Fuel management optimization based on power profile by Cellular Automata

Fuel management in PWR nuclear reactors is comprised of a collection of principles and practices required for the planning, scheduling, refueling, and safe operation of nuclear power plants to minimize the total plant and system energy costs to the extent possible. Despite remarkable advancements in optimization procedures, inherent complexities in nuclear reactor structure and strong inter-dependency among the fundamental parameters of the core make it necessary to evaluate the most efficient arrangement of the core. Several patterns have been presented so far to determine the best configuration of fuels in the reactor core by emphasis on minimizing the local power peaking factor ( P q ). In this research, a new strategy for optimizing the fuel arrangements in a VVER-1000 reactor core is developed while lowering the P q 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 P q 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.