Evaluation of applying axial variation of enrichment distribution method and radial variation of enrichment distribution in VVER/1000 reactor using a Hopfield neural network to optimize fuel management

In this present work the analysis technique was developed to find the optimum core configuration by applying neural network. This work investigates an appropriate way to solve the problem of optimizing fuel management in VVER/1000 reactor. To automate this procedure, a computer program has been developed.This program suggests an optimal core configuration which is determined to establish safety constraints. The suggested solution is based on the use of coupled programs, which one of them is the nuclear code, for making a database and modeling the core, and another one is Hopfield Neural Network Artificial (HNNA).The first stage of computational procedure consists of creating the cross section database and calculating neutronic parameters by using WIMSD4 and CITATION codes. The second one, consists of finding the optimum core loading pattern by applying the primary fuel assemblies of the VVER/1000 reactor core, using the HNNA method that based on minimizing power peaking factor (PPF) and maximizing the effective multiplication factor (keff). In the third second one, we apply a heuristic method to flat the flux core and decreasing the power peaking factor of the core. It consists of finding the best axial and radial variation of enrichment distribution to reach an optimum core loading pattern, by using HNNA and the cross section database.Finally, we compared obtained results of these methods to obtained results of the primary core, Suggested pattern of the Russian contractor.In total, the results show that applying the HNNA led us to the appropriate PPF and keff. Therefore, we achieved to a set of two basic parameters PPF and keff as effective factors on satisfying the safety constraints of VVER/1000 reactor core. It should be mentioned to say that the obtained results of HNNA suggested pattern is promising.Therefore, these methods ultimately eventuated to find the optimum configuration for VVER/1000 reactor core.