Multicycle Fuel Loading Pattern Optimization by Multiobjective Simulated Annealing Employing Adaptively Constrained Discontinuous Penalty Function

The multiobjective simulated annealing (MOSA)–based fuel assembly loading pattern (LP) optimization method, employing the discontinuous penalty function (DPF), is extended for multicycle applications by introducing an adaptively constrained discontinuous penalty function (ACDPF). A discontinuous point in the penalty function is adaptively shifted to a better direction during the course of MOSA such that the search can be more efficient. The advantages of the ACDPF-based MOSA algorithm over the original DPF-based algorithm are first examined with a real single-cycle LP optimization problem of an operating reactor, as well as with a simple LP optimization problem that has known solutions. A direct multicycle LP optimization method is then formulated with an application to the first four cycles of the Younggwang Nuclear Unit 4 (YGN4) core. The rearrangement method is devised as a fuel shuffling method that can avoid drastic changes in the LPs of the subsequent cycles of a seed cycle. It is demonstrated that the ACDPF-based MOSA combined with the rearrangement method produces quite effectively the optimum LP sets for the four cycles, which outperform the LPs generated by a series of cyclewise optimizations as well as the actual LPs of YGN4 that were already used in the plant.