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At least 127 records · Page 7

Delineating Confinement Regimes for Nafion Thin Films via Simultaneous QCM-D and Spectroscopic Ellipsometry

Proton-conducting ionomers used in electrodes of electrochemical devices form nanometer-scale films covering metallic catalyst surfaces, wherein they experience confinement and interfacial effects absent in the bulk polymer. This confinement alters the physical properties of the ionomer film, which is postulated to increase the density and is attributed to the transport limitations observed in fuel-cell electrodes. Despite studies showing reduced swelling, no systematic measurement has validated this phenomenon by demonstrating both densification and stiffening as the film gets thinner. Here, this study aims to fill this gap by reporting the humidity-driven changes in swelling, mass uptake, and density of Nafion ionomer films cast at varying thicknesses (10–320 nm) onto a gold-plated sensor. The films were simultaneously probed during humidification using spectroscopic ellipsometry (SE) and a quartz crystal microbalance with dissipation (QCM-D), which allowed for determination of the density and shear stiffness. The effects of confinement were prominently observed below ∼30 nm, with films showing increased density along with decreased swelling and mass uptake during hydration. In addition, the confined films show a negative excess volume upon initial water sorption, implying a larger proportion of absorbed water might bound to ionic groups in accord with notion of localized densification.

Espinet, Kevin B. [University of California, Berke↗

RU Net for Automatic Characterization of TRISO Fuel Cross Sections

TRistructural ISOtropic (TRISO) particle fuel is a type of nuclear fuel known for its high-temperature and high-burnup performance. Each sub-millimeter diameter TRISO particle consists of uranium-oxycarbide (UCO) or UO2 fuel kernel, coated with buffer, inner pyrolytic carbon (IPyC), silicon carbide (SiC), and outer pyrolytic carbon (OPyC) layers. The SiC layer acts as the main containment barrier for the TRISO particle to retain the fission products, while the IPyC and OPyC layers provide additional barriers to the release of fission products, especially fission gases. During irradiation, phenomena like kernel swelling, buffer densification, and IPyC fracture may impact fuel performance. Post-irradiation microscopy on entire compact cross sections or samples of individual particles deconsolidated from compacts is often used to identify these irradiation-induced changes in morphology. However, each fuel compact generally contains thousands of TRISO particles. To get statistical information on these phenomena, it is cumbersome work if done manually. For example, to get information about swelling/densification behaviors of different layers or kernels after irradiation, researchers previously manually measured the perimeter of each TRISO layer in hundreds of particles after four rounds of iterative grinding and polishing encompassing more than 2000 cross-section images for a total of four fuel compacts. To attempt to reduce the subjectivity inherent in that process and accelerate data analysis, we conducted a study on the automatic TRISO layer segmentation on cross-sectional microscopic images using Convolutional Neural Networks (CNNs). CNNs are a class of machine learning algorithms specifically designed for processing structured grid data that have gained popularity in recent years due to their remarkable performance in various computer vision tasks, including image classification, object detection, and image segmentation. In this research, we have generated the large irradiated TRISO layer dataset with more than 2000 cross-section TRISO microscopic images and the corresponding annotated images. Based on these annotated images, we have employed different CNNs for automatic segmentation of different TRISO layers. These include RU-Net (developed in this study), as well as three existing architectures: U-Net, Residual Network (ResNet), and Attention U-Net. The preliminary results show that the model based on RU-Net has the best performance in terms of intersection-over-union (IoU). Through the aid of these CNN models, we can expedite the analysis of TRISO particle cross-sections, significantly reducing the manual labor involved and improving the objectivity of the segmentation results.

Convolutional Neural Networks↗

Design of a first-of-A-kind instrumented advanced test reactor irradiation Capsule experiment for In situ thermal conductivity measurements of metallic fuel

Metallic fuel undergoes dramatic microstructural changes early in life due to fission gas swelling until ~2–3 at% burnup which affects the conductivity of the material, however the evolution of metallic fuel thermal conductivity during this early phase burnup has never been successfully measured in situ. The Irradiated Material Properties Accelerated Characterization Test (IMPACT) experiment will be the first in a series of experiments to irradiate advanced nuclear metallic fuel specimens with novel embedded thermal conductivity probes in ATR. In the current work the IMPACT experiment final design and supporting analysis is reported in detail. Results are evaluated for various reactor operational conditions to meet the functional requirements of the experiment. Finally, the first iteration of this IMPACT experiment will provide data regarding thermal properties evolution in uranium-zirconium (U10Zr) fuel, but this experiment vehicle is envisioned for future advanced fuels and structural materials irradiations in ATR.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Development and formulation of physics based metallic fuel models and comparison to integral irradiation data

