David Allen Anderson

In this work, we quantify the impact of grain boundary (GB) and surface diffusion on fission gas bubble evolution and fission gas release in UO 2 nuclear fuel using simulations with a hybrid phase field/cluster dynamics model. We begin with a comprehensive literature review of uranium vacancy and xenon atom diffusivity in UO 2 through the bulk, along GBs, and along surfaces. In our model we represent fast GB and surface diffusion using a heterogeneous diffusivity that is a function of the order parameters that represent bubbles and grains. We find that the GB diffusivity directly impacts the rate of gas release via GB transport, and that the GB diffusivity is likely below 10 4 times the lower value from Olander and van Uffelen (2001). We also find that the surface diffusivity impacts bubble coalescence and mobility, and that the bubble surface diffusivity is likely below 10 -4 times the value from Thou and Olander (1984).

Ternary eutectic salts composed of MgCl 2 , NaCl, and KCl, referred to as MNK salts, have recently emerged as promising candidates as high -temperature heat transfer fluids and thermal energy storage media. In this study, we performed classical molecular dynamics (MD) simulations to predict the densities, specific heat capacities, viscosities, and ionic self-diffusivities for MNK salts over a wide temperature range. The impact of LiCl additive on their thermophysical properties was also investigated. To capture the electronic polarization of Cl anions by neighboring cations, we developed a novel shell -model potential using the force -matching method and a dataset of ab initio calculated interatomic forces. Our extensive MD simulations predict structure and properties for pure salts and binary/ternary salt mixtures in the MgCl 2 -NaCl-KCl-LiCl system in overall good agreement with available experimental and theoretical data, which corroborates the accuracy and reliability of our developed potential.

Tritium (T) and He diffusion in LiAlO2 and LiAl5O8 phases influences the performance of tritium producing burnable absorber rods (TPBARs) by affecting the gas release, swelling and thermal conductivity of Li-bearing ceramic pellets. Frenkel pair defects and clusters created by irradiation can attract T and He interstitials and form clusters of the type HeixLi,HeixAl,HeixO,TixLi,TixAlandTixO,1≤x≤4 in a Li, Al or O vacancy site (notation denotes x He or T atoms in a 1 Li, 1 Al or 1 O vacant site). The concentration and mobility of each of these clusters collectively contribute to the diffusion of the He and T gases in LiAlO2 and LiAl5O8. In this work, free energy cluster dynamics simulations implemented in the Centipede code, are used to obtain the concentration and diffusivities of these clusters which are then used to calculate the total diffusivity of T and He gases in LiAlO2 and LiAl5O8. The results show that diffusivity of T is at least one order of magnitude higher in LiAlO2 as compared to that in LiAl5O8 whereas He diffusion is 2–13 orders of magnitude higher in LiAlO2 as compared to that in LiAl5O8. There is a higher concentration of highly diffusive species (T interstitials and Ti03Li for the case of tritium and Hei01Li, Hei02Li and Hei03Li for the case of He) in LiAlO2 than in LiAl5O8 which increase the total diffusion of T and He in LiAlO2.

In response to the nuclear industry desire to extend burnup beyond current licensing practices, the US Nuclear Regulatory Commission (NRC) released a research information letter (RIL) that provides a basis for analyzing fuel fragmentation, relocation, and dispersal (FFRD) in light-water reactors. Of the five elements discussed, the most ambiguous is the significance of transient fission gas (FG) release (FGR) (tFGR) and its effects on fuel performance under loss-of-coolant accident conditions. In fresh fuel, FG migration and eventual release is primarily governed by diffusion-based mechanisms at higher temperatures (>1,000 degrees C). However, the mechanisms governing FGR changes as burnup increases. More recent research indicates that FGR increases as burnup increases, specifically under temperature transient con-ditions, and this release occurs at lower temperatures with a new release mechanism. This behavior has been attributed to microcracking in the fuel and is likely related to microstructure embrittlement with the presence of over pressurized FG bubbles. The NRC RIL outlines the complexity of the phenomenon and a need for a deeper understanding to adequately address FFRD for regulatory application. Therefore, this manuscript intends to summarize the publicly available tFGR data and discuss the observed dependencies (e.g., burnup, heating rate, sample geometry, terminal temperature). An empirical model has been developed and benchmarked against recently published experimental data. However, this empirical model is limited to conditions for which fitting data exist and, therefore, a high-level dis-cussion is included to provide a roadmap for atomistically-informed multiscale modeling in conjunction with experimental data collection to develop a mechanistic tFGR model widely applicable to a broad range of nuclear fuel conditions at high burnup.

