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Uncertainty analysis of containment dose rate for core damage assessment in nuclear power plants

  • Wu, Guohua (Institute of Nuclear and New Energy Technology, Tsinghua University) ;
  • Tong, Jiejuan (Institute of Nuclear and New Energy Technology, Tsinghua University) ;
  • Gao, Yan (China Ship Development and Design Center) ;
  • Zhang, Liguo (Institute of Nuclear and New Energy Technology, Tsinghua University) ;
  • Zhao, Yunfei (Institute of Nuclear and New Energy Technology, Tsinghua University)
  • Received : 2017.10.15
  • Accepted : 2018.02.19
  • Published : 2018.06.25

Abstract

One of the most widely used methods to estimate core damage during a nuclear power plant accident is containment radiation measurement. The evolution of severe accidents is extremely complex, leading to uncertainty in the containment dose rate (CDR). Therefore, it is difficult to accurately determine core damage. This study proposes to conduct uncertainty analysis of CDR for core damage assessment. First, based on source term estimation, the Monte Carlo (MC) and point-kernel integration methods were used to estimate the probability density function of the CDR under different extents of core damage in accident scenarios with late containment failure. Second, the results were verified by comparing the results of both methods. The point-kernel integration method results were more dispersed than the MC results, and the MC method was used for both quantitative and qualitative analyses. Quantitative analysis indicated a linear relationship, rather than the expected proportional relationship, between the CDR and core damage fraction. The CDR distribution obeyed a logarithmic normal distribution in accidents with a small break in containment, but not in accidents with a large break in containment. A possible application of our analysis is a real-time core damage estimation program based on the CDR.

