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This application simulates microstructural and compositional evolution in two-phase, two-component systems. It is designed to run within the SPPARKS solver and combines the kMC with solution to the Cahn-Hilliard Eq. for phase field.
PIKA is a MOOSE-based application for modeling micro-structure evolution of seasonal snow. The model will be useful for environmental, atmospheric, and climate scientists. Possible applications include application to energy balance models, ice sheet modeling, and avalanche forecasting. The model implements physics from published, peer-reviewed articles. The main purpose is to foster university and laboratory collaboration to build a larger multi-scale snow model using MOOSE. The main feature of the code is that it is implemented using the MOOSE framework, thus making features such as multiphysics coupling, adaptive mesh refinement, and parallel scalability native to the application. PIKA implements three equations: the phase-field equation for tracking the evolution of the ice-air interface within seasonal snow at the grain-scale; the heat equation for computing the temperature of both the ice and air within the snow; and the mass transport equation for monitoring the diffusion of water vapor in the pore space of the snow.
Tusas is a general / flexible software framework for solving coupled systems of onlinear partial differential equations. Tusas was originally developed for phase-field simulation of solidification. In order for Tusas to be effective, the PDEs must be compatible with structured or unstructured Lagrange (nodal) finite element discretizations and explicit (Euler) or implicit (Euler, Trapezoid, BDF2) temporal discretizations.
The catastrophic events that occurred at the Fukushima-Daiichi nuclear power plant in 2011 have led to widespread interest in research of alternative fuels and claddings that are proposed to be accident tolerant. The United States Department of Energy (DOE) through its Nuclear Energy Advanced Modeling and Simulation (NEAMS) program has funded an Accident Tolerant Fuel (ATF) High Impact Problem (HIP). The ATF HIP is a three-year project to perform research on two accident tolerant concepts. The final outcome of the ATF HIP will be an in-depth report to the DOE Advanced Fuels Campaign (AFC) giving a recommendation on whether either of the two concepts should be included in their lead test assembly scheduled for placement into a commercial reactor in 2022. The two ATF concepts under investigation in the HIP are uranium silicide fuel and iron-chromium-aluminum (FeCrAl) alloy cladding. Utilizing the expertise of three national laboratory participants (Idaho National Laboratory, Los Alamos National Laboratory, and Argonne National Laboratory), a comprehensive multiscale approach to modeling is being used that includes atomistic modeling, molecular dynamics, rate theory, phase-field, and fuel performance simulations. Model development and fuel performance analysis are critical since a full suite of experimental studies will not be complete before AFC must prioritize concepts for focused development. In this paper, we present simulations of the two proposed accident tolerance fuel systems: U3Si2 fuel with Zircaloy-4 cladding, and UO2 fuel with FeCrAl cladding. Sensitivity analyses are completed using Sandia National Laboratories’ Dakota software to determine which input parameters (e.g., fuel specific heat) have the greatest influence on the output metrics of interest (e.g., fuel centerline temperature). We also outline the multiscale modelling approach being employed. Considerable additional work is required prior to preparing the recommendation report for the Advanced Fuels Campaign.