Metallic fuel has an important historical significance in the development of nuclear reactors and continues to be relevant to the progression of advanced test and power reactors. A number of models, ranging from empirical to mechanistic, have been developed and implemented in various fuel performance codes to describe U-Zr and U-Pu-Zr fuel and typical fast reactor cladding materials. One challenge of using these models to simulate fuel performance is the inevitable tangling of coupled phenomena that can cloud proper implementation, calibration, and eventual utilization of new models. Here in an effort to provide a baseline capability that will facilitate the use of advanced models, new capabilities have been implemented into the fuel performance code BISON specific to metallic fuel simulations, ranging from materials properties, fission gas release and swelling calculations, coolant channel models, and cladding correlations. These models have been applied to the X441/X441A EBR-II experimental assembly data, a set of irradiated metallic UPuZr fuel rods of varying pin designs. The models implemented in BISON are able to capture the general trend of the expected response of the fuel and cladding to irradiation in EBR-II, especially when considering the spread in experimental measurements and the uncertainties inherited from the historical material models. Ultimately, the models outlined here provide the baseline capabilities on which new models can build upon in order to improve the prediction of metallic fuel performance simulations in off-normal designs or operations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Qualification and Quantification of Porosity at the Top of the Fuel Pins in Metallic Fuels Using Image Processing

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, such as fuel axial expansion. While several fuel expansion results obtained from neutron radiography imaging have been published, the analysis of neutron radiography for the purpose of describing statistical properties of porous matter formed on top of the fuel pins, also referred to as fluff in previous publications, is significantly less represented in the literature with just a single paper so far. This study aims to validate and augment results reported in previous publications using automated image processing. The paper describes the statistical properties of the porous matter in terms of nine parameters derived from radiography images and correlates those parameters with such fuel properties as composition, expansion, temperature, and burnup. The reported results are based on 1097 fuel pins of eight different fuel compositions. For three major fuel types, U-10Zr, U-8Pu-10Zr, and U-19Pu-10Zr, a clear negative correlation is found between the Pu content and five parameters describing the amount of porous matter generated. The parameters describing granularity properties, however, showed either negative correlation or nonlinear dependency from fuel composition. The parameters describing the amount showed a positive correlation with fuel axial expansion, while granularity parameters showed a negative correlation with axial expansion. The dependency on cladding temperature was found to be weak. A positive correlation is demonstrated for volume parameters and fuel burnup. In general, reported results confirm and validate findings published in previous studies using a much larger number of pins and automated processing techniques, which easily lend themselves to reproducibility, thus avoiding subjective bias.

36 MATERIALS SCIENCE↗

Sustainable Aviation Fuel via Hydroprocessing of Catalytic Fast Pyrolysis Oil

Cycloalkanes have been identified as a promising alternative for sustainable aviation fuel (SAF) in a recent US Department of Energy Review of Technical Pathways to SAF. Cycloalkanes can provide desirable SAF properties, including energy density, and, in addition, they may be able to provide necessary seal swelling and leakage protection and replace undesirable aromatics in aviation fuel. Catalytic fast pyrolysis (CFP) followed by hydroprocessing constitutes a platform well suited for converting biomass to cycloalkanes. CFP oils are rich in phenolic compounds and, depending on CFP catalyst, in aromatic hydrocarbons, which can both be hydrogenated to form cycloalkanes. In this work, we report results from hydroprocessing of two types of CFP oil to produce fractions boiling in the sustainable aviation fuel range and meeting tested aviation fuel specifications. CFP oils prepared over a zeolite catalyst (ZSM-5) and a hydrodeoxygenation catalyst (Pt/TiO2) were hydroprocessed over a sulfided NiMo/Al2O3 catalyst in a two-stage process (1st stage ~250 degrees C and 2nd stage 385 degrees C) in a continuous trickle-bed hydrotreater. The hydrotreated product contained 39-40% material boiling in the SAF range by distillation with a carbon efficiency of 36-37% from CFP oil to SAF fraction. The SAF fractions consisted of 82-87% of cycloalkanes, had non-detectable oxygen contents and lower heating values (LHV) above the jet fuel minimum limit of 42.8 MJ/kg. The SAF-range product also had acceptable volatility and freeze and flash points per aviation fuel specifications. The results suggest a promising pathway for SAF production via the catalytic fast pyrolysis pathway. Methods to enhance the yield of SAF will be discussed.

