AUTOMATED FUEL MANAGEMENT OPTIMIZATION FOR FAST REACTORS

Abstract

The Versatile Test Reactor (VTR) is expected to operate in a persistent non-equilibrium state due to inter-cycle variations in experimental loading. The goal of planning and optimizing the fuel loading for this mode of operation can differ from equilibrium cycle optimization. In this work, a general algorithm for optimizing a core reload of a fast reactor with respect to some objective function is developed. The objective function used in this work is a preliminary model that is defined to capture most of the core parameters expected to be of interest, but elements could be added or subtracted as needed for different types of problems. The optimization method is a discrete evolutionary algorithm. Instead of using diffusion or transport to evaluate each potential core configuration that is considered during the execution of the optimization method, the necessary inputs to the objective function (k-effective and assembly power distribution) are evaluated approximately by treating the reloaded configuration as a small change to the previous configuration, for which a diffusion or transport solution has already been calculated. This approximate calculation facilitates evaluation of the objective function for several hundred potential configurations without a neutron transport solution, which would be a significant bottleneck in the optimization method. In the results, the evolutionary algorithm demonstrates good responsiveness to the tuning of the parameters of the objective function.