DEVELOPMENT OF STATISTICAL CORE THERMAL DESIGN METHODOLOGY USING A MODIFIED LATIN HYPERCUBE SAMPLING METHOD

Abstract

A statistical core thermal design methodology for generating the limit departure from nucleate boiling ratio (DNBR) is proposed and used in assessing the best-estimate thermal margin in a reactor core. This new methodology adopts a modified Latin hypercube sampling method. In this method, the independencies of the input variables are verified through a correlation coefficient test for statistical treatment of their uncertainties. Next, the DNBR response distribution is determined through a goodness-of-fit test. Finally, a limit DNBR with a one-sided 95% probability and a confidence level of 0.95 is estimated. This methodology is simpler than the conventional statistical method using the response surface and Monte Carlo simulation technique, but it maintains the same level of confidence in the limit DNBR result. This methodology is applied to the Yonggwang Nuclear Units 3 and 4 reactor cores using preliminary design data. From this study, it is deduced that the proposed methodology is useful for design application.