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Sensitivity of Spent Fuel Temperatures to Variable Canister Backfills

This report describes thermal modeling done to understand the effects of a hypothetical loss of backfill to a spent fuel storage canister. A NAC MAGNASTOR system was analyzed using STAR-CCM+ and COBRA-SFS at various heat loads, helium pressures, and air environments. When helium was lost later in life the results showed no safety impact to the thermal performance of the cask system and fuel cladding. However, there were other results of interest from this study. The potential to detect helium leaks using external temperature measurement was considered and found to be a potential area for future technology development. The other major result of interest was the significant change in flow velocities with an air environment. This data will be useful in understanding the potential impacts of a breached canister.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Assessment of Sodium Thermal Stratification Models Utilizing the TSTF Benchmark

As a result of certain transient scenarios, a thermally stratified layer of liquid sodium can develop in the bulk coolant volumes of a sodium-cooled fast reactor (SFR). In addition to the effects a stratification layer has on the temperature of the heat transport system, a stratification layer can also influence the transition to and establishment of natural circulation flow, which plays an important role in passive cooling and the inherent safety of a pool-type SFR. Therefore, the ability to accurately capture thermal stratification phenomena is important when demonstrating the safety basis of a pool-type SFR during transient sequences. The present work assesses various computational models with different fidelities in their ability to predict thermal stratification in the upper plenum of an SFR. Each computational model will be assessed using the data generated at the Thermal Stratification Test Facility (TSTF) located at the University of Wisconsin-Madison. Using measured flow rate and inlet temperature data, the measured temperature distributions of the tests are compared to the predictions of the lumped volume-based models in SAS4A/SASSYS-1, a 1D-based model in SAM, and a 3-D computational fluid dynamics (CFD) model using STAR-CCM+. The relative performance of the various computational methods is assessed with respect to key metrics such as bulk coolant temperature distribution and plenum exit temperature. A total of eight tests are analyzed, covering different combinations of flow rates (3 and 10 GPM) and upper internal structure (UIS) configurations (none, solid, porous, and open) The perfect mixing model of SAS4A/SASSYS-1 provides the highest accuracy when the flow rate is high and there is no UIS in the test vessel, as high flow rate injection promotes thermal mixing of the sodium in the test vessel. For most of the analyzed tests, the stratified volume model of SAS4A/SASSYS-1 is able to predict the delay in the outlet temperature drop and temperature distribution in the test vessel by a small number of layers to represent thermal stratification. However, the stratified volume model can only simulate a maximum of three temperature layers within a volume and when a layer approaches the elevation of the outlet, the predicted outlet temperature can demonstrate rapid, non-physical changes. The 1-D axial mixing model of SAM provides results that agree reasonably well with the measured data in the prediction of the temporal evolution of the outlet temperature with the exception of the case with a high flow rate and no UIS. The SAM 1-D model has a similar level of accuracy to CFD results when it comes to predicting the outlet temperature. CFD shows overall good agreement in predicting the temperature distribution in the test vessel and outlet temperature. As CFD can model the test vessel geometry in detail, it performs well in the cases of complex geometries such as tests that included a UIS and internal flow through the UIS resulting in active mixing of the coolant in the test vessel. Each of the models discussed in the present work has the potential to be useful during the various stages of reactor design, analysis, and licensing. The lumped-volume approach can be applied for fast turnaround safety calculations to obtain overall reactor behavior during transients. The 1-D models provide improved accuracy when stratification is expected for a relatively low increase in the computational cost. The CFD model can be utilized for confirmatory analysis of the 1-D model, when experimental measurements are not available.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

