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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 1,585 records · Page 88
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Samarium isotope compositions of uranium ore concentrates: A novel nuclear forensic signature

Uranium ore is mined and milled to produce uranium ore concentrate (UOC), a regulated product of the nuclear fuel cycle. Additionally, diversion of UOC from the fuel cycle into possible weapons production is a key concern in global nonproliferation efforts. As such, the ability to trace the origin of seized nuclear materials is imperative to law enforcement efforts. Although isotopic signatures of UOCs have proven fruitful to pinpoint sample provenance, new isotopic signatures are needed because most existing isotopic signatures are not indicative of the original ore body from which the U is derived. In this work, we developed a new method to separate samarium (Sm) from a U-rich sample matrix and report the first Sm isotope compositions of 32 UOCs derived from a variety of worldwide uranium mines. Relative to terrestrial standards, approximately half the UOCs have resolved and anticorrelated 149 Sm- 150 Sm isotope compositions, consistent with the capture of thermal neutrons by 149 Sm in the ore body. The UOCs with anomalous Sm isotope compositions tend to derive from older (~>1.5Ga) and higher-grade ore bodies, although other factors, such as the presence of neutron moderators like water, also play a role. Nonetheless, the Sm isotope compositions of UOCs directly reflects the neutron fluence over the history of the original ore body and can be used to discern different geologic conditions associated with that ore body. Overall, this work demonstrates the potential use of Sm isotopes as a novel nuclear forensics signature for origin assessment of UOCs.

58 GEOSCIENCES↗
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

Ceramic–Metal (Cermet) Composites: A Review of Key Properties and Synthesis Methods Focused on Nuclear Waste Immobilization

Here this paper reviews key properties, applications, and examples of ceramic-metal composites (cermets), and metal matrix composites (MMC) with emphasis on their applicability as waste forms for immobilizing nuclear waste. While the literature is mature for vitrified and cementitious radioactive waste forms, cermet materials have not received adequate attention as potential candidates for immobilizing nuclear waste. To promulgate this effort, this review connects cermet and MMC design, such as hardened tools, with the chemistry of radioactive waste streams. A discussion on certification and qualification standards for cermet waste forms, literature gaps, and “how-to” sections on cermet processing techniques. Key parameters discussed include thermal conductivity, chemical durability, and waste loading, as well as examples for metal-containing waste forms. As cermet waste forms gain momentum within the community, this review paper aims ensure the end-of-life nuclear fuel cycle is addressed from a materials and waste disposition perspective.

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

Recent Advances toward Efficient Calculation of Higher Nuclear Derivatives in Quantum Chemistry

In this article, we provide an overview of state-of-the-art techniques that are being developed for efficient calculation of second and higher nuclear derivatives of quantum mechanical (QM) energy. Calculations of nuclear Hessians and anharmonic terms incur high costs and memory and scale poorly with system size. Three emerging classes of methods—machine learning (ML), automatic differentiation (AD), and matrix completion (MC)—have demonstrated promise in overcoming these challenges. We illustrate studies that employ unsupervised ML methods to reduce the need for multiple Hessian calculations in dynamics simulations and those that utilize supervised ML to construct approximate potential energy surfaces and estimate Hessians and anharmonic terms at reduced cost. By extension, if electronic structure operations could be written in a manner similar to functions underlying ML methods, rapid differentiation or AD routines can be employed to inexpensively calculate higher arbitrary-order derivatives. While ML approaches are typically black-box, we describe methods such as compressed sensing (CS) and MC, which explicitly leverage problem-specific mathematical properties of higher derivatives such as sparsity and low-rank, to complete higher derivative information using only a small, incomplete sample. The three classes of methods facilitate reliable predictions of observables ranging from infrared spectra to thermal conductivity and constitute a promising way forward in accurately capturing otherwise intractable higher-order responses of QM energy to nuclear perturbations.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2025

Phosphate-Based Approaches for Dechlorination and Treatment of Salt Waste from Electrochemical Processing of Used Nuclear Fuel: A Perspective on Recent Work

