DEVELOPMENT OF AN UNCERTAINTY QUANTIFICATION METHOD OF THE BEST ESTIMATE LARGE LOCA ANALYSIS

Abstract

A statistical uncertainty quantification methodology for evaluation ot the emergency core cooling system (ECCS) performance is proposed and applied in assessing the best-estimate peak cladding temperature (PCT). In the proposed methodology, the Latin hypercube sampling method is adopted, and separate model uncertainties are used as input variables. The independency of the input variables is verified through a correlation coefficient test for statistical treatment of their uncertainties. Next, the PCT response distribution is determined through a goodness-of-fit test. Finally, the PCT with a one-sided 95% probability and a confidence level of 0.95 is estimated. This methodology is applied to the large-break loss-of-coolant accident (LBLOCA) of Kori Nuclear Units 3 and 4. This study shows that the proposed methodology is a useful one.