Exploration of Key Parameter Ranking for CANDU Fuel Performance Assessment Using GRS Uncertainty Method

Abstract

CANDU fuel performance can be simulated with fuel computer codes, such as ELESTRES for fuel under normal operating conditions. In the simulations, a significantly large number of input parameters are required to represent the fuel geometry, material properties, and operating conditions. This paper presents exploration results of using GRS uncertainty method infuel analysis, which are tentatively used to explore the impact of key input parameter identification and ranking based on the output of fuel centerline temperature. With the GRS uncertainty method,the key parameter identification and ranking could be assessed covering the parameter variation ranges. Hence, an adequate selection of input parameters can be made in the code application tohave fuel performance improvements and to assess the limiting fuel behaviour with reasonable conservative.