The evolution and release of fission gas impacts the performance of UO2 nuclear fuel. We have created a Bayesian framework to calibrate a novel model for fission gas transport that predicts diffusion rates of uranium and xenon in UO2 under both thermal equilibrium and irradiation conditions. Data sets are taken from historical diffusion, gas release, and thermodynamic experiments. These data sets consist invariably of summary statistics, including a measurement value with an associated uncertainty. Our calibration strategy uses synthetic data sets in order to estimate the parameters in the model, such that the resulting model predictions agree with the reported summary statistics. In doing so, the reported uncertainties are effectively reflected in the inferred uncertain parameters. Furthermore, to keep our approach computationally tractable, we replace the fission gas evolution model by a polynomial surrogate model with a reduced number of parameters, which are identified using global sensitivity analysis. We discuss the efficacy of our calibration strategy, and investigate how the contribution of the different data sets, taken from multiple sources in the literature, can be weighted in the likelihood function constructed as part of our Bayesian calibration setup, in order to account for the different number of data points in each set of data summaries. Our results indicate a good match between the calibrated diffusivity and non-stoichiometry predictions and the given data summaries. We demonstrate a good agreement between the calibrated xenon diffusivity and the established fit from Turnbull et al. (1982), indicating that the dominant uranium vacancy diffusion mechanism in the model is able to capture the trends in the data.

Uranium mononitride (UN) is a promising nuclear fuel that combines the advantageous properties of readily used UO2 and uranium alloys, such as high melting temperature and high uranium density, and thermal conductivity, respectively. A better understanding of UN behavior at operating temperatures can be obtained from finite temperature data, such as elastic properties. To get this information, ab initio molecular dynamics (AIMD) simulations were performed at five different temperatures using constant volume (NVT) and constant pressure (NPT) ensembles. Initially, the performance of PBE functional in reproducing experimental crystallographic properties and magnetic ordering is assessed. The finite temperature phonon dispersions are calculated using NVT simulation results, which show a softening of the phonon modes with increasing temperature. The NPT results are used to obtain the thermal expansion of UN and finite temperature electronic properties. The calculated thermal expansion is compared with our measurements using neutron diffraction. Additionally, the temperature dependent elastic properties of UN are evaluated using the strain-stress method in AIMD simulations, indicating that UN becomes softer and more compressible with increasing temperature. Also, the calculated Young’s modulus slope is in very good agreement with the experiment. The finite temperature heat capacity and electronic thermal conductivity are calculated from AIMD simulations, which are in better agreement with the experiment than the heat capacity and thermal conductivity calculated using the structures relaxed at 0 K. Lastly, the thermal diffusivity from AIMD has opposite temperature dependence compared to experimental results, which we argued comes from the underestimated electronic thermal conductivity.

This paper presents the state-of-the-art knowledge about the micro-mechanical modelling of the fuel behavior under irradiation with normal and off normal operating conditions. Modelling of fundamental processes can provide key insights in the behavior of the material. Such models target specific phenomena due to the limits of computational resources and scope of theory, necessitating a multiscale approach. This work follows a multiscale paradigm building up in spatio-temporal scale. The micro-mechanical modelling studied addresses all the loading conditions encountered in the reactor with elasticity, plasticity, creep and fracture behavior. Atomistic-scale modelling review reveals mechanisms and physical parameters for elasticity of fresh and irradiated fuel, rupture, dislocation gliding and internal stresses induced by pressurized bubble with fission gases. Simulation techniques proposed at this scale are Density Functional Theory, Molecular Dynamic with empirical potential, Dislocation Dynamics and Phase Field Crystal methodology.

The thermochemical details of fabricating uranium nitride (UN) by ammonolysis of uranium tetraflouride (UF4) were determined using density functional theory (DFT) and CALculation of PHAse Diagrams (CALPHAD) computational methods. The thermochemical data of all binary, ternary, and quaternary U-H-N-F phases were computed using DFT, and the data for the phases that have not been measured experimentally, including UN(2 )and NH4F(g), were combined with existing experimentally-determined data for CALPHAD modeling. The DFT data were benchmarked using experimental Gibbs energy of reaction and experimental thermochemical data for individual species. Phase diagrams relevant to the ammonolysis reaction are depicted, showing regions of stability for solid U-N, U-F and U-N-F phases. An unidentified phase produced in a previous experiment was identified as UN0.95F1.2 (UNF) by comparing its X-ray diffraction spectrum to the experimental spectrum, and its formation during the fabrication of UN from UF4 is supported by the simulated phase diagram. It is calculated that UN2 can be produced by the ammonolysis of UF4, but requires elevated temperatures, high NH3(g) partial pressure, and large amounts of flowing NH3(g) to avoid solid fluoride impurities in the uranium nitride. Likewise, U2N3 can be produced instead at temperatures greater than 980 K. The use of silane (SiH4) gas was investigated as a potential additive in the ammonolysis fabrication route to speed removal of fluorine. The addition of SiH4(g) offers little advantage to the removal of fluorine, and adds the complication of Si3N4 formation. The use of DFT to fill in missing data to perform CALPHAD calculations demonstrated here allows for the determination of more comprehensive and trustworthy phase diagrams than the use of existing experimental data alone.

