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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Overcoming challenges to support US resumption of high specific activity cobalt-60

Domestic production of high specific activity 60 Co was halted after a target rupture in 2012 at the Advanced Test Reactor (ATR). The Isotope Program (IP) within the US Department of Energy (DOE) Office of Science tasked a multilaboratory team of researchers and managers from Oak Ridge and Idaho National Laboratories with the redesign the radioisotope capsule. The objective of this effort was to create a more robust and reliable design, compared to the pre-2012 target. The team successfully completed this task to produce the DOE-IP cobalt (Co) production capsule design. Furthermore, 66 capsules were successfully fabricated by Oak Ridge National Laboratory (ORNL) and delivered to Idaho National Laboratory (INL) for irradiation in the ATR between January 2014 and October 2016. This paper describes the efforts of the team to prepare and disposition the two initial DOE-IP Co production capsules that were processed in March 2020. These efforts include performing accurate production predictions, experimentally validating predictions with assay measurements, shipping with the Orano-furnished Battelle Energy Alliance Research Reactor shipping package, and disassembling capsules at the isotope vendor site.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Application of HRGS for forensic characterization of uranium oxides, pure uranium metals and uranium alloys

A nondestructive iterative method for uranium-bearing material characterization with HRGS developed earlier in (J. appl. Rad. Isotopes, 166 (2020) 109433) is applied to determine matrix densities and uranium isotope masses of a variety of uranium materials, namely uranium ore, UO 2 and U 3 O 8 powders, fuel elements in the form of UO2 microspheres, uranium metal and uranium alloys. It is shown that U 3 O 8 powders with uranium mass fraction of about 84% can be distinguished from the powders of UO 2 with uranium mass fraction of about 87%; uranium products in the form of liquid or loose powder with matrix density of 0.5-2.0 g/cm 3 can be distinguished from uranium products in the form of compacted fuel elements with matrix density of 6.0-10.0 g/cm 3 and from pure metal uranium and uranium alloys with matrix density of 14.0- 19.0 g/cm 3 . In fuel microspheres based on UO2 the uranium mass fraction 88.02% measured by HRGS is consistent, within the measurement uncertainties, with the results of isotope dilution mass spectrometry 87.76±0.64 % and also is confirmed by X-ray diffraction technique. The uranium mass fraction of the uranium ore estimated as 0.08% by HRGS is consistent, within the measurement uncertainties, with the value 0.09±0.01% determined with WDXRF. Densities of two different uranium metal samples, estimated as 18.42 g/cm 3 and 19.33 g/cm 3 by HRGS are consistent with values 18.24±0.55 g/cm 3 and 18.86±0.59 g/cm 3 , respectively, obtained by the gas pycnometry technique.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Development of the generation III (ATR generation I) Plutonium-238 production target design

A domestic supply chain to produce 238 Pu fuel for radioisotope thermoelectric generators is critical for enabling future space exploration. A multi-laboratory effort has worked to establish a common target design to efficiently produce 238 Pu in two research reactors. This approach ensures that the annual production goals set forth by NASA are met, while also establishing redundant production capabilities. Here, this paper describes the effort to develop the common target design as well as considerations for future applications for the irradiation platform.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Improving stability of ALD ZrN thin film coatings over U-Mo dispersion fuel

Atomic layer deposition (ALD) of ZrN is a candidate technology for coating U-Mo dispersion fuel as a diffusion barrier coating. During the early development stages of the coating the ZrN deposition showed to be mechanically unstable and ultimately resulted in spalling. Based on experimental outcomes it was found that instabillity can be eliminated through the introduction of a thin amorphous (a) Al 2 O 3 interlayer coating deposited in between the ~1-μm thick ZrN and the U-Mo. substrate. To elucidate these findings simulations were performed with density functional theory (DFT) to measure work of adhesions at different interfaces while finite element modeling (FEM) was performed to measure the residual stress distribution. DFT indicated that the ZrN coating deposited over (a)-Al 2 O 3 is ~2.5 times stronger when compared to direct deposition over U or UO 2 substrate. While calculations from FEM recognized; (1) large stress concentrations can originate from the irregularly distributed native surface oxides (UO 2 ) over U-Mo and (2) stress concentrations can be reduced if those surface UO 2 can be modified to a uniform layer (achieved after application of a 8 nm (a)-Al 2 O 3 interlayer). These results provided explanations and confirmed the role played by interlayer in eliminating the original mechanical instability of the ZrN.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Thermodynamic modeling of KCl-PrCl 3 and KCl-LiCl-PrCl 3 systems

