PWR fuel management optimization using neural networks

This paper presents a new method to solve the problem of finding the best configuration of fuel assemblies in a pressurized water reactor (PWR) core. Finding the optimum solution requires a huge amount of calculations in classical methods. It has been shown that the application of continuous Hopfield neural network accompanied by simulated annealing method to this problem not only reduces the amount of calculations, but also guarantees finding the best solution. In this study flattening of neutron flux inside the reactor core of Bushehr NPP is considered as the objective function. The result is the optimum configuration which is in agreement with the pattern proposed by the designer.