•atomistic based models for defects in UO2 are reviewed.•Large discrepancies among defect energies/entropies are observed.•If O2 molecule is fitted, 2 models among the 7 satisfactorily reproduce experimental data.•The poor ability of DFT for O2 molecules is only part of the explanation.•Improve atomistic techniques on simple well characterized systems like UO2 is unavoidable. Defect thermodynamic models are increasingly used to describe the evolution of materials microstructure. Unfortunately, experimental data for these models are generally scarce and difficult to obtain, which has given rise to a growing trend toward using atomic scale calculations to complement experimental data. This paper is a review concerning the way atomistic techniques can help building defect models in crystals and how efficient they are in reproducing important experimental data, such as the OM ratio and phase diagrams. The issue is addressed through the example of non-stoichiometric uranium dioxide. In this article, eleven point-defect models from the literature (defect formation energies-entropies) are presented and compared on the same footing; four of them are fitted to experimental data, while seven are obtained through atomistic calculations. This allows to compare all the models on the same basis both among themselves and with a large set of experimental data of various physical quantities, including the phase diagram near stoichiometric uranium dioxide. The defect formation energies and entropies are very different from one model to another. While the fitted models usually correctly reproduce the data sets according to which they were fitted, only two atomistic based models correctly reproduce the OM ratio diagrams, provided the oxygen molecule energy is correspondingly fitted. No model simultaneously reproduces the measured conductivity and OM ratio as functions of the oxygen potential. The difficulties of the atomistic-based models in predicting this ratio and the oxygen potential probably arise, among others, from an erroneous calculation of energy of the oxygen molecule and of the oxygen incorporation in UO2 and also from a poor evaluation of the electron-hole formation Gibbs energy. The difficulty of obtaining reliable experimental data close to the stoichiometry might also contribute to the limited agreement between calculations and measurements, which is reason enough to reassess the behavior of the material in this stoichiometry region comprehensively, with a particular focus on the influence of uranium vacancies.

Fission gas release within uranium dioxide nuclear fuel occurs as gas atoms diffuse through grains and arrive at grain boundary (GB) bubbles; these GB bubbles grow and interconnect with grain edge bubbles; and grain edge tunnels grow and connect to free surfaces. In this study, a hybrid multi-scale/multi-physics simulation approach is presented to investigate these mechanisms of fission gas release at the mesoscale. In this approach, fission gas production, diffusion, clustering to form intragranular bubbles, and re-solution within grains are included using spatially resolved cluster dynamics in the Xolotl code. GB migration and intergranular bubble growth and coalescence are included using the phase field method in the MARMOT code. This hybrid model couples Xolotl to MARMOT using the MultiApp and Transfer systems in the MOOSE framework, with Xolotl passing the arrival rate of gas atoms at GBs and intergranular bubble surfaces to MARMOT and MARMOT passing evolved GBs and bubble surface positions to Xolotl. The coupled approach performs well on the two-dimensional simulations performed in this work, producing similar results to the standard phase field model when Xolotl does not include fission gas clustering or re-solution. The hybrid model performs well computationally, with a negligible cost of coupling Xolotl and MARMOT and good parallel scalability. The hybrid model predicts that intragranular fission gas clustering and bubble formation results in up to 70% of the fission gas being trapped within grains, causing the increase in the intergranular bubble fraction to slow by a factor of six. Re-solution has a small impact on the fission gas behavior at 1800 K but it has a much larger impact at 1000 K, resulting in a twenty-times increase in the concentration of single gas atoms within grains. Due to the low diffusion rate, this increase in mobile gas atoms only results in a small acceleration in the growth of the intergranular bubble fraction. Finally, the hybrid model accounts for migrating GBs sweeping up gas atoms. This results in faster intergranular bubble growth with smaller initial grain sizes, since the additional GB migration results in more immobile gas clusters reaching GBs.