BASIC BIOLOGICAL SCIENCES,BIOMASS FUELS↗

Compatibility of Elastomers with Polyoxymethylene Dimethyl Ethers and Blends with Diesel

Polyoxymethylene dimethyl ethers (PODEs) have shown promise as candidates for diesel fuel blendstocks due to their low sooting tendency, high cetane number, and diesel-comparable boiling point range. However, there is a lack of literature regarding compatibility of PODEs with common automotive elastomers, which would be a prerequisite to their adoption into the marketplace. To address this need, an exposure study and complementary solubility analysis were undertaken. A commercially available blend of PODEs with polymerization degree ranging from 3 to 6 was blended with diesel certification fuel at 0, 33, 50, 67, at 100% by mass. Elastomer coupons were exposed to the various blends for a period of 4 weeks and evaluated for volume swell. The elastomer materials included multiple fluoroelastomers (Viton and fluorosilicone) and acrylonitrile butadiene rubbers (NBR), as well as neoprene, polyurethane, epichlorohydrin (ECO), PVC-nitrile blend (OZO), ethylene propylene diene monomer (EPDM), styrene-butadiene rubber (SBR), and silicone. The exposure results indicated overall poor compatibility for PODE, with every elastomer except for fluorosilicone exhibiting greater than 30% volume swell at the 33% blend level. The general trend across the elastomers was either a consistent increase in volume swell with PODE concentration, or maximum in volume swell at an intermediate blend fraction. One notable exception is EPDM, which is not generally compatible with diesel fuel and which exhibited a reduction in volume swell with increasing PODE concentration. The same elastomers and PODE/diesel blends were evaluated using Hansen solubility parameter analysis, which predicted similar trends to the exposure study with the exception of ECO. From these results, we conclude that adoption of PODEs as a diesel fuel blendstock will require either the development of specialized elastomers, or that the blend fraction be kept to a low level to maintain compatibility with existing elastomers.

42 ENGINEERING↗

Cluster dynamics simulation of xenon diffusion during irradiation in UO 2

Diffusion of fission gas in UO 2 nuclear fuel impacts several important performance metrics, such as fission gas release, swelling, and thermal conductivity. Current empirical models of fission gas release have significant uncertainty, some of which derives from the bulk diffusion rate and its dependence on, for example, fuel chemistry and irradiation. In this work, we have applied the previously-developed Free Energy Cluster Dynamics (FECD) methodology in the code Centipede to calculate xenon cluster concentrations in UO 2 under intrinsic (high temperature) and irradiation-enhanced (intermediate temperature) conditions in order to develop a model of the xenon diffusion coefficient based on the atomic scale mechanisms responsible for transport. While the diffusion mechanism for xenon in UO 2 is adequately described by the Xe + U 2 O vacancy cluster for intrinsic conditions, a similar process is not capable of capturing measured in-pile fission gas diffusivity at intermediate temperatures. Therefore, a different diffusion mechanism must dominate under this regime. Using calculated atomistic data, we have shown that irradiation-enhanced diffusion at intermediate temperatures occurs via the larger Xe + U 4 O y vacancy clusters, which have lower migration barriers and increase in concentration by several orders of magnitude compared to intrinsic conditions. This mechanism is enabled by the increased uranium vacancy concentration under irradiation due to Frenkel pair production. In addition, the fast migration of uranium interstitials with two attached oxygen interstitials lowers the total uranium interstitial concentration through reactions with sinks. This allows the extended defects, such as Xe + U 4 O y vacancy clusters, to maintain high concentrations by limiting annihilation with attached vacancies. Furthermore, predictions using the Xe + U 4 O y diffusion mechanism are in good agreement with experiment, albeit with some differences in the Arrhenius slope, which we believe may be related to either experimental or model parameter uncertainty. Lastly, an analytical expression suitable for application in fuel performance simulations was derived to capture the predictions of the Centipede simulations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Diffusion of small anti-Schottky clusters in UO 2

