Optimizing the core loading pattern and fuel composition in a hexagonal small modular nuclear reactor via ANN-PSO approach

• This paper focuses on the redesign and evaluation of the NPM core with hexagonal FAs. • This study investigates the impact of altering the arrangement pattern of FAs and the quantity of gadolinia-containing rods within these assemblies. • The gadolinia concentration was effectively optimized using the Particle Swarm Optimization (PSO) algorithm. • The best model, based on TCs and PPFs, was selected. • The analysis findings revealed significant improvements in safety parameters for optimal core loading pattern with optimized gadolinia (Gd 2 O 3 ) Concentration. Small Modular Reactors (SMRs), such as the NuScale Power Module (NPM), have gained considerable attention in recent years. However, significant efforts are needed to enhance safety. The utilization of hexagonal Fuel Assemblies (FAs) offers numerous benefits from both neutronic and thermal-hydraulic perspectives. By leveraging these advantages, reactors performance can be improved without compromising safety regulations. Additionally, there has been consideration given to the use of burnable neutron absorbers, such as gadolinia, in novel nuclear fuels. This paper focuses on the redesign and evaluation of the NPM core with hexagonal FAs. The study investigates the impact of altering the arrangement pattern of FAs and the quantity of gadolinia-containing rods within these assemblies. Various models featuring hexagonal FAs, containing different mixed fuels, were tested through a series of simulations. Calculations were repeated under both Clean-Cold and Hot Full Power (HFP) conditions for each model. To examine different aspects of reactor performance, the concentration of the gadolinia absorber was varied, and its impact on parameters such as Temperature Coefficients (TCs), Power Peaking Factors (PPFs), and excess reactivity was investigated. The investigation involved simulations using the WIMS and CITATION neutronic calculation codes. The gadolinia concentration was effectively optimized using the Particle Swarm Optimization (PSO) algorithm. The best model, based on TCs and PPFs, was selected. The analysis findings revealed significant improvements in safety parameters such as TCs and PPFs for optimal core loading pattern with optimized gadolinia (Gd 2 O 3 ) Concentration.