Using Coupled Mesoscale Experiments and Simulations to Investigate High Burn-Up Oxide Fuel Thermal Conductivity

Abstract

Nuclear energy is a mature technology with a small carbon footprint. However, work is needed to make current reactor technology more accident tolerant and to allow reactor fuel to be burned in a reactor for longer periods of time. Optimizing the reactor fuel performance is essentially a materials science problem. The current understanding of fuel microstructure have been limited by the difficulty in studying the structure and chemistry of irradiated fuel samples at the mesoscale. Here, we take advantage of recent advances in experimental capabilities to characterize the microstructure in 3D of irradiated mixed oxide (MOX) fuel taken from two radial positions in the fuel pellet. We also reconstruct these microstructures using Idaho National Laboratory's MARMOT code and calculate the impact of microstructure heterogeneities on the effective thermal conductivity using mesoscale heat conduction simulations. The thermal conductivities of both samples are higher than the bulk MOX thermal conductivity because of the formation of metallic precipitates and because we do not currently consider phonon scattering due to defects smaller than the experimental resolution. We also used the results to investigate the accuracy of simple thermal conductivity approximations and equations to convert 2D thermal conductivities to 3D. It was found that these approximations struggle to predict the complex thermal transport interactions between metal precipitates and voids.

Formation mechanism of gas bubble superlattice in UMo metal fuels: Phase-field modeling investigation

“…Therefore, in the current work, the simulations of gas bubble evolution were performed in a two-dimensional, 256dx × 256dx simulation cell. The model can be implemented in Idaho National Laboratory's MARMOT and BISON fuel performance code [77,78], which has efficient scalable numerical methods, for large scale gas bubble microstructure evolution simulations in 3D and polycrystalline materials.…”

A machine learning approach to thermal conductivity modeling: A case study on irradiated uranium-molybdenum nuclear fuels

“…Thermal conductivity of nuclear fuel heterogeneous microstructures has been modeled previously using analytical, empirical [10,16,17,18], and phase field modeling [15] methods. In prior empirical modeling work, only select microstructural features (identified by researchers) were used to predict fuel thermal conductivity.…”

“…In addition to empirical modeling, computational modeling approaches have been used to predict thermal conductivity of nuclear fuel independent of experimental data. Such methods include COMSOL multiphysics simulations, finite element methods, and phase field modeling [15,16,17,18]. Reference [15] reports a method of estimating thermal conductivity of a polycrystalline metal with inter-and intra-granular gas bubbles using the phase field method.…”

Assessment of effective thermal conductivity in U–Mo metallic fuels with distributed gas bubbles

“…A finite element method (FEM) was used to calculate the effective change in grain boundary kapitza resistance due to the presence of elliptic intergranular gas bubbles in a bi-crystal UO 2 nuclear fuels [14]. Very recently, Teague et al [15] used FEM to assess the effect of defects including porosity, precipitates, and fission product layer on thermal conductivity in irradiated mixed oxide (MOX) fuels by directly using the three-dimensional microstructures from advanced 3D microstructure reconstruction techniques. However, the microstructures in irradiated nuclear fuels are very complicated.…”

“…But all these simulations were carried out in two dimensions. In very recent work, Teague et al [15] claimed that a phase-field model is used to relax the three dimensional microstructure before they calculated the thermal conductivity. This work will present a numerical method to assess the effect of three dimensional polycrystalline microstructure and gas bubble microstructures on thermal conductivity.…”