Nuclear reactor core optimization with Parallel Integer Coded Genetic Algorithm

The operation and fuel management of reactors are of utmost importance. Core performance analysis constitutes an important stage in core fuel management optimization. In this article, a new algorithm for core optimization on safety limitation of nuclear reactors is introduced. A Parallel Integer Coded Genetic Algorithm, PICGA, is applied to obtain the best configuration corresponding to the maximum multiplication factor. The PICGA may utilize two or more search algorithms along sharing their data, synchronously. This procedure makes the optimization search faster and more efficient. The PICGA is coupled with WIMSD4 and PARCS codes. The WIMSD4 and PARCS (Purdue Advanced Reactor Core Simulator) codes are used to calculate the group constants, fuel depletion, power peaking factors (PPFs) and corresponding effective multiplication factor, Keff. Implementation of the algorithm has been carried out in MATLAB for two reactor test cases, Tehran Research Reactor (TRR) and Bushehr Nuclear Power Plant (BNPP). Using the PICGA, we obtained new core pattern for TRR. Obtaining a configuration for Bushehr Nuclear Power Plant, which maximizes effective multiplication factor increment, is a test case to validate the procedure.