The catastrophic events that occurred at the Fukushima-Daiichi nuclear power plant in 2011 have led to widespread interest in research of alternative fuels and claddings that are proposed to be accident tolerant. Thus, the United States Department of Energy through its NEAMS (Nuclear Energy Advanced Modeling and Simulation) program has funded an Accident Tolerant Fuel (ATF) High Impact Problem (HIP). The ATF HIP is funded for a three-year period. The purpose of the HIP is to perform research into two potential accident tolerant concepts and provide an in-depth report to the Advanced Fuels Campaign (AFC) describing the behavior of the concepts, both of which are being considered for inclusion in a lead test assembly scheduled for placement into a commercial reactor in 2022. The initial focus of the HIP is on uranium silicide fuel and iron-chromium-aluminum (FeCrAl) alloy cladding. Utilizing the expertise of three national laboratory participants (INL, LANL, and ANL) a comprehensive mulitscale approach to modeling is being used including atomistic modeling, molecular dynamics, rate theory, phase-field, and fuel performance simulations. In this paper, we present simulations of two proposed accident tolerant fuel systems: U3Si2 fuel with Zircaloy-4 cladding, and UO2 fuel with FeCrAl cladding. The simulations investigate the fuel performance response of the proposed ATF systems under Loss of Coolant and Station Blackout conditions using the BISON code. Sensitivity analyses are completed using Sandia National Laboratories’ DAKOTA software to determine which input parameters (e.g., fuel specific heat) have the greatest influence on the output metrics of interest (e.g., fuel centerline temperature). Early results indicate that each concept has significant advantages as well as areas of concern. Further work is required prior to formulating the proposition report for the Advanced Fuels Campaign.
A number of advances have recently been made in modeling fracture initiation and propagation in ceramic light water reactor (LWR) fuel. These include the use of techniques such as peridynamics, the extended finite element method (XFEM), the discrete element method (DEM), and phase field fracture. Improved predictions of fracture in LWR fuel can benefit fuel performance simulations in a number of ways, with important implications for radial relocation, pellet-cladding mechanical interactions, and fragmentation during accident conditions. Although these modeling approaches appear promising, to-date most of their applications have been to fresh fuel. A major limitation in applying these approaches with confidence to a wider variety of conditions, such as fragmentation of high-burnup fuel, is that there is very limited data that can be directly used to validate the results of these fracture models. While fracture patterns are available from cross-sections of numerous irradiated fuel rods, the fuel rods have typically been subjected to complex irradiation histories. To validate models of fracture propagation, focused experiments that give snapshots of the initiation and propagation of fracture under well characterized prototypical reactor conditions are needed. Under a multi-institutional U.S. Department of Energy Integrated Research Project (IRP), three separate-effects validation experiments are underway to provide information on the propagation of cracks in LWR fuel under controlled conditions. The primary challenge in developing such an experiment is in providing conditions that result in a radial temperature distribution that is prototypical of LWR in-reactor conditions. Two out-of-reactor experiments are being planned that employ very different approaches to achieve such a temperature distribution. The first of these achieves this by employing a combination of inductive and resistive electrical heating to generate volumetric heating. The second experiment involves slowly heating a pellet in a metal rod to a high temperature, and then quenching that rod in a cold bath. The quenching process generates a temperature profile approximating that in an LWR fuel rod for a moment, but has a very different temperature history from the LWR. Finally, an experiment is being planned for the Idaho National Laboratory TREAT reactor that will use nuclear fission as a heat source, and which will employ a metal heat sink to replicate the thermal conditions provided by coolant in an LWR. These experiments all have their advantages and drawbacks, with varying levels of ability to reproduce actual LWR conditions and varying ability to use instruments to monitor quantities of interest over the course of the experiment that can be used to validate fracture models. For that reason, these different experimental approaches are complimentary to each other, and the combined results are expected to significantly improve confidence in the ability of computational models to simulate fracture in ceramic nuclear fuel.
Purpose of this work Oxidation modeling Oxidation of full-scale components Local properties in oxidized components Graphite fracture strength Phase field fracture modeling Microstructurally informed fracture model IG-110 tensile results and comparison to experiment Work in progress and future work
Reaction rates at spatially heterogeneous, unstable interfaces are notoriously difficult to quantify, yet are essential in engineering many chemical systems, such as batteries 1 and electrocatalysts 2. Experimental characterizations of such materials by operando microscopy produce rich image datasets 3–6, but data-driven methods to learn physics from these images are still lacking because of the complex coupling of reaction kinetics, surface chemistry and phase separation 7. Here we show that heterogeneous reaction kinetics can be learned from in situ scanning transmission X-ray microscopy (STXM) images of carbon-coated lithium iron phosphate (LFP) nanoparticles. Combining a large dataset of STXM images with a thermodynamically consistent electrochemical phase-field model, partial differential equation (PDE)-constrained optimization and uncertainty quantification, we extract the free-energy landscape and reaction kinetics and verify their consistency with theoretical models. We also simultaneously learn the spatial heterogeneity of the reaction rate, which closely matches the carbon-coating thickness profiles obtained through Auger electron microscopy (AEM). Across 180,000 image pixels, the mean discrepancy with the learned model is remarkably small (<7%) and comparable with experimental noise. Our results open the possibility of learning nonequilibrium material properties beyond the reach of traditional experimental methods and offer a new non-destructive technique for characterizing and optimizing heterogeneous reactive surfaces.
