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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Analysis of spent nuclear fuel multipurpose canister dynamics during rail transportation

The primary mode of spent nuclear fuel transportation within the United States will be by railcar. One such system is the Atlas railcar, which is designed to transport 17 different spent nuclear fuel cask systems, including bare fuel systems and canister fuel systems. In the latter configuration, multipurpose canisters containing spent nuclear fuel may be placed within an overpack for storage, or within a cask for transportation. Compared to bare fuel systems, canister fuel systems have additional degrees of freedom for motion during transportation, because clearance between the cask and canister allows for some motion of the canister to occur relative to the cask. This work investigates the effect of canister motion on the shock and vibration imparted to the spent nuclear fuel within. Structural dynamic analyses have been conducted to identify the effects of canister to cask clearance, presence and type of dunnage, and loading direction and frequency. This modeling study calculates anticipated cask motion, canister motion, and spent nuclear fuel structural dynamic response to normal conditions of transportation railcar motion using finite element analysis methods that were developed to model the rail segment of the ENSA/DOE (Equipos Nucleares S.A., U.S. Department of Energy) multimodal transportation test of 2017.

SNF, UNF, LS-DYNA, dynamics, kinematics, shock, vi↗
DOE OSTI2021

System and method for consolidating used nuclear fuel

A system and method for consolidating used nuclear fuel rods using tools operably suspendable in a recess containing the used nuclear fuel rods. The systems and methods safely consolidate the used nuclear fuel rods in containers.

Rose, Scott E.↗
DOE OSTI2024

A Review of Online Monitoring within Used Nuclear Fuel Recycling Processes

The processing of used nuclear fuels and related materials is often complex and variable. The ability to quickly optimize conditions to the material being processed can aid in increasing efficiency and safety, but requires very quick determination of the conditions present in the feedstock, the process, and the product. Furthermore, accurate quantification of materials such as enriched uranium and plutonium aids in maintaining material accountancy and avoiding nuclear proliferation risks. Traditional analytical methods require process samples to be collected and analyzed in a laboratory, which often takes days to weeks. Online monitoring is suitable for collecting this information nearly instantaneously, enabling much faster optimization of the process or detection of material diversion. Online monitoring is also beneficial as it is typically based on robust and nondestructive analytical methods, so no material is removed as samples. This review examines online monitoring relevant to used nuclear fuel processing for the determination of both chemical and physical parameters. The chemical parameters include quantities such as concentration, isotopic composition, and speciation. These values are often well suited to spectroscopic or spectrometric measurements as they are fast, nondestructive, and easily implemented in an online manner. Physical quantities are often more varied and include temperature, pressure, tank fill levels, and others. Due to the specificity of these quantities, specialized instrumentation is often used. However, this instrumentation is often amendable to online monitoring.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Analysis of Nuclear Fuel Cycle Data

Electricity generated using nuclear power accounted for 18.9% of all electricity consumed in the United States in 2021, putting it in third place behind natural gas (38%) and coal (22%) power plants. Nuclear power plants boast a significantly higher uptime or capacity factor—90% and above—compared to 49.1% for coal fired power plants and 56.6% for natural gas power plants. Renewable energy sources, such as solar photovoltaic (PV) and wind electricity, have lower capacity factors: 24.9% and 36.3%, respectively. In addition, nuclear power is cleaner than both coal and natural gas fired power plants. With the passing of the 2022 Inflation Reduction Act, significant tax credits will be claimed by producers of hydrogen with well-to-gate greenhouse gas (GHG) emissions below 0.45 kg CO 2e /kg H 2 . This has sparked interest in using clean sources of electricity, including nuclear power, to generate H 2 via water electrolysis. As uranium is a primary fuel for modern nuclear power plants, the upstream emissions from nuclear fuel production greatly impact the GHG emissions related to all nuclear power end use. Therefore, it is important to accurately determine the upstream emissions associated with the nuclear fuel cycle of nuclear power production in the United States. In this analysis, the nuclear fuel cycle was separated into distinct steps to allow better understanding of the chemical and energy inputs at each step of the fuel cycle. This also provides details of the GHG emissions at each step in the nuclear fuel cycle. The transportation distance for each step of the fuel cycle was updated to account for the locations of uranium processing facilities along the supply chain of the current U.S. nuclear power plants. Finally, all the updated values were incorporated into Argonne National Laboratory’s Greenhouse Gases, Regulated Emissions, and Energy Use in Technologies (GREET) model.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

