Geometrical shape optimization of a cold neutron source using artificial intelligence strategies

A new approach is developed for optimizing the geometrical shape of a cold neutron source to maximize its cold neutron outward leakage. An analogy is drawn between the shape optimization problem and a state space search, which is the fundamental problem in Artificial Intelligence applications. The new optimization concept is implemented in the computer code DAIT in which the physical model is represented by a two group, r-z geometry nodal diffusion method, and the state space search is conducted via the Nearest Neighbor algorithm. The accuracy of the nodal diffusion method solution is established on meshes of interest, and is shown to behave qualitatively the same as transport theory solutions. The dependence of the optimum shape and its value on several physical and search parameters is examined via numerical experimentation. 10 refs., 6 figs., 2 tabs