The low solubility of fission gas in nuclear fuel leads to inter- and intra-granular bubbles. These bubbles affect performance of the fuel rod and increase the fuel temperature through the increase of porosity in the fuel pellets and decreased thermal conductivity across the pellet-clad gap as gas is released into the plenum. The nucleation, growth, and inter-connectivity of the fission gas bubbles ultimately depend on the diffusivity of gas atoms through the fuel matrix. Using mechanisms and data previously established from density functional theory (DFT) and empirical potential calculations, diffusion and reaction models have been derived for xenon atoms, uranium atoms, and vacancies in the substitutional and interstitial locations. Although similar to previous models, the diffusion and reaction rates have been re-derived in a more robust manner. Previous studies have under-predicted the experimentally observed diffusivity of xenon atoms in UO{sub 2}, however it has been previously shown that by including xenon atoms bound to two vacancies, the calculated diffusivity approaches the measured data. The derived model for species diffusion and inter-species reactions has been implemented in the MARMOT phase-field code in a modular structure so as to capture the enhanced diffusion of xenon due to bound gas + vacancy-cluster movement. The MARMOT code allows for the diffusion, reaction, and source rates to be solved simultaneously, resulting in steady state or transient concentrations of each species, and ultimately the diffusion behavior of xenon atoms. By including the diffusion of clusters of different combinations of xenon and vacancies, the calculated diffusivity more closely captures the measured diffusivity of xenon when using preliminary parameters. (authors)
Advances in simulation of coupled heat and mass transfer in granular salt using the Finite Element Heat and Mass Transfer Code (FEHM) is presented in this paper. The modeling focuses on reproducing the results of an in-situ subsurface evaporation experiment beginning during the summer of 2015 carried out in the underground at the Waste Isolation Pilot Plant (WIPP). Run-of-mine (granular) salt was placed in a metal pan, and sample mass, as well as ambient temperature and humidity, were measured continuously on a data logger through May 2016. Changes in moisture content of the salt are interpreted from the change in mass, and these data provide insight into evaporation and water retention characteristics from salt in the WIPP underground. To allow simulation of the experimental data, FEHM was modified to include a variable humidity boundary condition. The new humidity boundary condition can adjust streams of inflowing air to reflect fractions of air and water at prescribed temperature and pressure conditions that in turn represent relative humidity. Attributes for the flow such as temperature, air mass fraction, and humidity can be specified for inflowing air. The in-situ experiment provided data for validation of FEHM code development to accurately compute water-vapor pressure lowering due to dissolved salt and capillary pressure for pore water stored granular WIPP salt. Using this new boundary condition capabilities, a numerical representation of the pan experiment was created. The numerical domain is a 2-dimensional square grid of 30 by 30 cm axes. Salt and air properties are assigned based on measured values. A low flow rate of air is specified across the pile of salt to represent drift ventilation airflow. Humidity and temperature of the flowing air are fixed to measured values, and the simulated pile of salt is allowed to take up or release water based only on gradients in humidity and water-vapor pressure. Mass changes of the modeled salt pan were compared to measured mass changes in the bench-scale experiment. Directionality of the modeled changes tracks well with measured values, with good correlation between peak and valley inflection points. This shows that in situations with airflow where the relative humidity boundary can apply, FEHM can produce accurate values if humidity, air flow, and initial conditions are well established. Finally, this work supports phased-field-thermal testing in salt planned for the underground at WIPP that is expected to begin in early 2017. (authors)
