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A statistical analysis methodology based on the code scaling, applicability and uncertainty (CSAU) evaluation approach for predicting the safety margin in case of a postulated large-break loss-of-coolant accident (LBLOCA) in a pressurized-water reactor (PWR) was developed by AREVA. All expected LBLOCA phenomena are listed in the Phenomena Identification and Ranking Table (PIRT) and are prioritized according to their importance on the figure of merit, here the fuel rod peak cladding temperature (PCT). For the high-ranked phenomena parameters are identified, which allow a quantification of the analysis uncertainty. AREVA has updated the PIRT to the state of the art and extended it to the application to pressurized-water reactors with combined emergency core cooling injection of German-type PWRs. This paper describes how the uncertainty distributions, required for a statistical analysis, have been derived and presents the result of an exemplary statistical analysis for a German-type 4-loop plant compared to that of a conservative deterministic analysis.

Statistical Large-Break LOCA analysis for PWRs with combined ECC injection