Fuel management optimization based on power profile by Cellular Automata

In this research, a new strategy for optimizing the fuel arrangements in a VVER-1000 reactor core is developed while lowering the Pq is considered as the main target. For this purpose, a Fuel Quality Factor, Z(r), served to depict the reactor core pattern. Mapping to ideal pattern is tracked over the optimization procedure in which the ideal pattern is prepared with considering the Z(r) constraints and their effects on flux and Pq uniformity. For finding the best configuration corresponding to the desired pattern, Cellular Automata (CA) is applied as a powerful and reliable tool on optimization procedure. To obtain the Z(r) constraints, the MCNP code was used and core calculations were performed by WIMS and CITATION codes. The results are compared with the predictions of a Neural Network as a smart optimization method, and the Final Safety Analysis Report (FSAR) as a reference proposed by the designer.