This dissertation develops a core management to ol called RELOAD-M capable of optimizing reactor-core fuel loadings for MYRRHA, the future fast-spectrum research facility currently under development at SCK• CEN, Belgium. Such a tool is needed for designing highly efficient loading patterns that reflect various performance objectives of the multipurpose machine. RELOAD-M can solve the single-cycle loading pattern optimization problem, using different metaheuristic optimization methods and reactor analysis codes. Two iterative population-based metaheuristics are implemented to solve the loading pattern optimization problem: Genetic Algorithm (GA) (with or without elitism) and Ant Colony Optimization (ACO). Both methods are applied to a simple core-reload problem with a known global optimum and the optimization results are compared. It is found that the elitist GA gives the most consistent results and performs best. MYRRHA reactor-core models are described and used for the neutronics evaluation of different loading patterns by reactor analysis codes tailored to fast-spectrum systems. A simple thermal-hydraulics module is implemented for the calculation of the maximum fuel-cladding temperature. All employed models give results that are sufficiently accurate and fast enough for optimization purposes.
|Place of Publication
|Published - 2 Feb 2015