Evaluating the effect of cross-over length and mutation rate variations on the performance of DERMAGA

Abstract

In the CANDU fuel management analysis, snapshots of power and burnup distributions in the core could be obtained by simulating and tracking reactor operation over extended period using various tools such as the ∗SIMULATE module of the reactor fuelling simulation program (RFSP) code. However, for some studies, such as an evaluation of a conceptual design of a next generation CANDU reactor, the quickest approach to obtain a snapshot of the power distribution in the core is based on the patterned-channel-age model implemented in the ∗INSTANTAN module of the RFSP code. Recently an alternative algorithm, called DERMAGA, has been developed for generating patterned-channel-ages to be used by the ∗INSTANTAN module. It has been demonstrated that the DERMAGA algorithm has been used successfully to produce patterned-channel-ages where the maximum channel and bundle powers are close to the values observed during operation. The heart of the DERMAGA algorithm is the Genetic Algorithm (GA) technique. Since there are many user-defined parameters that could be varied for an optimization using the GA technique, the performance of the algorithm could be affected by the choices of these parameters. Some numerical simulations have been conducted to evaluate the robustness of the DERMAGA algorithm against the variations in some of these parameters. The results from evaluating the performance of DERMAGA against the variation in the mutation rates per generation and the cross-over length are presented in this paper.