Keywords

References

  1. C.M. Allison, J.K. Hohorst, An assessment of effectiveness of core exit temperatures with respect to PWR core damage state using RELAP/SCDAPSIM/MOD3.4, Nucl. Eng. Des. 238 (2008) 1547-1560. https://doi.org/10.1016/j.nucengdes.2007.12.011
  2. U.S. Nuclear Regulatory Commission (NRC), Clarification of TMI Action Plan Requirements, NUREG-0737, Nuclear Regulatory Commission, U.S., 1980.
  3. U.S. Westinghouse Electric Company LLC, Westinghouse Owners Group Post Accident Core Damage Assessment Methodology, Westinghouse Electric Company LLC, U.S., 1984.
  4. U.S. Nuclear Regulatory Commission, Modifications Proposed by the Westinghouse Owners Group to the Core Damage Assessment Guidelines and Post Accident Sampling System Requirements, Nuclear Regulatory Commission, U.S., 1999.
  5. T. McKenna, J. Trefethen, K. Gant, et al., RTM-96 (NUREG/BR-0150). Response Technical Manual, vol. 1, Nuclear Regulatory Commission, U.S., 1996.
  6. International Atomic Energy Agency, Generic Assessment Procedures for Determining Protective Actions during a Reactor Accident, IAEA-TECDOC-955, International Atomic Energy Agency, Vienna, 1997.
  7. Y. Zhao, L. Zhang, J. Tong, et al., Development of rapid atmospheric source term estimation system for AP1000 nuclear power plant, Prog. Nucl. Energy 81 (2015) 264-275. https://doi.org/10.1016/j.pnucene.2015.02.008
  8. D. Winter, J.M. Agator, Utilisation of the SESAME system for diagnosis and prognosis of plant status during an emergency in a French PWR, Radiat. Protect. Dosim. 73 (1997) 273-276. https://doi.org/10.1093/oxfordjournals.rpd.a032151
  9. Feng Jun-yi, Tong Jie-juan, Qu Jingyuan, Research and application of SESAME system, Sci. Technol. Rev. 24 (2006) 61-64 (in Chinese).
  10. B.R. Sehgal, Nuclear Safety in Light Water Reactors: Severe Accident Phenomenology, 2012.
  11. Lutz R J. Westinghouse Owners Group Core Damage Assessment Guidance. Pittsburgh: Westinghouse Electric Company LLC.
  12. McGuire S A, Ramsdell J V, Athey G F, 2007. RASCAL 3.0.5: Description of Models and Methods, NUREG-1887. U.S. Nuclear Regulatory Commission, 1999.
  13. U.S. Atomic Energy Commission, Possibilities T. Consequences of Major Accidents in Large Nuclear Power Plants, WASH 740, Atomic Energy Commission, U.S., 1957.
  14. H.W. Lewis, R.J. Budnitz, W.D. Rowe, et al., Reactor Safety Study: an Assessment Accident Risks in U.S. Commercial Nuclear Power Plants, WASH-1400 (NUREG/CR-0400), Nuclear Regulatory Commission, U.S., 1975.
  15. T.J. McKenna, J.G. Giitter, Source Term Estimation during Incident Response to Severe Nuclear Power Plant Accidents, NUREG 1228, Nuclear Regulatory Commission, U.S., 1988.
  16. D. Ross, J. Murphy, M. Cunningham, et al., Severe Accident Risks: an Assessment for Five U.S. Nuclear Power Plants, NUREG-1150, Nuclear Regulatory Commission, U.S, 1990.
  17. L. Soffer, S.B. Burson, C.M. Ferrell, Accident Source Terms for Light-water Nuclear Power Plants, NUREG-1465, Nuclear Regulatory Commission, U.S., 1995.
  18. M. Vela-Garcia, K. Simola, Evaluation of JRC source term methodology using MAAP5 as a fast-running crisis tool for a BWR4 Mark I reactor, Annals of Nuclear Energy 96 (2016) 446-454. https://doi.org/10.1016/j.anucene.2016.06.040
  19. J.F. Li, Z.Q. Shi, X.Y. Wang, PWR containment radiation levels calculation related to core conditions, Nucl. Sci. Eng 24 (2004) 31-35 (in Chinese).
  20. H.N. Jow, W.B. Murfin, J.D. Johnson, XSOR Codes User's Manual, NUREG/ CRd5360, Nuclear Regulatory Commission, U.S., 1993.
  21. Michael D. Shields, Jiaxin Zhang, The generalization of Latin hypercube sampling, Reliability Engineering and System Safety 148 (2016) 96-108. https://doi.org/10.1016/j.ress.2015.12.002
  22. S.A. McGuire, J.V. Ramsdell, G.F. Athey, RASCAL 3.0.5: Description of Models and Methods, NUREG-1887, NRC, U.S., 2007.
  23. F.B. Judith, MCNPea General Monte Carlo Neparticle Transport Code, University of California, U.S, 2000.
  24. U.S. Nuclear Regulatory Commission, The Mesorad Dose Assessment Model, NUREG/CR-4000, Nuclear Regulatory Commission, U.S., 1986.
  25. U.S. Nuclear Regulatory Commission, State-of-the-Art Reactor Consequence Analyses Project, Nuclear Regulatory Commission, 2013.
  26. J.H. Hubbell, S.M. Seltzer, Tables of X-Ray Mass Attenuation Coefficients and Mass Energy-absorption Coefficients from 1 KeV to 20 MeV for Elements Z = 1 to 92 and 48 Additional Substances of Dosimetric Interest, National Institute of Standards and Technology, U.S., 1996.
  27. International Atomic Energy Agency (IAEA), Generic Models and Parameters for Assessing the Environment Transfer of Radionuclides from Routine Releases, International Atomic Energy Agency, Vienna, 1982.
  28. R. Henry, I. Tiselj, L. Snoj, CFD/Monte-Carlo neutron transport coupling scheme, application to TRIGA reactor, Ann. Nucl. Energy 110 (2017) 36-47. https://doi.org/10.1016/j.anucene.2017.06.018
  29. G. Katsiolides, E.H. Muller, R. Scheichl, et al., Multilevel Monte Carlo and Improved Timestepping Methods in Atmospheric Dispersion Modelling, 2016.
  30. R.G. Carpenter, Principles and procedures of statistics with special reference to the biological sciences, Ann. N. Y. Acad. Sci. 682 (1960) 283-295.
  31. A.C. Cameron, F.A.G. Windmeijer, An R-squared measure of goodness of fit for some common nonlinear regression models, J. Econom. 77 (1997) 329-342. https://doi.org/10.1016/S0304-4076(96)01818-0
  32. M. Knochenhauer, V. Hedtjarn Swaling, F. Di Dedda, F. Hansson, S. Sjokvist, K. Sunnegard, Using Bayesian Belief Network (BBN) Modelling for Rapid Source Term Prediction e Final Report, NKS-293, ISBN 978-87-7893-369-0, 2013.
  33. S.Y. Park, K.I. Ahn, SAMEX: a severe accident management support expert, Ann. Nucl. Energy 37 (2010) 1067-1075. https://doi.org/10.1016/j.anucene.2010.04.014
  34. K.I. Ahn, S.Y. Park, Development of a risk-informed diagnostics and prognostics system to support severe accident management, Nucl. Eng. Des 239 (2009) 2119-2133. https://doi.org/10.1016/j.nucengdes.2009.06.001

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