Design and optimization of dual-cooled fuel assembly in a 12×12 configuration for NuScale SMR based on neutronic-thermohydraulic parameters using the combined ANN-GA approach

Abstract

The Small Modular Reactors (SMRs) use conventional solid fuels. To increase the safety of SMRs, Dual-Cooled Fuel (DCF) can be used. The DCF with two heat transfer surfaces improves heat removal from the fuel. For the first time, this study investigated the use of DCF in a new fuel assembly configuration for the NuScale reactor. Important neutronic and thermohydraulic (N–Th) parameters are obtained. Finally, the optimal DCF rod in a 12 × 12 configuration for the NuScale reactor has been presented. For this purpose, initially, a DCF assembly in a 12 × 12 configuration was designed for the reactor. The fuel mass, enrichment of 235U, and dimensions of fuel assemblies and the core are kept fixed. Then, 32 types of fuel rods with different internal radii were proposed for this assembly. Each of these fuels was placed separately in the assembly and simulated by neutronic codes under cold-clean and full power conditions. Also, the designed fuels were simulated using Computational fluid dynamics (CFD) software, and important thermohydraulic parameters were obtained. Also, to select the optimal fuel rod, the Artificial Neural Network (ANN) and Genetic Algorithm (GA) coupled method is used. To investigate the optimal DCF effects on N–Th parameters in the NuScale reactor, the reference reactor was also simulated and compared with the results of optimal DCF. As one of the most important results of this study, the fuel rod with an internal radius of 0.413423 cm was introduced as the optimal fuel. Also, optimal fuel reduces the temperature and pressure drop, and increases the Departure from Nucleate Boiling Ratio (DNBR).