The Ethical Aspects of Choosing a Nuclear Fuel Cycle

In this paper, we addressed the problem of choosing a nuclear fuel cycle. Ethical problems related to the choice of a nuclear fuel cycle, such as the depletion of natural uranium reserves, the accumulation of nuclear waste, and the connection with the problems of nonidentity and distributive justice are considered. Here, we examined cultural differences in attitudes toward nuclear safety and the associated ambiguities in the choice of a nuclear fuel cycle. We suggested that the reduction in consumption of natural uranium does not seem to be a feasible way of reducing nuclear waste because of the nonidentity problem.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Nuclear Fuels and Reprocessing Technologies: A U.S. Perspective

Reprocessing and/or waste management issues are of concern to the “back end” of the nuclear fuel cycle. Of course, there are a great many “nuclear fuel cycle” scenarios to consider; if not in practice, then at least in theory. The simplest conceptually is the “once through” fuel cycle in which the spent fuel is discarded. The more complex fuel cycle scenarios involve reprocessing spent nuclear fuels and a family of nuclear reactor technologies to accommodate burning and breeding for various military and commercial needs. Therefore, the selection of a specific “fuel cycle” is what ultimately imposes the engineering requirements of the reprocessing and waste management technologies. No one part is independent of the other parts in a fuel cycle flowsheet; all parts are fully integrated. This paper presents a summary of radiochemical processes, nuclear reactor technologies, nuclear fuel types, and the reprocessing technologies that serve the different nuclear fuel types. Comprehending how this series of topics are related to each other is a prerequisite to understanding the requirements of any reprocessing strategy. The summary materials presented here are selective, as opposed to comprehensive. More detailed information on any one subject can be found in the reference materials.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Seeing the whole picture: Methods for getting the most from micro X-ray computed tomography of TRISO nuclear fuel particles

Tristructural isotropic (TRISO) coated fuel particles are a nuclear fuel form under extensive study for use in advanced nuclear reactor concepts. TRISO fuels are subjected to high temperature neutron irradiations and then examined to assess their performance by determining fission product retention and studying morphological changes. Micro X-ray computed tomography is one method of nondestructively studying the effects of TRISO performance. This work addresses the need for image processing to remove X-ray tomographic reconstruction artifacts that prevent the study of TRISO features, as the TRISO particles’ high Z kernel can introduce metal artifacts that degrade the image quality in the surrounding low Z coating layers. These metal artifacts were reduced by imaging the TRISO particles with both high- and low-energy X-rays and applying a mask to the radiographs obtained with low-energy X-rays to digitally remove the dense fuel kernel region. These masked radiographs were then used to produce a tomographic reconstruction which was combined with the tomographic reconstruction of the high-energy data. This enabled the relatively-low-density TRISO buffer layer to be examined in more detail, providing information on irradiation induced dimensional changes of the coatings. This methodology, which helps see the full picture of a TRISO particle, is not limited to nuclear fuels but can be applied to systems that contain highly attenuating material surrounded by less dense materials.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Optimizing Hydride Stability in U-ZrH x Nuclear Fuel: The “Goldilocks Radius”

Nuclear-powered microreactors show great promise for opening new nuclear energy markets due to the flexibility offered by their rapid/streamlined in-factory fabrication, transportability, and self-regulating nature. The economic benefits of any commercialized nuclear reactor, however, rely on the system’s ability to produce large amounts of heat and efficiently convert that heat into electrical power reliably for long periods of time. Uranium-zirconium hydride (U-ZrH x ) is currently being considered for compact reactor designs because it is a well-known nuclear fuel system that is self-moderating, but this fuel, which has historically been used for research reactors, has not been optimized for commercial power production. Here, this paper analyzes the hydride stability of standard 304 stainless steel–clad U-ZrH x fuel under commercially relevant conditions. Fuel element design parameters, including physical dimensions, as-fabricated hydrogen content, burnup, peak fuel temperature, temperature gradient, operational fuel cycle duration, and volumetric heat generation rate, are discussed with a focus on hydrogen distribution and phase stability within the fuel element. Hydride stability declines more rapidly as the coolant temperature, burnup, and fuel cycle duration increase. Using a fuel-cladding gap material with heat transfer properties superior to air, such as helium or sodium, is essential to prolonging fuel hydride stability. The fuel’s physical dimensions are also important. At very small fuel diameters, the H/Zr ratio in the fuel meat decreases too rapidly due to the hydrogen content’s dependence on fuel meat volume. Conversely, the fuel meat temperature and temperature gradient exacerbate hydrogen loss at very large fuel diameters. We find that the most important parameter to consider when optimizing the hydride stability of U-ZrH x fuel is the relationship between the fuel meat radius and the power density in the fuel. A simple equation is empirically determined that relates the “Goldilocks radius,” that is, the fuel radius for which the H/Zr ratio is most stable, to the power density in the fuel.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Multifidelity Active Learning for Failure Estimation of TRISO Nuclear Fuel

