Evaluation Result of PIRT Methodology for Fire Modeling

One of sensitive items for the fire risk analysis with fire models is the major effect of input data to modeling result. If input factors are influential to the output of the program, their reliability must be appraised at the initial stage of design. In addition to the importance of input data, modeling itself should be reviewed by the verification and validation process. As shown in NUREG-1824, EPRI and NRC already verified the mathematical solution of the governing equations for CFAST and FDS. However, the validation of fire modeling must be done to quantify uncertainties originated from the physical approximation and immature capabilities of the program designer. A way to reduce uncertainties of fire modeling is to compare the predicted values by fire models and the experimental results.One of the ways to upgrade the fire modeling credibility is to find out what sort of phenomenon is important at fire scenarios and how much the fire model is adequate to the real fire situations. In this purpose, we studied PIRT to apply to fire modeling tools and PIRT means Phenomena Identification Ranking Table which has been used to assess the code scaling, applicability, and uncertainty (CSAU) by NRC. When fire models are used to simulate the real fire situation, it is important to identify the critical input data and effective factors to modeling output. At this study, it was confirmed that the fire modeling in NPPs can be implemented by the representative six types of fire scenarios and major fire phenomena which was originated from the baseline fire scenarios. The expert panel also determined the most important sub-phenomenon of fire in major fire situation. One of most valuable output at this study is the list of ranking table for the key parameters. By use of this result, the fire modeling practices in NPPs can be more upgraded with enhanced credibility