Fuel reloads optimization for TRIGA research reactor using Genetic Algorithm coupled with neutronic and thermal-hydraulic codes

Abstract This paper presents a case study of applying Genetic Algorithm (GA) coupled with Monte Carlo N-Particle Transport (MCNP) and PARET codes for thermal-hydraulic safety analysis to optimize the fuel reload TRIGA Mark II Moroccan research reactor. Based on radial distribution 238U burnup ratio inside reactor core, five most burned elements were replaced by others fresh (12 % wt uranium) using Multi-Objective Algorithms (MOGA) method. Three aspects optimization considered in this including 1) maximization effective multiplication factor (Keff), 2) minimization maximum Centre Fuel Temperature (CFT) 3) Departure from Nuclear Boiling Ratio (DNBR). The GA programming process developed work was adapted handle constraints concerning limits successive core configurations (CCs) automatically generated code. MOGA method works an elitist selection based Binary Tournament Selection (BTS) method, modified two-point crossover simple mutation operator. results obtained indicate that can successfully find optimal CC Keff 1.03498, CFT 554 °C DNBR 2.94 when are inserted. variation neutron fluxes respect distance best illustrated.