Uranium dioxide (UO{sub 2}) is the primary nuclear fuel in light water reactors. The thermal conductivity of UO{sub 2} is an important fuel performance metric as it affects nuclear energy conversion efficiency and safety. Unfortunately UO{sub 2} has a very low thermal conductivity, even in the single crystal form. In reactor environment, the radiation-induced defects, fission products, and complex microstructural evolution degrade the thermal conductivity of UO{sub 2} significantly. These defects and microstructures in UO{sub 2} fuels include point defects, gas bubbles, metallic precipitates, etc.. In the rim region of a fuel pellet, high burnup structure also forms which contains many nanograins and thus high density of grain boundaries. Therefore, understanding how different irradiation-induced microstructures affect the thermal conductivity in nuclear fuels is important for predicting the overall thermal transport properties in nuclear fuels. In this work, the unit effect of each microstructure on the thermal conductivity of UO{sub 2} is evaluated, using grain boundary as an example. The obtained unit mechanism can be used as input for the multiplier model that describes the combined effect of various microstructures. In this work we use phase field simulations coupled with heat conduction calculations to study the co-evolution of grain size and thermal conductivity. The simulation data are used to calibrate an analytical model. Based on the sufficient statistics from simulations, we conclude that the analytical model can well predict the grain-size-dependent thermal conductivity over a wide range of grain sizes if the input parameters are calibrated. (authors)
Due to the high thermal conductivity and uranium density compared to UO{sub 2} fuel used in current Light Water Reactors (LWRs), U-Si fuels, such as the U{sub 3}Si{sub 2} and U{sub 3}Si{sub 5} compounds, are currently under investigation for the development of accident tolerant fuels (ATF) in response to the Fukushima Daiichi accident in Japan. In order to perform meaningful mesoscale and macroscale fuel performance simulations, fundamental material properties of nuclear fuels should be known. One example is the simulations of fission gas bubble evolution and gas bubble-induced swelling in nuclear fuels using mesoscale methods, such as phase field and rate theory. To properly describe the gas bubble behavior in the fuel, it is crucial to know the surface energies of the fuel. Unfortunately, there is no study of the surface properties of U{sub 3}Si{sub 2} from both experiment and theory. To this end, we systematically investigate the surface properties of U{sub 3}Si{sub 2} using density functional theory (DFT) based first-principles calculations. Of several low index facets, we studied the (001) and (100) surfaces of tetragonal U{sub 3}Si{sub 2} with all the possible terminations. Since all the studied surfaces are not stoichiometric, we also investigated the effect of elemental chemical potentials on the formation of surface. We systematically investigate the surface properties of U{sub 3}Si{sub 2} using density functional theory calculations. Of several low-index facets, the (001) and (100) surfaces show similar averaged surface energies calculated using even number of layers. At the high Si chemical potential, the Si-terminated U{sub 3}Si{sub 2}(100) and U{sub 3}Si{sub 2}(001) surfaces show lower energies than those of the U-terminated surfaces, with U,Si-terminated U{sub 3}Si{sub 2}(001) as the most stable surface. The surface energies of all non-stoichiometric U{sub 3}Si{sub 2} are linearly dependent on the Si chemical potential. The surface energies of U-terminated surfaces decrease as Si potential decreases. The U{sub 2}-terminated U{sub 3}Si{sub 2}(100) surface becomes that the most stable surface at U-rich side. Based on the current results, an averaged surface energy of U{sub 3}Si{sub 2}, i.e., 1.45 J/m{sup 2}, is recommended for the description of the rounded facets of gas bubbles in U{sub 3}Si{sub 2} by mesoscale simulations. (authors)
Ni coarsening is an important degradation mechanism in solid oxide cells. It is reported that Ni coarsening is faster under a humid atmosphere experimentally, but the underline mechanism is not well understood. In this work, Ni coarsening through Ni(OH)x surface diffusion was investigated by a combination of density-functional theory (DFT) and phase-field modeling (PFM). DFT is used to evaluate the surface coverage and diffusivity of Ni(OH)x on Ni (111) surface and the results are used as an input to the PFM to simulate Ni coarsening under humid atmospheres on both reconstructed and synthetic microstructures. It is found that steam partial pressure and microstructure effect alone cannot explain the faster Ni coarsening under a humid atmosphere observed experimentally. Large local overpotential in fuel cell mode is needed to explain the fast Ni coarsening.