PELICAN Design, Test Planning, and Commissioning Results

To support design efforts for the Versatile Test Reactor (VTR) core assemblies, an experimental facility has been designed and constructed at Argonne National Laboratory to match the hydraulic flow conditions within the VTR’s primary heat transport system (PHTS). This facility, the Pressure drop Experimental Loop for Investigations of Core Assemblies in advanced Nuclear reactors, PELICAN, provides the ability to measure pressure drop across a full-scale fuel assembly containing prototypic axial reflectors, fuel, and plena components. The PELICAN facility was designed and built to offer maximum flexibility, allowing testing from short sub-sections all the way to the full-length core fuel assemblies. The report presents the high-level program objectives, a summary of the facility design, instrumentation, and control systems, and the testing procedure. The outcomes from facility characterization efforts and first test matrix results are then presented and then, finally, the conclusion contains a summary of the future work to be performed. This test facility was designed to match the hydraulic conditions of the flowing sodium in the VTR using water as a surrogate fluid. To do so, the water is elevated to a temperature of 110°C where its viscosity matches that of sodium, and with a 50-HP centrifugal pump, is capable of generating full scale flow rates to achieve prototypic Reynolds and Euler number flow conditions. To prevent boiling, the system is maintained at elevated pressure of at least 2.7-3.0 bar (40-44 psig). A set of 15 tests have been used to perform checkout activities in order to commission the device, survey the capabilities of PELICAN, and generate experimental data at isothermal conditions and over a range of flow rates up to 44 kg/s (700 GPM) to produce datasets used in the verification and validation of VTR design and modeling efforts. Initial testing focused on facility characterization, which assessed the operational capabilities of various control systems. The thermal control system was qualified, including the thermal response of the loop to the heat added by self- and auxiliary heaters, the chiller and heat exchanger systems for removing excess heat, and their coupled ability to maintain steady-state isothermal conditions as desired. Additionally, the pressure control system was verified to ensure necessary operating environments that promote pump health and prevent boiling of loop inventory at high temperatures could be met. With these systems in place, the first set of matrix tests have been carried out using orifice plates with inner diameters of 2.25-inches and 2.5-inches. Orifice plate flow behavior is well covered in scientific literature, and the results find good agreement with the measured pressure drop vs flow rate and those of theoretical predictions. This initial testing not only helps to validate the experiment, but it also produces a high quality data set for a geometry that is easily reproducible for simulations. Finally, the report is concluded with a discussion of the work to come and provides a snapshot of the test articles in the experimental pipeline whose designs are being inspired by the current designs from the VTR.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

RADAI: A Large-Scale Realistic Dataset for Radiation Detection Algorithm Development

Open, realistic datasets are essential for developing and benchmarking radiation detection algorithms, yet they remain scarce. The Radiological Anomaly Detection and Identification (RADAI) project was develop to create datasets that meet the training and testing needs for sophisticated radiation detection algorithms. The RADAI dataset is a large-scale synthetic resource that integrates high-fidelity Monte Carlo simulations with realistic urban scenarios to capture both background variability and source signatures. RADAI models construction-material NORM, people and vehicles, urban clutter, and dynamic environmental effects such as cosmic-ray and rain-induced transients, and they provide list-mode detector data with motion and response modeling suitable for algorithm training and evaluation. The RADAI project resulted in three publicly-released complementary datasets together with an online scoring portal for standardized performance assessment and an open software toolkit that supports data access, augmentation, model development, and evaluation. These resources enable reproducible comparisons across methods and promote rigorous studies at the scale required by contemporary machine learning. By grounding algorithm development in realistic, well-documented conditions, RADAI supports progress toward more robust detection, identification, and localization in complex urban environments.

Ghawaly, James M. [Division of Computer Science an↗

Validation of Numerical Tools for Calculating Reactivity Feedback in Sodium Fast Reactors Using SEFOR Experimental Data

The Southwest Experimental Fast Oxide Reactor (SEFOR) was an experimental sodium-cooled fast breeder reactor operated from 1969 to 1972 with experiments designed to measure Doppler reactivity feedback in a wide temperature range from around 350 °F to temperatures approaching the melting point of mixed oxide fuel of around 5000 °F, providing valuable data for code validations. Co-supported by the Department of Energy (DOE) Fast Reactor Program (FRP) and the DOE Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, the SEFOR benchmark project focused on using the experimental data to validate numerical tools that are used in industry and academia to design and license sodium-cooled fast reactors (SFRs). By the end of FY-25, substantial progress was achieved in the SEFOR benchmark study. A variety of numerical tools commonly used for modeling SFRs were applied to develop models for SEFOR core configurations I-D, I-E, I-I, and I-J. These included Monte Carlo codes such as MCNP, Serpent, and Shift; deterministic codes such as the legacy Argonne Reactor Computation (ARC) suite and the high-fidelity NEAMS code Griffin; and the system analysis code SAS4A/SASSYS-1 (SAS). Using these models, both SEFOR zero-power experiments and power-ascending tests were successfully simulated. Comparisons were performed against experimental measurements of core criticalities, reflector worth, kinetics parameters (Λ/βeff), isothermal reactivity feedback (from 350 °F to 760 °F at zero power), and power-ascending reactivity feedback (as power increased from 0.4 MW to 17 MW). In general, these comparisons demonstrated very good agreement between numerical results and experimental data. In Fiscal Year 26 (FY-26), the SEFOR benchmark project will continue to address the modeling issues identified in FY-25. Effort will focus on the simulation of reactivity insertion transients in SEFOR core II using the ARC/SAS model. Future work will also focus on incorporating BISON into the SEFOR core modeling process to enable the first Multiphysics simulations of the isothermal tests based on the MOOSE framework.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Mesoscale modeling to inform Bison models of accident tolerant fuel concepts