Molten salt electrolysis can recover the actinides from spent nuclear fuels, and it involves a eutectic LiCl-KCl in molten form as an electrolyte. During reprocessing, the concentration of fission products such as La, Nd, Pr, etc., increases and affects the recovery efficiency of the electrolyte. In this work, thermodynamic modeling of KCl-PrCl 3 and KCl-LiCl-PrCl 3 systems was carried out using the CALPHAD (Calculation of Phase Diagrams) approach for the first time. The thermodynamic functions for the pure salts were taken from the SGTE (Scientific Group Thermodata Europe) Substances (SSUB) database. The experimental thermochemical and phase equilibria data available in the literature were used as input for the assessment of KCl-PrCl 3 and KCl-LiCl-PrCl 3 systems. The model parameters for the KCl-LiCl system were adjusted to include the new Gibbs energy descriptions for the pure salts. In addition, the sublattice model for the liquid phase in the LiCl-PrCl 3 system was modified and reassessed to ensure the model compatibility for higher-order extrapolation. There is a good agreement between the experimental and calculated thermochemical and phase diagram data for all the optimized constituent binaries and the ternary system. Furthermore, this work will be beneficial for determining the solubility limit of PrCl 3 in molten LiCl-KCl electrolytes and their thermodynamic properties for improving the efficiency of the pyrochemical process.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Hydrogen uptake in graphite matrix at high temperature

Tritium management is a critical challenge for the next generation of nuclear reactors, such as Fluoride Salt Cooled High Temperature Reactors (FHRs) and High Temperature Gas-cooled Reactors (HTGRs), due to the higher production rate (up to 10,000 times) than conventional Light Water Reactors (LWRs). Graphitic materials employed as moderator, reflector, and fuel pebbles offer a potential pathway for tritium recovery by serving as a sink for tritium. Prediction of uptake capacity under reactor relevant conditions remains a challenge due to a lack of low partial pressure data and significant inter-grade variability of graphite. This study addresses these gaps by providing a comprehensive characterization of hydrogen (as a tritium surrogate) uptake and release behavior in the A3-3 graphite matrix (GM) used in fuel pebbles. Uptake measurements are performed at reactor relevant temperatures of 600- 800 °C, 1-200 Torr hydrogen pressure, and 15-120 min equilibration time, followed by thermal desorption spectroscopy up to 1100 °C. Uptake experiments at different equilibration times demonstrate the role of kinetics in hydrogen uptake, which can be modeled as a diffusion-with-trapping process. In the thermodynamics limit, the Sips adsorption model is shown to capture the uptake in A3-3 GM well. Our campaign provides a set of new results for hydrogen uptake in A3-3, including limiting uptake capacity at 600 °C, apparent diffusion coefficient at 600 °C, and the first estimates of the FHR/HTGR relevant (600 °C, 20 Pa partial pressure) equilibrium uptake capacity and time to saturation. Desorption data highlights a new site for hydrogen uptake, not observed in nuclear graphite, which we attribute to the non-graphitized binder. Using the Kissinger method, we estimate activation energy for release from the desorption peaks, confirming the activation energy for release from the basal planes and providing the first estimate for the activation energy of release from the binder.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Analytical models of hydrogen transport in graphite

The importance of graphite-hydrogen chemical reactions to fusion, fission, and hydrogen storage applications, combined with the rapidly evolving knowledge on the underlying mechanisms, has led to the development of multiple models to describe hydrogen transport in graphite. Significant differences exist among these models, resulting from discrepancies in the modeling assumptions, intended degree of fidelity, and conditions of applicability. This paper attempts at reconciling these apparent differences by providing a comprehensive description of the constitutive equations governing hydrogen transport in graphite at high-temperature, identifying outstanding gaps in knowledge, illustrating how these different models approach them, and proposing alternative analytical formulations grounded on experimental results from hydrogen-graphite studies. Governing equations, closing relations, and simplifying assumptions are discussed for hydrogen transport at the inter-granular and intra-granular level, accompanied by compiled experimental data and illustrated energy diagrams associated to the proposed transport mechanisms. Analytical formulations are provided to reproduce competing hypotheses on the mechanisms, supporting the development of a range of computational models that can enable resolution of outstanding knowledge gaps through comparative testing against experimental data.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

UO 2 + 5 vol% ZrB 2 nano composite nuclear fuels with full boron retention and enhanced oxidation resistance

