Development and application of a microstructure dependent thermal resistor model for UO2 reactor fuel with high thermal conductivity additives

Abstract

High thermal conductivity additives are being explored to make next generation accident tolerant fuels for light water reactors (LWRs). The goal is to create composite fuels that will more effectively dissipate heat, thus lowering the high centerline temperatures that develop in current LWR fuel. These fuels can employ various additives and the fuel microstructures vary depending on the manufacturing process. In this work, a thermal resistor model is developed to quickly estimate the effective thermal conductivity of a composite with a high thermal conductivity additive. This model is unique in that it employs a parameter, the continuousness of the secondary constituent, to consider the composite microstructure in its predictions. A genetic algorithm was developed to measure a composite’s continuousness. The model and algorithm are validated using data from literature from four experimental composites composed of UO2 with beryllium oxide and silicon carbide additives. The model predictions have an absolute mean error across a wide temperature range of less than 0.50W/mK in most cases. These tools are then used to create a set of guidelines for microstructure design.