The aggregation of irradiation-induced defect clusters in UO 2 leads to the formation of dislocation loops and cavities which contribute swelling and ultimately produce deleterious effects on the fuel. Despite their fundamental role in fuel evolution, the kinetics of these defect clusters are not currently well understood. In this work, we investigate the diffusive behavior of interstitial clusters via Molecular Dynamics (MD) simulations. In this work, our investigation considers a range of defect cluster sizes, each composed of N UO 2 units or anti-Schottky defects. We report a complex cluster size - mobility relation; increasing cluster size corresponds to an increase in mobility up until a critical size (N=4) where diffusivity reaches a maximum, after which the trend reverts and further increasing size corresponds to a decrease in mobility. The rapid migration observed correlates well with the very low barriers reported in a few historic experimental studies. Further analysis of the cluster shape and orientation reveals a strong structural preference for near-planar configurations oriented normal to the $\langle$100$\rangle$ direction. Rotational energy barriers are found to be similar in both magnitude and trend to the observed diffusion barriers. Lastly, connections are drawn to the behavior of large defect clusters including the formation of (1/3) $\langle$111$\rangle$ Frank dislocation loops.

36 MATERIALS SCIENCE↗

Microstructure, Thermal, and Mechanical Properties Relationships in U and UZr Alloys (Final Report)

Uranium-zirconium (U-Zr) alloys are candidate fuel systems for transmutation based reactors that can be used to burn long-lived minor actinides and fission products in fast spectrum reactors. Metallic fuels have also been gaining more recent attention for applications as accident tolerant fuels, as well as for use in small modular reactors. This research focused on a “science-based” approach to capture the connections between U and U-Zr alloys’ three-dimensional (3-D) microstructure, thermal properties, and mechanical properties through closely coordinated experiments and modeling efforts from the unirradiated to the irradiated fuels. Advanced characterization and modeling techniques were used to understand irradiation-induced microstructural evolution and its direct impact on the thermal and mechanical properties of U and U-Zr fuel. Closely coordinated experiments and modeling were performed to provide crucial data that does not currently exist. Overall, this research spanned multiple length and time scales within the models and experiments. The scope of the research encompassed the understanding of the irradiation effects in U and various U-Zr alloys with particular attention paid to three task areas: (1) microstructural evolution, (2) in-situ/ex-situ thermal and mechanical properties, and (3) multiscale modeling connections to microstructure, thermal, and mechanical properties. This research resulted in (1) the 3-D characterization of neutron irradiated U-Zr fuel in multiple phase regions to better understand fission gas swelling and constituent redistribution, (2) development of a microstructural model linking thermal and mechanical properties via in situ Raman and nanoindentation, (3) and mesoscale phase field modeling was coupled with the AEH method in the MOOSE framework was used to calculate the effective thermal conductivities of U-Zr fuels consisting of α-U and δ-UZr 2 heterogeneous microstructures.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

The use of U3Si2/Al dispersion fuel for high power research reactors

In order to investigate the irradiation performance of U3Si2/Al dispersion fuel at relatively aggressive reactor conditions, compared to how this fuel is typically used in a research or test reactor, post irradiation examination was performed on two fuel plates that were irradiated at ~270 W/cm2 average surface heat flux and to a maximum local burnup greater than 8 × 1021 fissions/cm3 in the Advanced Test Reactor as part of the RERTR-8 experiment. As part of the non-destructive examinations that were performed on both fuel plates, detailed thickness measurements using a high-fidelity measurement bench were performed on one fuel plate and a segment of the second fuel plate. This paper provides the first reported results of such high-resolution thickness measurements for U3Si2/Al dispersion fuel plates, containing primarily the U3Si2 fuel phase, irradiated at such power levels to high burnup. For destructive examination using optical metallography, samples were generated from both irradiated plates. Localized regions of high swelling (characteristic of internal blistering) were observed on the surface of both fuel plates, suggesting that the performance limits had been reached for each plate. Destructive examinations showed that the fuel particles that are primarily U3Si2, which become amorphous during irradiation, in both plates contained relatively large fission gas bubbles with evidence of fission gas bubble interconnection.