The boron isotope ( 10 B) can be used as a neutron absorber in UO 2 to control the reactivity of nuclear fuel pellets, however, the boron source can react with oxygen source in UO 2 to form B 2 O 3 that vaporize readily at temperatures above 1200 °C. Unfortunately, the sintering of UO 2 fuel requires hours holding at high temperature (>1700 °C), resulting in an inevitable B loss during sintering and unpredictable B concentration in final product. It is challenging to incorporate boron through a conventional sintering method. In this work, we demonstrated that spark plasma sintering (SPS), a field assisted sintering technology, can effectively densify UO 2 + 5 vol% ZrB 2 composite fuel pellets by rapid consolidation at 1600 °C for a short duration of 5 min under an applied pressure of 40 MPa. Further, thermogravimetric analysis (TGA) measurements confirm that ZrB 2 is fully retained inside the composite fuel pellets. Inside the composite fuel pellets, nano sized ZrB 2 particles are uniformly distributed along the grain boundaries of the UO 2 matrix. The ZrB 2 particle transforms to a glassy B 2 O 3 phase covering the sample surface and grain boundaries of UO 2 matrix after a simple post-sintering annealing at 1000 °C in flowing Argon gas for 4 h. The formed glassy B 2 O 3 slows down the diffusion of oxygen ions and postpones the onset temperature for oxidation of UO 2 from 400 °C to 550 °C. This study demonstrates the capability of SPS, an advanced fuel manufacturing technique, to achieve a full retention of ZrB 2 in UO 2 oxide fuel and increase oxidation resistance through a simple post-sintering annealing. The reported work holds great engineering potential for development of advanced oxide fuel for nuclear application.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Smoothed particle hydrodynamics modeling and analysis of oxide reduction process for uranium oxides

A common kinetic feature for oxide reduction chemical/electrochemical processes is oxygen transport via a porous metallic layer, which has been considered as a rate-determining step for reducing uranium oxides to metallic uranium. Accounting this kinetic behavior must involve the resolution of the moving reactive interface between shrinking oxide and expanding metal phases. This study presents a numerical model using smoothed particles hydrodynamics (SPH) to effectively deal with the evolution of the shrinking core reaction interface and oxygen transport via mass transfer of lithium oxide (Li 2 O) species in multiple mass transfer domains. We successfully validated the proposed model against a theoretical derivation for the oxide reduction process handling a shrinking oxide core with molten salt and metal ash medium on a simple planar geometry. Armed with successful validation results, the model examined a realistic reactant geometry to extend the arguments beyond the one-dimensional analyses, allowing the proposed model to apply to general application scenarios with multi-dimensional geometry. Here, this study demonstrated that the proposed model could simulate and evaluate an arbitrary reaction basket design without iterative experimental trials, which is prohibitive for a scaled high-temperature molten salt study in an inert environment. The construct potentially provides not only deep insights on multiphysics behaviors governing the process dynamics but also a robust framework for evaluating and screening candidate basket designs in the most cost-effective manner.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

A phase field study of the thermal migration of gas bubbles in UO 2 nuclear fuel under temperature gradient

Phase field models are developed to study the gas bubble migration in uranium dioxide nuclear fuel in which a large temperature gradient exists during the operation. In this work, thermal diffusion mechanism for nanosized gas bubbles and vapor transport process for micron-sized gas bubbles are considered, respectively. In both cases, gas bubbles migrate to the high-temperature area. Due to the velocity difference between leading and trailing edges of the gas bubbles, nanosized gas bubbles are elongated along the temperature gradient direction when thermal diffusion is dominated. Micron-sized gas bubbles are either compressed along temperature gradient direction to form lenticular shape bubbles or elongated along temperature gradient direction, depending on the location of the gas bubbles within the fuel pellet. Initial gas bubble radius has no significant effect on the gas bubble migration velocity for both thermal diffusion and vapor transport mechanisms. We notice that the shape change of the gas bubble due to vapor transport mechanism has no significant effect on the migration velocity. Furthermore, the center cavity formation is also captured by our model which is due to the migration and accumulation of lenticular gas bubbles at the center of the fuel pellet. The modeling results compare well with experimental observations and theoretical analysis in the literature.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

A quantitative phase-field model for gas bubble evolution in UO2

Due to the large formation energy of vacancies and noble gas atoms in the form of interstitials or substitutional atoms in nuclear fuel (UO2), the thermodynamic equilibrium concentrations of these species are very low in the nuclear fuel matrix even at very high temperatures, which imposes difficulties upon the quantitative study of bubble evolution via the phase-field method. In this study, a quantitative phase-field model is proposed to deal with this problem. The system’s free energy density is derived according to the principles of thermodynamics, with consideration of the elastic effect and with the use of real material parameters from experiments. The model is useful for the study of the kinetics of gas bubble growth with very dilute concentrations of vacancy and gas atoms in the matrix. This model is applied to study single bubble growth and multiple bubble growth under various concentrations of vacancy and gas atoms and at various temperatures. The elastic effect and the effects of the generation rate of vacancies and gas atoms on bubble growth are analyzed.

low defect concentration, nuclear fuel, gas bubble↗
DOE OSTI2021

Modeling brittle fracture due to anisotropic thermal expansion in polycrystalline materials

