A PN-based approach along PSO scheme for PWR core reloading patterns optimization

Core performance analysis constitutes an essential phase in core fuel management optimization. The output consists mainly of the neutron flux and core power distributions which are needed for deriving the safety related thermal margins. Based on the results of the core simulation, feasible options of loading patterns and control strategies can be specified within the broader scope. In other words, the output is employed in the logical decisions where the fuel management strategies are determined over a few core cycles. ork is focused on the strategy for obtaining a core reload optimization based on using continuous version of particle swarm optimization, PSO, along PN approximation for core analysis. In the last decades the obstruction one faced to use Boltzmann equation for neutron transport in optimization algorithms, was the formidable requirement of computer storage and running time. Now days, however, development of computer storage and running time make it possible to implement advanced methods for particle transport. In this paper an even-parity spherical harmonic expansion for angular distribution and finite element discretization for space variable is used to treat core analysis of particle swarm optimization. It is illustrated that the increasing spherical expansion of angular flux improves the obtained core loading pattern through PSO algorithm.