U 3 Si 2 and doped UO 2 have been under investigation in recent years as potential accident-tolerant fuel concepts. In this report, lower-length scale studies of these fuel concepts carried out during Fiscal Year 2020 are detailed. U 3 Si 2 is a potential accident-tolerant fuel that shows promise due to its high thermal conductivity and higher uranium density relative to UO 2 . However, its swelling and fission gas release behavior in light water reactor (LWR) conditions is relatively unknown. To provide mechanistic insight and determine parameters for engineering-scale fuel performance modeling of pellet-form U 3 Si 2 , phase-field simulations of the growth, interconnection, and venting of intergranular fission gas bubbles were performed. The fractional coverage of the grain boundary and the fraction of bubble area that is vented were calculated as a function of time. From the simulation data, the fractional grain boundary coverage at saturation, an important parameter needed in engineering-scale modeling of swelling and fission gas release, was determined. Multiple simulations were run to determine the uncertainty in the calculated value. The effect of model assumptions and input parameters that are not well known was evaluated. Simulation results are compared to related theoretical and computational work. Based on the simulation results, a value of 0.60 for the fractional grain boundary coverage at saturation is recommended for U 3 Si 2 fuel.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Determination of Molecular Structure and Dynamics of Molten Salts by Advanced Neutron and X-ray Scattering Measurements and Computer Modeling

The design and development of fully functional Molten-Salt Reactors (MSR) require detailed knowledge of the molten salt properties in order to understand and predict the salt’s behavior. Fundamental properties of interest include molecular structure, speciation, and dynamics (such as diffusion coefficients) of salt components and dissolved corrosion and fission products. Computer modeling is necessary to predict changes in physical and chemical properties due to irradiation, burning of dissolved fuel, and corrosion. The modeling requires experimental data, and advanced neutron and x-ray scattering and spectroscopy provide the most reliable and direct determination of the structure (Pair-Distribution Functions, PDF), and dynamics of ions in the melt. This project dealt with both fluoride and chloride salts. The PDFs have been measured by a combination of neutron and x-ray diffraction. We utilized the techniques of isotope substitutions, a very powerful tool available for neutron-scattering, to extract the details of the liquid structure. Although similar measurements have been done before, modern advanced neutron and x-ray-scattering techniques allow collecting the data at much higher resolution and in a wider range of temperatures. Importantly, we were among the first to study fluoride salts by neutron scattering. The importance of impurities and their effects on salt properties have become apparent recently and so new methods of salt purification were developed. We took advantage of these developments to produce reliable data, which have been used for computer simulations of both clean salts and those with added fission and corrosion products most relevant for MSRs. Ab initio molecular dynamics simulations have been performed to understand the multi-component liquid solution, in particular solubility of impurities and thermodynamic interactions in relation to the ionic-cluster structure of the fluid. We applied machine learning to regress from the simulation and experimental data in order to develop a fast-acting model that can handle molten salt with an arbitrary (≥ 10) number of chemical elements and be able to predict chemical potential as a function of composition and temperature. This project resulted in a number of experimental and computer-simulation publications, a patent application, and numerous conference presentations (American Physical Society, American Chemical Society, and The Electrochemical Society among others). Multiple students and postdocs participated and collaborated on aspects of this project. This project seeded new collaborations between MIT and other institutions, such as the University of Massachusetts Lowell, the University of Illinois Urbana-Champaign, the University of California Berkeley, and Oak Ridge and Los Alamos National Labs. As such, this project has had a broad and lasting impact beyond its original scientific scope.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

