United States Nuclear Regulatory Commission - Protecting People and the Environment

Compendium of Analyses to Investigate Select Level 1 Probabilistic Risk Assessment End-State Definition and Success Criteria Modeling Issues (NUREG/CR-7177, ERI/NRC 13-210)

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Publication Information

Manuscript Completed: June 2013
Date Published: May 2014

Prepared by:
1A. Krallbr
1P. Sawant
1S. Choi
1M. Khatib-Rahbar
2 D. Helton

1Energy Research, Inc.
P. O. Box 2034
Rockville, MD 20847

2U.S. Nuclear Regulatory Commission

D. Helton, NRC Project Manager

NRC Job Code V6219

Prepared for:
Office of Nuclear Regulatory Research
U. S. Nuclear Regulatory Commission
Washington, DC 20555-0001

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Abstract

As part of the routine development, maintenance, and application of the US Nuclear Regulatory Commission's (NRC's) risk tools, assumptions are made with respect to how nuclear power plant accidents will be represented. The NRC conducts research, and performs analyses, to investigate the adequacy of these assumptions. Recently, the Office of Nuclear Regulatory Research has increased its use of the MELCOR computer code for investigating assumptions related to the success criteria, sequence timing, and end-state definition aspects of Level 1 probabilistic risk assessment (PRA). This report augments the existing collection of contemporary Level 1 PRA success criteria analyses and complements other ongoing work related to success criteria analyses for the Byron Station that will be documented in an upcoming NUREG report.

This report focuses on investigations of (a) the effect of modeling assumptions on key figures-of-merit such as the time of depletion of the refueling water storage tank; (b) the relative conservatism or nonconservatism associated with commonly used and potential core damage surrogates; (c) the time required to arrest fuel heatup if mitigation equipment is recovered following a core heatup; and (d) the comparison of MELCOR to the Modular Accident Analysis Program (MAAP) for characterizing the safety margins of selected PRA sequences through an uncertainty quantification process.

Page Last Reviewed/Updated Thursday, May 29, 2014