Here, this work investigated brittle fracture of polycrystalline materials due to thermal stresses arising from anisotropic thermal expansion. We used phase-field fracture simulations with the properties of alpha-uranium (α-U) and assumed a linear elastic mechanical response. Three-dimensional simulations were used to predict fracture for various conditions and crystallographic textures. We found that fracture was more pronounced during cooling than during heating because the anisotropy increased with temperature. We also found that the total crack surface area increased with increasing average misorientation, while the net shape change of the material decreased with increasing misorientation. Two-dimensional simulations in which one crystallographic coefficient of thermal expansion (CTE) was set to zero indicated that the expansion behavior in the crystallographic direction with the smallest CTE was the primary cause of fracture.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

The impact of anisotropic thermal expansion on the isothermal annealing of polycrystalline α -uranium

Although grain growth impacts microstructural evolution in a wide variety of materials systems, the effect of anisotropic thermal expansion on grain boundary mobility and texture evolution has not been widely studied. Anisotropic thermal expansion occurs in multiple non-cubic metals, and the thermomechanical processing behavior of these materials can be better understood with further study into the impact of thermal expansion on grain boundary mobility and texture evolution. In this work, we develop a mesoscale phase field model of grain growth that includes the effect of anisotropic thermal expansion, which is applied to study polycrystalline α-uranium, a highly anisotropic metal. Three-dimensional simulations on polycrystalline a-uranium with and without thermal expansion eigenstrains are performed to study the grain boundary mobility and texture evolution as a function of temperature. A strain-free temperature of 933 K is selected, and the system is studied at within the range of 873 – 933 K at intervals of ten degrees, resulting in increasing thermal eigenstrain with decreasing temperature. We also estimate a grain boundary mobility prefactor and activation energy based on existing experimental data of isothermal annealing of α-uranium. The grain boundary mobility is found to display significant deviation from Arrhenius behavior with the inclusion of thermal expansion eigenstrain as the amount of thermal eigenstrain (and thus elastic strain energy within the system) increases. This result explains an experimentally observed grain boundary mobility deviation from Arrhenius behavior. Furthermore, the texture evolution is affected, such that the grain orientations become less random with increasing thermal eigenstrain, which could explain experimentally observed texture behavior. These results indicate that the effect of thermal expansion should be considered when predicting the thermomechanical processing behavior of α-uranium and other materials with anisotropic thermal expansion.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

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↗
DOE OSTI2026

Machine learning guided prediction of solute segregation at coherent and semi-coherent metal/oxide interfaces

Investigation of semi-coherent metal/oxide interfaces with misfit dislocations using density functional theory (DFT) is computationally intensive to the point of being prohibitive, as it involves several hundreds to many thousands of atoms. In this study, we examined the solute segregation behavior at the Fe/Y 2 O 3 interface—a model interface for cladding applications in nuclear fission reactors—using a combination of DFT calculations and machine learning (ML) approaches. Both coherent and semi-coherent interfaces were considered. ML models were trained on DFT-calculated segregation energies to identify the key chemical, geometric and strain energy related features that govern solute segregation behavior at coherent Fe/Y 2 O 3 interfaces. Furthermore, it was found that ML models when trained on DFT calculated segregation energy of elements at a coherent interface, comprising of about a hundred-atom supercell, can predict the segregation energy of elements at a semi-coherent Fe/Y 2 O 3 interface (with multiple hundreds of atoms) at a fraction of computational cost (1/35th), with an accuracy comparable to DFT calculations.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Bayesian discovery of optimal reduced order models from mechanistic and experimental data: A case study of Pd penetration in TRISO fuels using BISON

TRistructural ISOtropic (TRISO) particles rely on a silicon carbide (SiC) layer as the primary structural material and barrier to metallic fission products (FPs) release. Accurate prediction of palladium (Pd) transport and penetration is therefore critical for qualifying TRISO fuels for advanced reactors. The empirical correlation for Pd penetration in BISON is derived from historical particle-fuel data, but cannot explain the large scatter in the experimental data that arises from varying experimental conditions. To aid fuel qualification, we previously developed a mechanistic reduced order model (ROM) using BISON that resolves these dependencies. Here, in this work we build on that mechanistic ROM and perform validation and quantify its uncertainty using Bayesian uncertainty quantification (UQ). calibration against a suite of in-pile and out-of-pile experiments spanning particle compositions, geometries, and operating conditions, and we benchmark it against the empirical correlation. Bayesian UQ identifies influential parameters, calibrates them to data, and yields predictive intervals. Results show that while the empirical correlation can be tuned to fit a single experiment type, it transfers poorly; the mechanistic ROM sustains accuracy with credible uncertainty across disparate conditions. This demonstrates a practical path—via Bayesian UQ applied to mechanistic ROMs—to leverage single-effect experiments for inferring in-reactor behavior and supporting TRISO fuel qualification.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