The Case for and Against a Gadolinium Bias in SCALE: Round 2

The “Opening Arguments” for and against a gadolinium bias in SCALE were presented at the American Nuclear Society Annual Meeting in Philadelphia, Pennsylvania, in June, 2018. Some critical experiments included in the Oak Ridge National Laboratory Verified, Archived Library of Inputs and Data (VALID) indicate a significant bias as a function of gadolinium concentration. Other experiments indicate that no significant bias exists. The work presented here develops a larger suite of gadolinium-bearing benchmark models to further examine code, data, and benchmark performance. The new benchmark models have been reviewed for accuracy, but documentation and review for addition to the VALID library have not been completed. The problematic benchmarks included in VALID are HEU-SOL-THERM-014 and -016. These are two evaluations from a series of experiments from the Institute for Physics and Power Engineering (IPPE), Russia, documented in the International Criticality Safety Benchmark Evaluation Project (ICSBEP) Handbook. The entire set of evaluations also includes HEU-SOL-THERM-015, -017, -018, -019, and -025. Each evaluation contains a different uranium concentration, and different configurations within each evaluation include different gadolinium concentrations. These 7 evaluations contain a total of 52 configurations and form the largest subset of experiments considered, and they allow for a more complete assessment of the performance of these benchmarks than has historically been possible using just the HEU-SOL-THERM-014 and -016 results. Additional solution experiments are considered, including MIX-SOL-THERM-006 and -007 and PU-SOL-THERM-034. MIX-SOL-THERM-007 is in the VALID library, whereas MIX-SOL-THERM-006 and PU-SOL-THERM-034 are not. The results for MIX-SOL THERM-007 have not shown a gadolinium trend. These mixed- and plutonium-fueled solutions include 28 configurations. Some experiments including solid fuel and solid gadolinium are also included. These experiments include highly enriched uranium (HEU) foils moderated with polyethylene in HEU-MET-THERM-010, -016, and -034, and low enriched uranium (LEU) pin arrays with gadolinia absorber rods in LEU-COMP THERM-036 and -043. A total 32 cases with solid fuel are included. The IPPE solution benchmarks show a fairly high degree of variability, but no clear trend as a function of gadolinium concentration can be observed. The mixed- and plutonium-fueled solutions show less variability than the HEU solutions and also no trend relative to gadolinium concentration. The solid-fueled experiments also show no trend as a function of gadolinium content. The entire set of benchmarks shows no clear trend on gadolinium content or the energy of the average neutron lethargy causing fission.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Comparison of Fission Product Release Predictions using PARFUME with Results from the AGR-2 Irradiation Experiment

The PARFUME (PARticle FUel ModEl) code was used to predict fission product release from tristructural isotropic (TRISO) coated fuel particles and compacts during the second irradiation experiment (AGR-2) of the Advanced Gas Reactor Fuel Development and Qualification Program. The PARFUME model for the Advanced Gas reactor (AGR)GR-2 experiment used the fuel compact volume average temperature for each of the 560 days of irradiation to calculate the release of fission products of silver, cesium, and strontium from a representative particle for a select number of AGR -2 compacts. In addition, safety tests were performed on 15 compacts ranging from 1500 to 1800°C to determine fission product release at temperatures that bound reactor accident conditions. PARFUME was used to calculate the fission product release of silver, cesium, strontium, and krypton during these safety tests. Post-irradiation examination (PIE) measurements provided the data on release of fission products from the fuel compacts and fuel particles, and retention of fission products in the compacts outside the silicon carbide (SiC) layer. The predicted fraction release from PARFUME was then compared to PIE measurements.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Fuel performance analysis of fully-resolved TRISO compact

The TRi-structural ISOtropic (TRISO) fuel multilayered coating structure offers multiple barriers to fission product release, enhancing safety and performance. The heterogeneous nature of TRISO fuel compacts, comprising thousands of randomly distributed coated fuel particles embedded in a graphite matrix, creates intricate stress fields and thermal gradients that cannot be accurately modeled using simplified one-dimensional or homogenized approaches. Consequently, three-dimensional modeling enables the prediction of fuel compact dimensional changes, internal pressure buildup, and fission product transport pathways under diverse irradiation and thermal conditions. This capability facilitates detailed analysis of particle-to-particle interactions, matrix cracking mechanisms, and the statistical distribution of coating failures, which directly impact fuel performance and safety margins. This capability is particularly critical for advanced reactors, such as high-temperature gas-cooled reactors and other Generation IV reactor designs where TRISO fuel operates at elevated temperatures and burn-up levels. This work introduces a novel method to generate an optimized packing of TRISO compacts and a complete 3D mesh with random distribution of TRISO particles, which are discretized into each coating component layer.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Multiphysics Simulation of the NASA SIRIUS-CAL Fuel Experiment in the Transient Test Reactor Using Griffin

