New genetic algorithms (GA) to optimize PWR reactors: Part II: Simultaneous optimization of loading pattern and burnable poison placement for the TMI-1 reactor

Abstract

In this paper, the GARCO–PSU (Genetic Algorithm Reactor Code Optimization–Pennsylvania State University) code simultaneously optimizes the core loading pattern (LP) and the burnable poison (BP) placement in a pressurized water reactor (PWR). The LP optimization and BP placement optimization are interconnected, but it is difficult to solve the combined problem due to its large size. Separating the problem into two sequential steps provides a practical way to solve the problem. However, the result of this method alone may not develop the real optimal solution. GARCO–PSU achieves solving the LP optimization and BP placement optimization simultaneously by developing an innovative genetic algorithm (GA). The classical representation of the genotype has been modified to incorporate in-core fuel management basic knowledge. GARCO has three modes; the first mode optimizes the LP only, the second mode optimizes the LP and BP placement in sequence. The third mode, which optimizes the LP and BP placement simultaneously, is described in this paper. GARCO, as stated in Part I, can be applied to all types of PWR core structures having different geometries with an unlimited number of fuel assembly (FA) types in the inventory.