des, 119(1), pp.1~15 (1990)
  8. Seola Han, "Numerical experiments on order statistics method based on Wilks' formula for best-estimate plus uncertainty methodology", J. Environ. Manag, 235(1), pp.28~33
  9. Horst Glaeser, "GRS method for uncertainty and sensitivity evaluation of code results and applications", Sci. Technol. Nuclr. Install (2008)
  10. S. S. Wilks, "Determination of sample sizes for setting tolerance limits", Ann. Math. Stat, 12(No. 1), pp.91~96 (1941)
  11. Dong Gu Kang, "Analysis of LBLOCA using best estimate plus uncertainties for three-loop nuclear power uprate", Ann. Nucl. Energy, 90, pp.318~330 (2016)
  12. Luciano Burgazzi, "Reliability evaluation of passive systems through functional reliability assessment", Nucl. Technol, 144(2) (2003)
  13. Jalil Jafaria, "Hossein Kazeminejad, Hadi Davilu, Reliability evaluation of a natural circulation system", Nucl. Eng. Des, 224(1), pp.79~104 (2003)
  14. Michel Marqu"es, "Methodology for the reliability evaluation of a passive system and its integration into a probabilistic safety assessment", Nucl. Eng. Des, 235(24), pp.2612~2631 (2005)
  15. E. Zio, "Estimation of the functional failure probability of a thermalhydraulic passive system by Subset Simulation", Nucl. Eng. Des, 239(3), pp.580~599 (2009)
  16. E. Zio, "An optimized Line Sampling method for the estimation of the failure probability of nuclear passive systems", Reliab. Eng. Syst. Saf, 95(Issue 12), pp.1300~1313 (2010)
  17. Christoper J. Fong, "Reliability analysis of a passive cooling system using a response surface with an application to the flexible conversion ratio reactor", Nucl. Eng. Des, 239(12), pp.2660~2671 (2009)
  18. Hyeonmin Kim, "The Generation of Failure Surface for Reliability Assessment of Passive Safety Systems Using Deep Learning Technology", Transactions of the Korean Nuclear Society Spring Meeting (2019)
  19. Ferson Scott, "What Monte Carlo methods cannot do,” human and ecological risk assessment", Int. J, 2(4) (1996)
  20. Introduction to Probability, Statistics, and Random Process, "H. Pishro-Nik", Kappa Research LLC, ~ (2014)
  21. H. Touchette, "The large deviation approach to statistical mechanics", Phys. Rep, 478(1-3), pp.1~69 (2009)
  22. M. Mitzenmacher, "Probability and Computing: Randomized and Probabilistic Techniques in Algorithms and Data Analysis" (2017), Cambridge University Press
  23. Rajmund Drenyovszki, "Power system reliability assessment based on Large Deviation Theory bounds", 2016 IEEE International Energy Conference (ENERGYCON) (2016)
  24. Rajmund Drenyovszki, "On the convexity of Chernoffbound in the context of consumption admission in smart grids", International Conference on Smart Systems and Technologies (SST) (2016)
  25. Samprit Chatterjee, "Regression Analysis by Example" (2012), John Wiley &Sons
  26. Literature Review of Methods for Representing Uncertainty, "Enrico Zio", Foundation for an Industrial Safety Culture, ~ (2013)
  27. Gerald J. Hahn, "Sample sizes for Monte Carlo simulation", IEEE Transact. Syst. Man Cybern, (5), pp.678~680 (1972)[DOI]
  28. ChernoffHerman, "A measure of asymptotic efficiency for tests of a hypothesis based on the sum of observations", Ann. Math. Stat, 23(4), pp.493~207 (1952)
  29. Sarah Kang, "Sensitivity and uncertainty analysis for ULOF of PGSFR using PAPIRUS", Ann. Nucl. Energy, 110, pp.1232~1241 (2017)
  30. Seong Gu Kim, "A concept design of supercritical CO2 cooled SMR operating at isolated microgrid region", Int. J. Energy Res, 41(4), pp.512~525 (2017)
  31. Bong Seong Oh, "Safety evaluation of supercritical CO2 cooled micro modular reactor", Ann. Nucl. Energy, 110, pp.1202~1216 (2017)
  32. Seok-Jung Han, "A quantitative evaluation of reliability of passive systems within probabilistic safety assessment framework for VHTR", Ann. Nucl. Energy, 37(3), pp.345~358 (2010)
  33. 소은서, "Level 1 probabilistic safety assessment of supercritical – CO 2 – cooled micro modular reactor in conceptual design phase", Nuclear Engineering and Technology, 53(2), pp.498~508 (2021), 한국원자력학회[DOI]
  34. Basic Safety Principles for Nuclear Power Plants 75-INSAG-3 Rev.1”, INSAG-12, "IAEA", International Atomic Energy Agency, ~ (1999)
  35. Rates of Initiating Events at U.S. Nuclear Power Plants: 1987-1995, "USNRC", United States Nuclear Regulatory Commission, ~, pp.NUREG (1998), CR-5750
  36. Industry-averaged Performance for Components and Initiating Events at U.S. Commercial Nuclear Power Plants, "USNRC", United States Nuclear Regulatory Commission, ~, pp.NUREG (2007), CR-6928
  37. Ho-Gon Lim, "MOSAIQUE e a network based software for probabilistic uncertainty analysis of computerized simulation models", Nucl. Eng. Des, 241(5), pp.1776~1784 (2011)
  38. J. C. Helton, "Latin hypercube sampling and the propagation of uncertainty in analyses of complex systems", Reliabil. Eng. Syst. Reliabil, 81(1), pp.23~69 (2003)
  39. Theory Manual, "H. S. Lim", Korea Atomic Energy Research institute, ~, pp.KAERI (2014), TR-5728[DOI]
  40. Bong Seong Oh, "Safety Analysis and Development of Control Logic of KAIST Micro Modular Reactor with GAMMAþ Code", MS, pp.2016
  41. I. Andre, "Khuri and siuli mukhopadhyay, “response surface methodology", pp.128~149 (2010), Wiley

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