After approximately 50 years, NASA is restarting efforts to develop nuclear thermal propulsion (NTP) for interplanetary missions. Building upon nuclear engine tests performed from the late 1950s to the early 1970s, the present research and testing focuses on advanced materials and fabrication methods. A number of transient tests have been performed to evaluate materials performance under high-temperature, high-flux conditions, with several more experiments in the pipeline for future testing. The measured data obtained from those tests are being used to validate the Griffin reactor multiphysics code for this particular type of application. Griffin was developed at Idaho National Laboratory (INL) using the MOOSE framework. This article describes the simulation results of the SIRIUS-CAL calibration experiment in the Transient Reactor Test Facility (TREAT). SIRIUS-CAL was the first transient test conducted on NASA fuels, and although the test was performed with a relatively low core peak power, the test specimen survived a temperature exceeding 900 K. Griffin simulations of the experiment successfully matched the reactor’s power transient after calibrating the initial control rod position to match the initial reactor period. The thermal-hydraulics model largely matches the time-dependent response of a thermocouple located within the experiment specimen to within the uncertainty estimate. However, the uncertainty range is significant and must be reduced in the future.

33 ADVANCED PROPULSION SYSTEMS↗

Energy Arbitrage: Comparison of Options for use with LWR Nuclear Power Plants

Arbitrage is the opportunistic buying and selling of a commodity during local pricing valleys and peaks respectively to maximize economic value. This report evaluates options for energy arbitrage integrated with existing light water reactor (LWR) nuclear power plants (NPPs) where nuclear energy could be stored in a variety of forms and later recovered to generate electrical power during periods when grid electricity demand and pricing are high. The forms of energy storage examined in this report include the potential value of batteries, hydrogen, and thermal energy storage for coupling with nuclear power. Various large demand response options are also analyzed, including the production of liquid nitrogen via air separation and liquefaction, liquefaction of hydrogen, compressed hydrogen, and the cryogenic capture of CO2. Demand response refers to dispatchable loads that can cycle up or down depending on-grid electricity demand to aid in balancing the grid. Large demand response options could dispatch to aid nuclear power stations in avoiding power turndowns by providing an alternate disposition for electrical energy by producing marketable products (e.g., liquid nitrogen, hydrogen, or captured CO2). Static conditions were chosen and analyzed in this report for each option. Dynamic operation or optimization of energy arbitrage or demand response are out of scope for this report. The analysis is based on storage systems with discharge capacities of 500 MW for which various durations of storage and costs of charging (electricity cost) are examined. While the value of thermal energy to an industrial user for flexible plant operations has been previously proven as a business case, this report evaluates costs of hydrogen energy storage and leading thermal energy storage options, and large demand response loads that could be integrated with LWRs in comparison to utility-scale battery storage for use of off-peak nuclear energy. Compilation of this information will be used by the Idaho National Laboratory (INL) RAVEN/HERON systems integration and economics tool to evaluate thermal energy dispatch to industrial users. Relative ranking of energy storage options was done using a levelized cost of storage (LCOS) metric which calculates a rough breakeven cost for the system, taking into account the capital and operating costs as well as the revenue from arbitrage. Table ES1 below shows the LCOS for each of the energy storage options considered. First, in the table, lithium iron (Fe) phosphate batteries are listed as the base case for comparison against the other options. Next is hydrogen storage where most of the hydrogen analyses assumed the hydrogen to be produced using solid oxide electrolytic cell (SOEC) high temperature steam electrolysis (HTSE). The others used existing models of polymer electrolyte membrane (PEM) low temperature electrolysis to produce hydrogen. HTSE performance parameters and costs were taken from existing INL models. Various means were assumed to convert the hydrogen to electricity, including PEM fuel cells (FCs) and a gas turbine mixed in a 30 vol% mixture with natural gas. Physical storage (pressure vessels) and geological storage (natural underground features) were used to store the hydrogen as noted. Geological storage is more economical, but the locations are limited because of the requirement for pre-existing geological formations that will support storage. Thermal energy storage (TES) options were also analyzed including electro-thermal energy storage (ETES) and four different liquid sensible heat TES storage media as noted (Hitec, Hitec XL, Therminol-66, and Dowtherm A). The ETES process considered was modified using existing public documentation on an Echogen process and uses a separate supercritical CO2 charge and discharge cycle with sand as the heat storage media.

