Multi objective loading pattern optimization of PWRs with Fuzzy logic controller based Gravitational Search Algorithm

The multi objective Loading Pattern Optimization (LPO) is one of the most important concerns for the incore design of nuclear reactors. Hence, different techniques have been presented for optimization of incore patterns for nuclear reactors, this paper presents a new optimization technique, which uses Fuzzy Logic Controller (FLC) for solving multi-objective optimization problems. In this work, using the FLC, the gravity constant of the Gravitational Search Algorithm (GSA) is controlled to reach better optimization results and convergence rate. A well-designed loading pattern of fuel assemblies in a reactor core depends on Neutronics and Thermal-Hydraulics (NTH) aspects, simultaneously. In this way, for multi-objective optimization, the NTH parameters are included in the fitness function. Neutronic goals are focused on multiplication factor, power peaking factor, and power density and for TH, fuel temperature and critical heat flux are considered. In the present investigation, for evaluating the Fuzzy Gravitational Search Algorithm (FGSA), four cases have been studied. At the first step, to demonstrate the performance of proposed algorithm, the Ackley and Shekel Foxholes functions have been studied. In the next step, the FGSA algorithm with a multi-objective fitness function has been applied for two PWR reactors. For the NTH calculations, valid codes have been executed in searching iterations. The results reveal that convergence rate of the FGSA method is quite promising. Also, the FGSA improves the quality of multi objective LPO in average and could be accounted as a trustworthy method.