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Criticality effect according to axial burnup profiles in PWR burnup credit analysis

  • Kim, Kiyoung (Central Research Institute, Korea Hydro & Nuclear Power Co., Ltd.) ;
  • Hong, Junhee (Chungnam National University)
  • 투고 : 2019.02.20
  • 심사 : 2019.04.10
  • 발행 : 2019.09.25

초록

The purpose of the critical evaluation of the spent fuel pool (SFP) is to verify that the maximum effective multiplication factor ($K_{eff}$) is less than the critical safety limit at 100% stored condition of the spent fuel with the maximum reactivity. At nuclear power plants, the storage standard of spent fuel, ie, the loading curve, is established to prevent criticality from being generated in SFP. Here, the loading curve refers to a graph showing the minimum discharged burnup versus the initial enrichment of spent fuel. Recently, US NRC proposed the new critical safety assessment guideline (DSS-ISG-2010-01, Revision 0) of PWR SFPs and most of utilities in US is following it. Of course, the licensed criterion of the maximum effective multiplication factor of SFP remains unchanged and it should be less than 0.95 from the 95% probability and the 95% confidence level. However, the new guideline is including the new evaluation methodologies like the application of the axial burnup profile, the validation of depletion and criticality code, and trend analysis. Among the new evaluation methodologies, the most important factor that affects $K_{eff}$ is the axial burnup profile of spent fuel. US NRC recommends to consider the axial burnup profiles presented in NUREG-6801 in criticality analysis. In this paper, criticality effect was evaluated considering three profiles, respectively: i) Axial burnup profiles presented in NUREG-6801. ii) Representative PWR axial burnup profile. iii) Uniform axial burnup profile. As the result, the case applying the axial burnup profiles presented in NUREG-6801 showed the highest $K_{eff}$ among three cases. Therefore, we need to introduce a new methodology because it can be issued if the axial burnup profiles presented in NUREG/CR-6801 are applied to the domestic nuclear power plants without any other consideration.

키워드

과제정보

연구 과제 주관 기관 : Korea Institute of Energy Technology Evaluation and Planning

참고문헌

  1. DSS-ISG-2010-01, Final Division of Safety Systems Interim Staff Guidance, "Staff Guidance Regarding the Nuclear Criticality Safety Analysis for Spent Fuel Pools," Revision 0.
  2. J.C. Wagner, M.D. DeHart, C.V. Parks, Recommendations for Addressing Axial Burnup in PWR Burnup Credit Analyses, NUREG/CR-6801 (ORNL/TM-2001/ 273), U.S. Nuclear Regulatory Commission, Office of Nuclear Regulatory Research, Washington, DC, March 2003.
  3. A Comprehensive Modeling and Simulation Suite for Nuclear Safety Analysis and Design. ORNL/TM-2005/39 Version 6.1.
  4. Scale: A Comprehensive Modeling and Simulation Suite for Nuclear Safety Analysis and Design, ORNL/TM-2005/39, Version 6.1, June 2011. Available from: Radiation Safety Information Computational Center at Oak Ridge National Laboratory as CCC-785.
  5. J.C. Dean, R.W. Tayloe Jr., "Guide for Validation of Nuclear Criticality Safety Calculational Methodology," NUREG/CR-6698, Nuclear Regulatory Commission, Washington, DC, January 2001.
  6. Kiyoung Kim, Sungwhan Chung, Development of Evaluation Technology on the Long-Term Integrity of PWR Spent Nuclear Fuel Wet Storage, December 2018, 2018-50003339-전-1324TR.
  7. "Criticality Analysis of the Spent Fuel Storage Racks," Prepared for Korea Power Engineering Company, Inc., HI-2043334 Revision 1, September 2005.
  8. Kiyoung Kim, Development of Evaluation Technology on the Long-Term Integrity of PWR Spent Nuclear Fuel Wet Storage, 2017. KHNP 2017-50003339-전-0482TM.
  9. Kiyoung Kim, Bounding Fuel Type for Criticality Analysis of Dry Storage Cask. KNS Spring Meeting (P03C34), May 2017. Korea Jeju.
  10. J.C. Wagner, M.D. DeHart, Review of Axial Burnup Distribution Considerations for Burnup Credit Calculations. Oak Ridge National Lab, March 2000. ORNL/TM-1999/26.

피인용 문헌

  1. On computing the effective multiplication factor using the ADO method vol.167, 2022, https://doi.org/10.1016/j.anucene.2021.108743