Wachs, Daniel M.↗

Method for measurement of TRISO kernel and layer volumes by X-ray computed tomography

Layer dimensions are key parameters for as-fabricated tristructural-isotropic (TRISO) particle fuel as well as for post-irradiation examination of particle performance. Layer thicknesses are typically measured by optical microscopy of the particle cross section near mid-plane, while layer volumes are estimated with serial sectioning and microscopy. This method for measuring layer volumes is limited due to the resolution limit imposed by slice thickness and the effect of the polishing process on delicate irradiated particle microstructures. In this study, image processing software has been developed to segregate the three-dimensional (3D) TRISO particle images provided by x-ray computed tomography (XCT) into high-resolution volumetric data for the kernel, all particle layers, and any internal voids introduced during irradiation. These data can be used to analyze key in-reactor behaviors of TRISO particles such as kernel swelling or buffer shrinkage, which are important inputs for fuel performance modeling.

36 MATERIALS SCIENCE↗

Self-assembly of solid nanoclusters in molybdenum under gas ion implantation

The self-assembly of defects in materials could create unique physical and chemical properties. In nuclear fuels, the formation of self-assembled fission products mitigates fission-gas-release and swelling. In this work, we report the formation of a solid nanocluster superlattice in molybdenum, an important constituent in metallic fuels, under krypton gas ion implantation. X-ray absorption near edge structure measurements coupled with density functional theory calculations show that the pressure of krypton nanoclusters in molybdenum is ~2 GPa and molecular dynamic simulations reveal that the krypton atoms are solid in the nanoclusters with a krypton-to-vacancy ratio of ~0.28 at 300 K.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Evaluation of Irradiation Creep Effects in HT9 Cladding for FAST Experiments

The push for advanced reactor fuels for improved reactor safety and efficiency had led to a renewed interest in metallic fuel for nuclear reactor applications. Experimental investigation is necessary to ensure a robust understanding of the thermomechanical properties of new metallic fuel designs. Unfortunately, with the current experimental facilities, thoroughly investigating the responses of metallic fuel burnup would take a prohibitively long time. To alleviate this, the Fission Accelerated Steady State Test (FAST) was developed to accelerate the irradiation testing while simultaneously decreasing the sensitivity to fabrication tolerances by reducing the fuel diameter and scaling the experiment. This method successfully scales the radiation effects on the fuel, but the HT9 cladding is not exposed to prototypic radiation conditions. This raises questions on whether the FAST experiment results are truly indicative of the HT9 cladding performance due to radiation induced creep effects not being appropriately accounted for. Using BISON fuel performance code, the simulated FAST cladding strain is compared to simulated EBR-II cladding strain. This is done through a sensitivity study of input parameters and scaling of neutron fluence on the cladding. This allows a parametric comparison of physical phenomena on the effective difference between cladding strains between FAST and equivalent burnup EBR-II fuel pins. The results show that the irradiation induced deformation (creep or swelling) is insignificant compared to the thermal-mechanical deformation. Therefore, the difference between the FAST experiment cladding and the EBR-II experiment cladding is negligible and comparison of fuel system performance between the two experiments is appropriate.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Phase-field simulations of fission gas bubble growth and interconnection in U-(Pu)-Zr nuclear fuel

Abstract The growth and interconnection of fission gas bubbles in the hotter central regions of U-(Pu)-Zr nuclear fuel has been simulated with a phase-field model. The Cahn-Hilliard equation was used to represent the two-phase microstructure, with a single defect species. The volume fraction of the bubble phase and surface area of the bubble-matrix interface were determined during growth and interconnection. Surface area increased rapidly during the initial stages of growth, then slowed and finally decreased as bubble interconnection began and coarsening acted to reduce surface area. The fraction of the bubbles vented to a simulation domain boundary, f V , was quantified as a measure of the microstructure’s interconnectivity and plotted as a function of porosity p . The defect species diffusivity was varied; although changes in diffusivity significantly affected the microstructure, the plots of f V vs. p did not change significantly. The percolation threshold p c was calculated to be approximately 0.26, depending on the assumed diffusivity and using an initial bubble number density based on experimental observations. This is slightly smaller than the percolation threshold for continuum percolation of overlapping 3D spheres. The simulation results were used to parameterize two different engineering-scale swelling models for U-(Pu)-Zr in the nuclear fuel performance code BISON.