The Tristructural isotropic (TRISO)-coated particle fuel is a robust nuclear fuel proposed to be used for multiple modern nuclear technologies. Therefore, characterizing its safety is vital for the reliable operation of nuclear technologies. However, the TRISO fuel failure probabilities are small and the computational model is time consuming to evaluate them using traditional Monte Carlo-type approaches. In the paper, we present a multifidelity active learning approach to efficiently estimate small failure probabilities given an expensive computational model. Active learning suggests the next best training set for optimal subsequent predictive performance and multifidelity modeling uses cheaper low-fidelity models to approximate the high-fidelity model output. After presenting the multifidelity active learning approach, we apply it to efficiently predict TRISO failure probability and make comparisons to the reference results.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

A machine learning approach to quantify degradation of nuclear fuels and the effects of fission products

Nuclear fuel performance is critically dependent on understanding the evolution of fuel properties under operational conditions, a complex challenge driven by chemical changes and substantial radiation damage during fission. Traditionally, property evolution has been determined via empirical data collected following irradiation. However, these empirical correlations are limited in their applicability beyond the specific conditions in which they were obtained. This study explores a novel approach to address this challenge by applying materials informatics to develop a machine learning random forest (ML-RF) model that captures the effects of fission products on fuel compounds. The model predicts formation enthalpy (ΔH f ) by leveraging extensive quantum materials property data and correlating it with material descriptors such as composition, atomic and site features, and crystal lattice properties. This ML-RF model enables rapid interpolation across the compositional and structural spaces covered by the training data, thus supporting high-throughput screening and energetic ranking of candidate phases. The model demonstrates the ability to predict ΔH f with a mean absolute error (MAE) of approximately 0.1 to 0.2 eV/atom across a wide range of compounds, including key nuclear fuel systems (U-O, U-N, U-C, U-Si, and U-Mo). For example, it was used to assess shifts in stoichiometry for UO 2 (O/M) and UN (N/M) fuels, revealing their distinct tendencies in chemical potential variation and enabling preliminary convex hull analyses. Furthermore, the model provides insights into how individual fission products affect fuel properties. Results indicate that larger fission products (e.g., Nd, Pu, Ce) have a more pronounced impact on UO 2 , while lighter ones (e.g., Zr) strongly influence UN. Here, the model developed in this work can be used to support the Accelerated Fuel Qualification approach by facilitating preliminary evaluations prior to extensive materials modeling and experimentation. To this end, the trained model has been made available to the fuel community to support ongoing fuel development efforts.

Accelerated fuel qualification↗
DOE OSTI2024

Acoustic sensing and autoencoder approach for abnormal gas detection in a spent nuclear fuel canister mock-up

