A Phenomena Identification and Ranking Table (PIRT) Exercise for Nuclear Power Plant Fire Modeling Applications (NUREG/CR-6978)

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Publication Information

Manuscript Completed: December 2007
Date Published: November 2008

Prepared by:
T.J. Olivier, S.P. Nowlen

Sandia National Laboratories
Risk and Reliability Analysis Department 6761
P.O. Box 5800
Albuquerque, NM 87185

J. Dreisbach, D. Stroup, NRC Project Managers

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

NRC Job Code N6374

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This report documents the results of a Phenomena Identification and Ranking Table (PIRT) exercise performed for nuclear power plant (NPP) fire modeling applications conducted on behalf of the United States Nuclear Regulatory Commission (NRC) Office of Nuclear Regulatory Research (RES). The PIRT exercise is performed via a facilitated expert elicitation process. In this case, the expert panel was comprised of seven international fire science experts. The panel was facilitated by Sandia National Laboratories (SNL). The objective of a PIRT exercise is to identify key phenomena associated with the intended application and to then rank the current state of knowledge relative to each identified phenomenon. The panel is presented with a series of specific fire scenarios, each of which is based on the types of scenarios typically considered in NPP applications. Each scenario includes a figure of merit; that is, a specific goal to be achieved in analyzing the scenario using fire modeling tools. To illustrate, one scenario involved a main control room fire. For this scenario the figure of merit was predicting the time to operator abandonment. Given each scenario, the panel identifies all those related phenomena that are of potential interest to an assessment based on the figure of merit. The phenomena are ranked relative to their importance in predicting the figure of merit. Each phenomenon is then further ranked for the existing state of knowledge and the adequacy of existing modeling tools to predict that phenomenon. The PIRT panel covered several fire scenarios and identified a number of areas potentially in need of further fire modeling improvements. The results are discussed in detail.

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