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Modeling Characteristics of an Operational Probabilistic Safety Assessment (PSA)

[+] Author Affiliations
Richard C. Anoba

Anoba Consulting Services, LLC, Pacifica, CA

Yehia Khalil

Dominion Nuclear Connecticut, Waterford, CT

J. J. Fluehr, III

Omaha Public Power District, Omaha, NE

Richard Kellogg, Alan Hackerott

Omaha Public Power District, Blair, NE

Paper No. ICONE10-22010, pp. 1-10; 10 pages
doi:10.1115/ICONE10-22010
From:
  • 10th International Conference on Nuclear Engineering
  • 10th International Conference on Nuclear Engineering, Volume 2
  • Arlington, Virginia, USA, April 14–18, 2002
  • Conference Sponsors: Nuclear Engineering Division
  • ISBN: 0-7918-3596-0 | eISBN: 0-7918-3589-8
  • Copyright © 2000 by ASME

abstract

Probabilistic Safety Assessments (PSAs) are increasingly being used as a tool for supporting the acceptabilty of design, procurement, construction, operation, and maintenance activities at nuclear power plants. Since the issuance of Generic Letter 88-20 [1] and subsequent Individual Plant Examinations (IPEs)/Individual Plant Examinations for External Events (IPEEEs) [2], the NRC has issued several Regulatory Guides such as RG 1.182 [3] to describe the use of PSA in risk informed regulation activities. The PSA models developed for the IPEs were typically based on a “snapshot” of the the risk profile at the nuclear power plant. The IPE models contain implicit assumptions and simplifications that limit the ability to realistically assess current issues. For example, IPE modeling assumptions related to plant configuration limit the ability to perform online equipment out-of-service assessments. The lack of model symmetry results in skewed risk results. IPE model simplifications related to initiating events have resulted in non-conservative estimates of risk impacts when equipment is removed from service. The IPE models also do not explicitly address all external events that are potentially risk significant as equipment is removed from service.

Copyright © 2000 by ASME
Topics: Safety , Modeling

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