25 ENERGY STORAGE↗

Automatic information extraction from neutron radiography imaging to estimate axial fuel expansion in $\mathrm{EBR-II}$

Approximately 130,000 metal fuel pins were irradiated in the Experimental Breeder Reactor II (EBR-II) during its 30 years of operation to develop and characterize existing and prospective fuels. For many of the metal fuel irradiation experiments, neutron radiography imaging was performed to characterize fuel behavior, like fuel swelling. However, due to the lack of technology or resources, many of the images have not been processed or were processed manually through visual examination. This paper represents first-attempt to develop an image processing algorithm capable of automatically extracting information regarding the degree of fuel swelling from neutron radiography imaging. The algorithm was applied to 120 images of three different metallic fuel pin compositions—U-10Zr, U-8Pu-10Zr, and U-19Pu-10Zr. The algorithm performs operations of image intensity adjustment, image binarization, region finding, and labeling to extract information about fuel swelling. The average growth for U-10Zr was found to be 8.49% with 95% Confidence Interval (CI) [8.33 –8.66%], for U-8Pu-10Zr — 7.50% with 95% CI [7.23 – 7.78%], and for U-19Pu-10Zr — 3.15%, with 95% CI [2.40 – 3.91%]. The results obtained by applying this automatic image processing algorithm are consistent with previously reported studies of the same types of fuels. The automatic image processing algorithm will be expanded to include thousands of available neutron radiography images and different types of fuels to investigate empirical dependencies of fuel swelling, which can be subsequently applied to advanced fuel modeling. Results from this study can later be compared to BISON simulations to further benchmark modeling efforts and develop assessment cases.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Investigation of constituent redistribution in U-Pu-Zr fuels and its dependence on varying Zr content

This contribution investigates fuel constituent segregation and fuel-cladding chemical interactions (FCCI) in three U-Pu-Zr fuel pins irradiated to ~11% burnup in Experimental Breeder Reactor-II as part of the X441 DP-1 experiment. In examined pins, Zr content ranged from 6 to 10 and 14 wt.%, while Pu concentration was constant at 19 wt.% Pu. The primary goal of the investigation was to determine the role Zr content plays in fuel performance and this manuscript provides assessment of both constituent redistribution and FCCI as a function of axial position. FCCI was observed in all pins, though no cladding failure was noted. Optical and scanning electron microscopy (SEM) results show that variation in Zr content alters the number and relative size of constituent redistribution zones in the fuel. For example, larger Zr-rich central regions and smaller U-rich intermediate regions were observed in 14 wt.% Zr fuels. More importantly, all examined fuels have four or more discrete constituent redistribution regions, where each region has dissimilar morphological features. The existence of four to six distinctive regions deviates from traditionally accepted three region redistribution model, highlights complexity of constituent redistribution in this metal fuel, and identifies the need to conduct additional studies using state-of-the-art instrumentation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Dislocation loop evolution in Kr-irradiated ThO 2

Here, the early stage of microstructural evolution of ThO 2 , under krypton irradiation at 600, 800, and 1000°C, was investigated using in situ transmission electron microscopy (TEM). Dislocation loops grew faster, whereas their number density decreased with increasing irradiation temperature. Loop density was found to decrease with ion dose. Interstitial dislocation loops, including Frank loops with Burgers vector of $\textit{a}/3\langle111\rangle$ and perfect loops with Burgers vector of $\textit{a}/2\langle110\rangle$, were determined by traditional TEM and atomic resolution–scanning TEM techniques. Atomistic and mesoscale level modeling are performed to interpret experimental observations. The migration energy barriers of defects in ThO 2 were calculated using density-functional theory. The energetics of different dislocation loop types were studied using molecular dynamics simulations. Loop density and diameter were analyzed using a kinetic rate theory model that considers stoichiometric loop evolution. This analysis reveals that loop growth is governed by the mobility of cation interstitials, whereas loop nucleation is determined by the mobility of anion defects. Lastly, a rate theory model was used to extract the diffusion coefficients of thorium interstitials, oxygen interstitials, and vacancies.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Molecular dynamics studies of grain boundary mobility and anisotropy in BCC γ-uranium