Currently, spent nuclear fuel (SNF) from commercial nuclear power plants is stored in stainless-steel canisters for interim dry storage. To provide an inert environment, these canisters are backfilled with helium after vacuum drying. However, the helium environment may be contaminated during extended storage because of the material degradation. For example, the heavier fission gas xenon may be released from the fuel rods into the canister cavity should the fuel cladding be breached. Other gases such as air and water vapor may also be present as a result of leakage caused by chloride-induced stress corrosion cracking on the canister walls or by insufficient vacuum drying. Therefore, monitoring the gas composition can provide critical information about the health of SNF canisters. In this study, noninvasive testing was conducted on a 2/3-scaled SNF canister mock-up using acoustic sensing. Ultrasonic transducers were placed on the exterior surface of the canister to probe the gas composition. A dataset was collected by sealing the canister mock-up and introducing up to 1.53% argon or 1.29% air into the helium background gas. Three methods were used to detect changes in the gas composition: the time-of-flight (TOF) method, the differential method, and the autoencoder method. Results showed that the TOF method had sufficient resolution to detect abnormal gas concentrations of less than 1.0%. The differential method demonstrated a periodic in-phase and out-of-phase behavior between the benchmark (i.e., pure helium) and abnormal (i.e., with argon or air) state signals. The variational autoencoder (VAE) and the Wasserstein autoencoder (WAE) were trained on the benchmark data and were applied directly to the abnormal state data. It was found that both the unsupervised VAE and the WAE were able to distinguish the benchmark and abnormal states of the canister mock-up based on the reconstruction error.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Prospects for additive manufacturing of nuclear fuel forms

Additive manufacturing (AM) is viewed as a critical enabling technology for achieving superior performance and improved economics across many sectors. Although the past decade has seen increased application of AM methods to nuclear reactor cladding and structural materials, exploration of AM as applied to the uranium-bearing nuclear fuel forms has been limited. The two major families of nuclear fuel forms (monolithic, particle/dispersion) are utilized with their own set of core objectives in mind, and their differences require distinct fabrication infrastructures. These reference fabrication methods impose many limitations on nuclear fuels. Further, both currently operating reactors and future concepts have the potential for improved performance if these accepted limitations are relaxed or removed entirely. The primary limitations of reference fabrication processes for the common nuclear fuel forms are outlined in this paper. This groundwork is then used to identify avenues of fuel performance specific to each of these fuel architectures that could be exploited if the restrictions of conventional fuel fabrication are removed. Moreover, multiple targets for AM studies are laid out for each of the major nuclear fuel variants. Finally, key strategic components to guide research activities in AM of nuclear fuels are outlined, with an emphasis on use of modeling and simulation to motivate research aims and embrace of an accelerated testing methodology to screen and quality new fuel forms.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Demonstration of Integrated PostIrradiation Process Steps forMultikilogram Amounts of Low- and High-Burnup Used Nuclear Fuels

sponsored research and development (R&D) on the advanced, closed nuclear fuel cycle, including post-irradiation processing of used fuels, recovery of separated components, and preparation of recycle nuclear fuels. During the period 2007–2010, kilogram-scale demonstrations of the integrated processing steps were performed for actual light water reactor (LWR) used nuclear fuels (UNF). These integrated processing demonstrations were called “the Coupled-End-to-End” (CETE) campaigns and were associated with the Global Nuclear Energy Partnership program, which ran concurrently. The demonstrations were carried out in the shielded hot cells and associated gloveboxes located in the Irradiated Fuels Examination Laboratory (IFEL) and the Radiochemical Engineering Development Center (REDC) at the Oak Ridge National Laboratory (ORNL). Limited circulation program reports and a few technical papers were issued. The subject document provides a comprehensive summary of results, technical comparisons, and conclusions obtained from the demonstration campaigns and subsequent associated R&D.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

The Role of Pulse Radiolysis in Advanced Nuclear Fuel Cycles

The effects of ionizing radiation are ubiquitous throughout all aspects of a nuclear fuel cycle. The complexity and intensity of these effects are greatest during reactor operations and in the management of used nuclear fuel and waste. Radiation-induced processes typically promote the chemical transformation of molecules and materials with the formation of potentially detrimental degradation products and corresponding changes in physical and chemical properties, which ultimately impact the effectiveness and longevity of nuclear technologies. Consequently, a molecular-level understanding of radiation effects over multiple time, distance, and material domains is essential for the innovation and deployment of next generation nuclear technologies. Attaining this knowledge necessitates a firm grasp of radiation-induced reaction kinetics, for which pulsed electron radiolysis is the methodology of choice. Presented here are several recent studies from our group that demonstrate the critical role of pulsed electron radiolysis techniques in the advancement of our understanding of radiation-induced chemistry under advanced nuclear fuel cycle conditions. Research topics include late actinide redox chemistry, radiation robustness of used nuclear fuel reprocessing complexants, and the behavior of metal cations in high temperature molten salt media.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2022

