DOI QR코드

DOI QR Code

Multi-unit Level 2 probabilistic safety assessment: Approaches and their application to a six-unit nuclear power plant site

  • Received : 2017.09.20
  • Accepted : 2018.04.03
  • Published : 2018.12.25

Abstract

The risk of multi-unit nuclear power plants (NPPs) at a site has received considerable critical attention recently. However, current probabilistic safety assessment (PSA) procedures and computer code do not support multi-unit PSA because the traditional PSA structure is mostly used for the quantification of single-unit NPP risk. In this study, the main purpose is to develop a multi-unit Level 2 PSA method and apply it to full-power operating six-unit OPR1000. Multi-unit Level 2 PSA method consists of three steps: (1) development of single-unit Level 2 PSA; (2) extracting the mapping data from plant damage state to source term category; and (3) combining multi-unit Level 1 PSA results and mapping fractions. By applying developed multi-unit Level 2 PSA method into six-unit OPR1000, site containment failure probabilities in case of loss of ultimate heat sink, loss of off-site power, tsunami, and seismic event were quantified.

Keywords

References

  1. IAEA, Reference data series No. 2, 2015 edition: nuclear power reactors in the world, Agency Int. At. Energy (2) (2015) 1-86.
  2. Pickard Lowe, Garrick, Inc, in: Seabrook Station Probabilistic Safety Assessment e Section 13.3 Risk of Two Unit Station, Prepared for Public Service Company of New Hampshire, PLG-0300, 1983.
  3. U.S. NRC, "Policy Issue Related to New Plant Licensing and Status of the Technology-neutral Framework for New Plant Licensing," no. September, 2005.
  4. S. Schroer, M. Modarres, An event classification schema for evaluating site risk in a multi-unit nuclear power plant probabilistic risk assessment, Reliab. Eng. Syst. Saf. 117 (2013) 40-51. https://doi.org/10.1016/j.ress.2013.03.005
  5. V. Hassija, C. Senthil Kumar, K. Velusamy, Probabilistic safety assessment of multi-unit nuclear power plant sites - an integrated approach, J. Loss Prev. Process. Ind. 32 (1) (2014) 52-62. https://doi.org/10.1016/j.jlp.2014.07.013
  6. K. Ebisawa, T. Teragaki, S. Nomura, H. Abe, M. Shigemori, M. Shimomoto, Concept and methodology for evaluating core damage frequency considering failure correlation at multi units and sites and its application, Nucl. Eng. Des. 288 (2015) 82-97. https://doi.org/10.1016/j.nucengdes.2015.01.002
  7. C.S. Kumar, V. Hassija, K. Velusamy, V. Balasubramaniyan, Integrated risk assessment for multi-unit NPP sites - a comparison, Nucl. Eng. Des. 293 (2015) 53-62. https://doi.org/10.1016/j.nucengdes.2015.06.025
  8. S. Zhang, J. Tong, J. Zhao, An integrated modeling approach for event sequence development in multi-unit probabilistic risk assessment, Reliab. Eng. Syst. Saf. 155 (2016) 147-159. https://doi.org/10.1016/j.ress.2016.07.008
  9. T.D. Le Duy, D. Vasseur, E. Serdet, Probabilistic Safety Assessment of twin-unit nuclear sites: methodological elements, Reliab. Eng. Syst. Saf. 145 (2016) 250-261. https://doi.org/10.1016/j.ress.2015.07.014
  10. I.S. Kim, M. Jang, S.R. Kim, Holistic approach to multi-unit site risk assessment: status and issues, Nucl. Eng. Technol. 49 (2) (2017) 286-294. https://doi.org/10.1016/j.net.2017.01.003
  11. M. Prasad, G. Vinod, A.J. Gaikwad, A. Ramarao, Site core damage frequency for multi-unit Nuclear Power Plants site, Prog. Nucl. Energy 96 (2017) 56-61. https://doi.org/10.1016/j.pnucene.2016.12.007
  12. K. Oh, S.H. Han, J.H. Park, H.-G. Lim, J.E. Yang, G. Heo, Study on quantification method based on Monte Carlo sampling for multi-unit probabilistic safety assessment models, Nucl. Eng. Technol. 49 (4) (2017) 710-720. https://doi.org/10.1016/j.net.2016.12.009
  13. M. Modarres, T. Zhou, M. Massoud, "Advances in multi-unit nuclear power plant probabilistic risk assessment, Reliab. Eng. Syst. Saf. 157 (2017) 87-100. https://doi.org/10.1016/j.ress.2016.08.005
  14. D.-S. Kim, S.H. Han, J.H. Park, H.-G. Lim, J.H. Kim, Multi-unit Level 1 probabilistic safety assessment: Approaches and their application to a six-unit nuclear power plant site, Nucl. Eng. Technol. 50 (2018) 1217-1233. https://doi.org/10.1016/j.net.2018.01.006
  15. S.-Y. Kim, Y.H. Jung, S.H. Han, S.-J. Han, H.-G. Lim, Multi-unit Level 3 probabilistic safety assessment: Approaches and their application to a six-unit nuclear power plant site, Nucl. Eng. Technol. 50 (2018) 1246-1254. https://doi.org/10.1016/j.net.2018.09.019
  16. S.H. Han, K. Oh, H.-G. Lim, J.-E. Yang, AIMS-MUPSA software package for multi-unit PSA, Nucl. Eng. Technol. 50 (2018) 1255-1265. https://doi.org/10.1016/j.net.2018.06.012
  17. IAEA, Safety Series SSG-4: Development and Application of Level 2 Probabilistic Safety Assessment for Nuclear Power Plants, 2010.

Cited by

  1. AIMS-MUPSA software package for multi-unit PSA vol.50, pp.8, 2018, https://doi.org/10.1016/j.net.2018.06.012
  2. Multi-unit risk assessment of nuclear power plants: Current status and issues vol.50, pp.8, 2018, https://doi.org/10.1016/j.net.2018.09.010
  3. Multi-unit Level 3 probabilistic safety assessment: Approaches and their application to a six-unit nuclear power plant site vol.50, pp.8, 2018, https://doi.org/10.1016/j.net.2018.09.019
  4. Development of logical structure for multi-unit probabilistic safety assessment vol.50, pp.8, 2018, https://doi.org/10.1016/j.net.2018.10.012
  5. Investigating the Effect of Prior Distributions on Posterior Estimates of Common Cause Failure Parameters Using Bayesian Method vol.6, pp.3, 2018, https://doi.org/10.1115/1.4045803
  6. A Method to Avoid Underestimated Risks in Seismic SUPSA and MUPSA for Nuclear Power Plants Caused by Partitioning Events vol.14, pp.8, 2021, https://doi.org/10.3390/en14082150
  7. Probability subtraction method for accurate quantification of seismic multi-unit probabilistic safety assessment vol.53, pp.4, 2021, https://doi.org/10.1016/j.net.2020.09.022
  8. A preliminary site risk assessment vol.58, pp.7, 2018, https://doi.org/10.1080/00223131.2021.1879687
  9. Multi-unit nuclear power plant probabilistic risk assessment: A comprehensive survey vol.213, pp.None, 2021, https://doi.org/10.1016/j.ress.2021.107782