AXIAL: a system for boiling water reactor fuel assembly axial optimization using genetic algorithms

A system named AXIAL is developed based on the genetic algorithms (GA) optimization method, using the 3D steady state simulator code Core-Master-PRESTO (CM-PRESTO) to evaluate the objective function. The feasibility of this methodology is investigated for a typical boiling water reactor (BWR) fuel assembly (FA). The axial location of different fuel compositions is found in order to minimize the FA mean enrichment needed to obtain the cycle length under the safety constraints. Thermal limits are evaluated at the end of cycle using the Haling calculation; the hot excess reactivity and the shutdown margin at the beginning of cycle are also evaluated. The implemented objective function is very flexible and complete, incorporating all the thermal and reactivity limits imposed during fuel design analysis; furthermore, additional constraints can be easily introduced in order to obtain an improved solution. The results show a small improvement in the FA average enrichment obtained with the system related to the reference case that has been studied. The results show that the system converge to an optimal solution, it is observed that the mean fuel enrichment decreases while all the constraints are satisfied. A comparison was also performed using one-point and two-points crossover operator and the results of a sensitivity study for different mutation percentage are also showed.