Monolithic U-10Mo fuel undergoes significant microstructural changes during fuel burnup which degrades its mechanical properties. In this talk, we present results form a numerical method to assess the impact of the various microstructural features--grains, intragranular and intergranular Xe gas bubbles--on the elastic stiffness tensor. Using the Multiphysics Object-Oriented Simulation Environment (MOOSE), phase-field-based microstructures are combined with asymptotic expansion homogenization method to obtain effective elastic constants as a function of porosity and fission density. The results are verified and compared against analytical homogenization models. With this approach, elastic degradation in operating nuclear fuels can be quantified when the distributions of microstructural features are known from experimental characterization or rate-theory based models. We further develop an evolution model based on the virial equation of state for Xe gas and investigate the effect of growth and coalescence of the bubbles at the grain boundary faces and triple junctions.
To improve the economics of commercial nuclear reactors, nuclear vendors and utilities are seeking approval for increased burnup usage of the existing nuclear fleet. This is especially critical for meeting the clean energy initiative by the United States Government, Department of Energy (DOE). However, one of the key challenges the nuclear industry faces in this regard is that the regions exposed to high burnup and low temperatures exhibit a fine-grained microstructure with large bubbles known as high-burnup structure (HBS) [1]. The formation of HBS has been correlated to the diminished performance of the reactor, as well as fuel fragmentation and pulverization during transient and accidental conditions [2]. Therefore, it is paramount to understand the mechanisms for HBS formation along with its impact on the properties and performance of nuclear fuels. While existing programs, such as Nuclear Energy Advanced Modeling and Simulation (NEAMS) and Advanced Fuel Campaign (AFC) are focusing on evaluating the performance impact of HBS, the physical mechanisms contributing to HBS formation are still not fully understood. In addition, having predictive capabilities and sound understanding of the microstructural evolution of nuclear fuel is essential for accelerated development, qualification, and deployment of new nuclear materials and novel reactor designs for advanced nuclear reactors. There is a lack of consensus among researchers regarding the mechanisms leading to such restructuring observed in HBS. Grain subdivision due to polygonization versus recrystallization, continuous versus discrete recrystallization occurring in tandem or conjunction, etc., have been proposed and debated. In general, it is hypothesized that defect accumulation and dislocation interaction within the grains cause the realignment of dislocations into grain boundaries, leading to the new subgrain formation, which over time transforms into new grains. However, due to the lack of transient data, the importance of fission rate, irradiation, thermal, and stress history of the fuel on the restructuring could not be assessed. In situ microstructural evolution under various irradiation conditions is desired to bridge this gap. Alternatively, phase-field-based models have been developed to capture HBS formation via discrete recrystallization utilizing the classical nucleation approach [3–5]. However, in these models, the grain nucleation criteria are often defined based on empirical relations for burnup and fission gas density leading to dislocation density change. A mechanistic approach to capture the dislocation interaction with the microstructural features leading to grain subdivision is lacking.