Grain morphologies such as grain size and aspect ratio in uranium-based metallic fuels are important microstructural features that can impact various fuel performance properties such as fission-gas-induced swelling, thermal transport, high burnup structure formation, and radiation resistance. Accurate prediction of the fuel grain morphologies requires knowledge of critical grain growth parameters such as grain boundary (GB) mobility and anisotropy. In this work, molecular dynamics simulations were performed to study the GB mobility and its anisotropy in pure body-centered-cubic (BCC) γ uranium. Nine GBs with different combinations of misorientation angles (20°, 30°, 45°) and rotation axes (<100>, <110>, <111>), as well as an additional <111> 38.2° GB were studied using three interatomic potentials. Here, it is found that the GB mobility anisotropy has complex trends, depending on both rotation axis and misorientation. However, in general the <110> rotation axis has the fastest GB mobility at the same misorientation. The results of this work can be used as not only baselines for future studies of GB mobility in uranium-based alloys such as uranium-molybdenum (U-Mo) fuels, but also input for mesoscale modeling of grain growth in uranium-based alloys.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

SPARC - Plans for a New Critical Experiment Facility with a Horizontal Split Table

Several critical experiment facilities, sometimes referred to as zero power reactor facilities, have provided crucial data to aid understanding and validate nuclear-physics models since the beginning of nuclear technology. Indeed, the first man-made reactor, Chicago Pile-1, was essentially this type of reactor. However, there was a downturn in nuclear technology development toward the turn of the millennium, and the need for these specialized research facilities waned. Now there are few of these experimental facilities operational in the world and those that remain have relatively small critical assembly machines. The need for criticality safety benchmark experiments at intermediate neutron energy levels and the modern resurgence of interest in advanced reactors designs, many of which do not have historical precedents in terms of nuclear fuel composition, moderator, and coolant combinations, all combine to create a substantial need for a critical experiment facility with a large horizontal split-table (HST) machine. A HST machine is used to arrange two separate and subcritical parts of a core assembly, bring them together in a precise manner to achieve criticality using remote controls, and separate them to achieve a subcritical configuration again. A new effort was recently performed to develop user needs for a HST, assess candidate locations at the Idaho National Laboratory (INL), and develop a plan for deployment. This project is referred to as the System Physics Advanced Reactor Critical facility (SPARC). A few months after this assessment began, and shortly after as a viable pathway was emerging, a series of important presidential executive orders were issued to revitalize nuclear energy in the United States (U.S.). The relevance of SPARC to these executive orders was immediately apparent. The far-reaching potential of SPARC to these executive orders will reside in its ability to produce data which facilitates licensing of advanced nuclear reactor designs while reducing uncertainties to help increase energy production alongside new criticality safety data to enable more efficient nuclear fuel manufacture, transport, and storage.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

New systems in MOOSE

The Multiphysics Object-Oriented Simulation Environment (MOOSE) serves as a common library of classes between applications developed for advanced reactor analysis, fusion device engineering, spent fuel cask analysis, geochemistry studies, among other fields. These applications drive the development of the framework to meet their needs. Systems in MOOSE group capabilities that share a common purpose and generally common code. They can be leveraged by all downstream applications, providing extensive code re-use and shared maintenance. They facilitate the discovery by new users of the classes meeting at least partially their needs, and offer the same opportunities for customization as other systems. The addition of a new system to MOOSE opens new ways of solving or discretizing nonlinear problems, of performing distributed postprocessing, and a plethora of other needs. While new systems can be introduced in downstream applications rather than at the framework level, the framework team monitors common needs across the community and often triggers their addition. Documentation, training material, development needs can be centralized, limiting duplicated work across the community. The last three years have seen a large expansion in the capabilities of MOOSE. The supporting role of the framework in the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program has created numerous feature requests to support neutronics, thermal hydraulics, computational fluid dynamics and thermo-mechanics simulations in the Griffin, SAM, Pronghorn and Bison applications respectively. Similarly, laboratory-directed research and development (LDRD) projects in additive manufacturing, high-Reynolds flow simulations, structure optimization also necessitate an expansion of the framework capabilities. This summary reports on the new systems created in MOOSE, their design, their capabilities and some of the relevant interfaces.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