Basic investigations related to genetic algorithms in core designs

The use of genetic algorithms as a tool to improve nuclear reactor core design optimization is proposed. A method based on genetic algorithms are developed to solve optimization problems that involve cell parameters adjustment. In this paper we address a global optimization approach to nuclear reactor core design problems. In previous work, a great variety of local optimization method have been applied in such a kind of problems. In order to illustrate the performance, we apply the method based on genetic algorithms to two traditional test problems that have been considered in literature. These test problems describe the principal framework of the approach proposed, because they have known optimal solutions. Due to the global exploitation capacity and independence of prior knowledge of the search space characteristics proportioned by the genetic algorithms the application scope was extended. The method was applied to optimize a more complex problem, to which traditional methods do not apply. The goal of this third problem is to minimize the average peak factor in a three enrichment zone reactor by the adjust of the fuel radii, cladding thickness, equivalent radii, the three zone enrichments, fuel material and cladding material. In this case a qualitative analysis of the results is made.