Aagesen, Larry K. (ORCID:000000034936676X)↗

Swelling and Fission Gas Release of U-10Mo and U-17Mo Following Neutron Irradiation at 250 – 500°C

The performance of metallic fuel alloys, U-10Mo and U-17Mo, was examined using the MiniFuel test system in the High Flux Isotope Reactor. Approximately 0.8 mm thick disks were irradiated at target temperatures of 250°C, 350°C, 450°C, and 500°C up to three different fission densities, culminating at a maximum fission density of 6.8 × 10 20 cm −3 . Fission rates decayed from 3 – 6 × 10 13 cm −3 s −1 to 2 – 4 × 10 13 cm −3 s −1 over the course of the longest, eight cycle, irradiation as the 235 U was consumed and the 239 Pu concentration accumulated. Actual irradiation temperature on the last day of irradiation was measured via dilatometry using the SiC passive thermometry recovered from the MiniFuel subcapsules and compared favorably with the thermal calculations using as-built geometry and test conditions. Furthermore, average simulated temperatures were within 50°C of the target temperatures, except for the 500°C irradiation, for which the temperature variation was 62°C, 32°C, and 90°C in the in two, four, and eight cycle irradiations, respectively. Fission gas release (FGR) measurements showed no release above recoil for any U-17Mo fuels or for the U-10Mo fuel irradiated at 250°C. Finally, significant (40%–80%) FGR was found for the medium- to highest-burnup U-10Mo samples irradiated at target temperatures 350°C–500°C. Significant FGR correlated with sample thickness swelling, which was as high as 13%–35% for high-release samples and below 7% for all other (low–gas release) samples.

FGR↗

Building Structure-Property Relationships of Cycloalkanes in Support of Their Use in Sustainable Aviation Fuels

In 2018 13.7 EJ of fuel were consumed by the global commercial aviation industry. Worldwide, demand will increase into the foreseeable future. Developing Sustainable Aviation Fuels (SAFs), with decreased CO 2 and soot emissions, will be pivotal to the on-going mitigation efforts against global warming. Minimizing aromatics in aviation fuel is desirable because of the high propensity of aromatics to produce soot during combustion. Because aromatics cause o-rings to swell, they are important for maintaining engine seals, and must be present in at least 8 vol% under ASTM-D7566. Recently, cycloalkanes have been shown to exhibit some o-ring swelling behavior, possibly making them an attractive substitute to decrease the aromatic content of aviation fuel. Cycloalkanes must meet specifications for a number of other physical properties to be compatible with jet fuel, and these properties can vary greatly with the cycloalkane chemical structure, making their selection difficult. Building a database of structure-property relationships (SPR) for cycloalkanes greatly facilitates their furthered inclusion into aviation fuels. The work presented in this paper develops SPRs by building a data set that includes physical properties important to the aviation industry. The physical properties considered are energy density, specific energy, melting point, density, flashpoint, the Hansen solubility parameter, and the yield sooting index (YSI). Further, our data set includes cycloalkanes drawn from the following structural groups: fused cycloalkanes, n-alkylcycloalkanes, branched cycloalkanes, multiple substituted cycloalkanes, and cycloalkanes with different ring sizes. In addition, a select number of cycloalkanes are blended into Jet-A fuel (POSF-10325) at 10 and 30 wt%. Comparison of neat and blended physical properties are presented. One major finding is that ring expanded systems, those with more than six carbons, have excellent potential for inclusion in SAFs. Our data also indicate that polysubstituted cycloalkanes have higher YSI values.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Data-driven methods for diffusivity prediction in nuclear fuels

The growth rate of structural defects in nuclear fuels under irradiation is intrinsically related to the diffusion rates of the defects in the fuel lattice. The generation and growth of atomistic structural defects can significantly alter the performance characteristics of the fuel. This alteration of functionality must be accurately captured to qualify a nuclear fuel for use in reactors. Predicting the diffusion coefficients of defects and how they impact macroscale properties such as swelling, gas release, and creep is therefore of significant importance in both the design of new nuclear fuels and the assessment of current fuel types. In this article, we apply data-driven methods focusing on machine learning (ML) to determine various diffusion properties of two nuclear fuels—uranium oxide and uranium nitride. We show that using ML can increase, often significantly, the accuracy of predicting diffusivity in nuclear fuels in comparison to current analytical models. We also illustrate how ML can be used to quickly develop fuel models with parameter dependencies that are more complex and robust than what is currently available in the literature. In conclusion, these results suggest there is potential for ML to accelerate the design, qualification, and implementation of nuclear fuels.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