Catalytic Effects of Silver in Iodine Reactors for Dissolved Used Nuclear Fuel

The dissolution of used nuclear fuel generates a variety of off-gasses including flammable hydrogen and other species that are a concern for environmental release. The H-Canyon facility at the Savannah River Site is currently dissolving aluminum-clad research reactor fuel from material test reactors and the High Flux Isotope Reactor (HFIR) using a mercury-catalyzed nitric acid flowsheet. Savannah River National Laboratory recently developed and deployed a Raman spectrometer to monitor the off-gas stream from the dissolution process. Results from these measurements indicated a lack of the expected hydrogen, nitrous oxide, and nitric oxide in the off-gas stream. It was proposed that the silver on the silver nitrate–coated berl saddles present in the reactors for iodine capture were acting as a catalytic hydrogen recombiner. Nitric oxide is readily oxidized to nitrogen dioxide under normal conditions, but it was unclear what happened to the nitrous oxide. A laboratory-scale iodine reactor was assembled and filled with silver nitrate–coated berl saddles to help ascertain the fate of nitrous oxide and hydrogen. Testing with this laboratory-scale reactor observed the recombination of hydrogen when a simulated dissolver off-gas was passed through the reactor containing silver nitrate–coated berl saddles at the approximate temperatures seen in H-Canyon. However, the nitrous oxide concentration was unchanged, suggesting a more complex process occurring within the off-gas stream before it reaches the iodine reactors at H-Canyon.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Elucidating the Radiation-Induced Redox Chemistry of Plutonium Under Used Nuclear Fuel Reprocessing Conditions

Plutonium plays a critical role in the development of sustainable nuclear fuel cycles, and yet, our fundamental understanding of this element’s inherent radiation-induced redox chemistry and associated impacts on nuclear fuel cycle technologies is limited. Unanticipated changes in oxidation state distribution can influence the speciation and transport of plutonium in a given process. Control of these parameters is especially important for used nuclear fuel reprocessing technologies, wherein the separation and recovery of plutonium is typically achieved by the selective formation, maintenance, and complexation of specific oxidation states. Furthermore, plutonium’s inherent radiation-induced redox chemistry has the capacity to influence the radiolytic behavior of its complexes, the longevity of which are critical in the design of efficient and cost-effective advanced reprocessing technologies. These radiation-induced processes are unavoidable under fuel cycle conditions owing to the inherency of ionizing radiation fields to the decay of plutonium’s isotopes and to the various other radioisotopes generated by nuclear fission and neutron-capture process and the subsequent radioactive decay of their products. As such, mechanistically understanding the response of plutonium’s multiple oxidation states to multi-component ionizing radiation fields is essential for predicting the behavior of this critical element under used nuclear fuel reprocessing conditions. Here, through a combination of time-resolved (electron pulse) and steady-state (alpha and gamma) irradiation experiments complemented by quantitative, multiscale modeling calculations, we present advances in our understanding of radiation-induced plutonium redox chemistry!

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Reliability estimation of an advanced nuclear fuel using coupled active learning, multifidelity modeling, and subset simulation

Tristructural isotropic (TRISO)-coated particle fuel is a robust nuclear fuel and determining its reliability is critical for the success of advanced nuclear technologies. However, TRISO failure probabilities are small and the associated computational models are expensive. Here we used coupled active learning, multifidelity modeling, and subset simulation to estimate the failure probabilities of TRISO fuels using several 1D and 2D models. With multifidelity modeling, we replaced expensive high-fidelity (HF) model evaluations with information fusion from two low-fidelity (LF) models. For the 1D TRISO models, we considered three multifidelity modeling strategies: only Kriging, Kriging LF prediction plus Kriging correction, and deep neural network (DNN) LF prediction plus Kriging correction. While the results across these multifidelity modeling strategies compared satisfactorily, strategies employing information fusion from two LF models called the HF model least often. Next, for the 2D TRISO model, we considered two multifidelity modeling strategies: DNN LF prediction plus Kriging correction (data-driven) and 1D TRISO LF prediction plus Kriging correction (physics-based). The physics-based strategy, as expected, consistently required the fewest calls to the HF model. However, the data-driven strategy had a lower overall simulation time since the DNN predictions are instantaneous, and the 1D TRISO model requires a non-negligible simulation time.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