Reloading pattern optimization of VVER-1000 reactors in transient cycles using genetic algorithm

The present paper proposes application of the genetic algorithm (GA) and the innovative weighting factor method to optimize the reloading pattern of Bushehr VVER-1000 reactor in the second cycle. To estimate the composition of fuel assemblies remaining from the first cycle and precisely calculate the objective parameters of each reloading pattern in the second cycle, coupling of WIMSD5-B and CITATION-LDI2 codes in the neutronic section and the WERL code in the thermo-hydraulic section was employed. Optimization of the reloading patterns was carried out in two states. To meet the mentioned objective, with application of the weighting factor method in the first state, the type and quantity of the loadable fresh assemblies were determined to enable the reactor core to maintain the core criticality over the entire cycle length. Afterwards, the genetic algorithm was used to optimize the reloading pattern of the reactor to obtain an arrangement with flat radial power distribution. In the second state, the optimization algorithm was free to select the type and number of fresh fuel assemblies to be able to search for an arrangement with the maximum effective multiplication factor and the safe power peaking factor. In addition, in order to ensure the safety and desirability of the proposed patterns in both states, a time-dependent examination of the thermo-neutronic behavior of the reactor core was carried out during the second cycle. With consideration of the new solutions proposed in this research to increase the precision, speed, and scope of the searches and the structural constraints on reloading pattern optimization calculations, it seems that the present paper is a novel step toward the optimization of the reloading patterns of nuclear reactors.