Reliable material performance is required for plasma-facing material (PFM) candidates. Previous research has shown that plasma and neutron radiation exposure induces microstructural changes in PFMs; changes in thermal and electrical conductivities and in material hardening and embrittlement were also observed after neutron irradiation. These material property changes will negatively impact the performance of the PFMs in a fusion reactor. Despite the well-known connection between material microstructure, properties, and performance, there is a need for validated modeling capabilities connecting PFM property degradation with microstructural evolution under fusion-relevant conditions. We are developing a simulation capability to couple plasma-induced microstructural evolution to material property degradation. Our approach relies on deliberate mapping between individual simulation models and experimental characterization for validation. The open-source Multiphysics Object-Oriented Simulation Environment (MOOSE) software was used for this simulation capability development. A MOOSE phase-field model was coupled with the cluster dynamics code, Xolotl, to predict microstructural evolution. Microstructure characterization techniques, including scanning electron microscopy (SEM), transmission electron microscopy (TEM), and laser scanning confocal microscopy (LSCM) are used to validate these microstructural evolution simulations. Calculation of thermal and electrical conductivities with first principles simulations was performed for bulk material and for grain boundaries; these results are used within MOOSE models to calculate effective thermal and electrical conductivities as a function of grain characteristics. Thermoreflectance and four-probe techniques were employed to measure the thermal and electrical conductivities, respectively. A MOOSE crystal plasticity model was adapted to predict microstructure-sensitive deformation behavior, and X-ray diffraction (XRD) was used to collect bulk dislocation density data for validation. After individual simulation validation, these models are coupled to predict material property changes resulting from plasma exposure. We focused here on an experimental design to emphasize the separate effects of moderate thermal loads and plasma exposure using tungsten. Annealing of tungsten was performed under a protective environment for temperatures ranging from 500 C to 1500 C. The plasma exposure was completed in the Tritium Plasma Experiment at Idaho National Laboratory under a deuterium flux of 1e22 D/m^2-s. This incremental approach is employed to build confidence in the modeling capability: separate-effects tests ensure that the models capture key mechanisms from single environmental conditions before predicting PFM property degradation under combined loads. We will show our early results from coupling these simulation models to predict PFM property changes from microstructural evolution. Comparisons of the simulation results with preliminary validation data will be discussed.
The silicon carbide (SiC) layer in tristructural isotropic (TRISO) fuel particles serves as a barrier to prevent the escape of fission from the fuel kernel. The release of silver (Ag) is a concern due to the long half-life of the 110mAg isotope. In this study, the effective diffusion coefficient of the fission product Ag through the grain boundary (GB) network is calculated using a combination of atomistic and phase-field methods. Atomistic calculations of Ag diffusivity in SiC bulk and GBs are leveraged to develop a mesoscale effective Ag diffusion coefficient (Deff) in SiC. Since GBs serve as pathways for Ag diffusion, Deff is defined as a function of temperature, microstructure variables, and fluence. Deff is implemented in the fuel performance code Bison to predict Ag release from AGR-1 TRISO fuel particles. We hereby quantify the impact of SiC grain size and irradiation on Ag release and improve Bison's predictions.
The silicon carbide (SiC) layer in tristructural isotropic (TRISO) fuel particles serves as a barrier to prevent the escape of fission from the fuel kernel. The release of silver (Ag) is a concern due to the long half-life of the 110mAg isotope. In this study, a combination of atomistic and phase-field methods focuses on quantifying the effect of irradiation and SiC microstructure on Ag diffusion. Atomistic calculations provide the Ag diffusivity in SiC bulk and GBs, also providing an estimate of the effect of irradiation defects on Ag diffusivity in bulk SiC. These lower length scale efforts are leveraged to develop a mesoscale effective Ag diffusion coefficient (Deff) in SiC. Deff is defined as a function of temperature, microstructure variables, and fluence. Deff is implemented in the fuel performance code Bison to predict Ag release from AGR-1 and AGR-2 TRISO fuel particles. We hereby quantify the impact of SiC grain size and irradiation on Ag release and improve Bison's predictions.