Phosphate-based reagents are being considered by the U.S. Department of Energy (DOE) Office of Nuclear Energy to process halide salt-based nuclear wastes for stabilization prior to disposal. As evidenced by the Experimental Breeder Reactor-II (EBR-II) project, electrochemical processing (pyroprocessing) can be employed to recover uranium and other actinides for reintegration into the nuclear fuel cycle from metallic fuels. The resultant salt-based wastes generated from electrochemical processing of EBR-II fuel contains fission products within a LiCl–KCl eutectic salt that necessitate appropriate disposal. This paper provides an overview of recent efforts to support halide-based salt waste treatment for disposition, as well as a basis for comparison with other related efforts in salt waste treatment through salt partitioning initiatives. The U.S. DOE has selected a phosphate waste form reference material for further investigation and longer-term studies.

electrorefiner↗
DOE OSTI2023

Global Nuclear Explosion Discrimination Using a Convolutional Neural Network

Using P-wave seismograms, we trained a seismic source classifier using a Convolutional Neural Network. We trained for three classes: earthquake P-wave, underground nuclear explosion (UNE) P-wave, and noise. With the current absence of nuclear testing by countries that have signed the Comprehensive Test Ban Treaty, high quality seismic data from UNEs is limited. Even with limited training data, our model can accurately characterize most events recorded at regional and teleseismic distances, finding over 95% signals in the validation set. We applied the model on holdout datasets of the North Korean test explosions to evaluate the performance on unique region and station-source pairs, with promising results. Additionally, we tested on the Source Physics Experiment events to investigate the potential for chemical explosions to act as a surrogate for nuclear explosions. We anticipate that machine-learning models like our classifier system can have broad application for other seismic signals including volcanic and non-volcanic tremor, anomalous earthquakes, ice-quakes or landslide-quakes.

58 GEOSCIENCES↗
DOE OSTI2020

Nuclear spin conservation enables state-to-state control of ultracold molecular reactions

Quantum-state control of reactive systems has enabled microscopic probes of underlying interaction potentials and the alteration of reaction rates using quantum statistics. However, extending such control to the quantum states of reaction outcomes remains challenging. Here in this work, we realize this goal by utilizing the conservation of nuclear spins throughout the reaction. Using resonance-enhanced multiphoton ionization spectroscopy to investigate the products formed in bimolecular reactions between ultracold KRb molecules we find that the system retains a near-perfect memory of the reactants’ nuclear spins, manifested as a strong parity preference for the rotational states of the products. We leverage this effect to alter the occupation of these product states by changing the coherent superposition of initial nuclear spin states with an external magnetic field. In this way, we are able to control both the inputs and outputs of a reaction with quantum-state resolution. The techniques demonstrated here open up the possibilities to study quantum entanglement between reaction products, and ultracold reaction dynamics at the state-to-state level.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2023

Stochastic gradient descent for optimization for nuclear systems

The use of gradient descent methods for optimizing k-eigenvalue nuclear systems has been shown to be useful in the past, but the use of k-eigenvalue gradients have proved computationally challenging due to their stochastic nature. ADAM is a gradient descent method that accounts for gradients with a stochastic nature. This analysis uses challenge problems constructed to verify if ADAM is a suitable tool to optimize k-eigenvalue nuclear systems. ADAM is able to successfully optimize nuclear systems using the gradients of k-eigenvalue problems despite their stochastic nature and uncertainty. Furthermore, it is clearly demonstrated that low-compute time, high-variance estimates of the gradient lead to better performance in the optimization challenge problems tested here.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Emergence of competing electronic states from non-integer nuclear charges

Understanding many-electron phenomena with competing near-degenerate electronic states is of fundamental importance to chemistry and condensed matter physics. One of the most significant challenges for exploring such many-electron phenomena is the necessity for large system sizes in order to realize competing states, far beyond those practical for first-principles methods. Here, we show how allowing non-integer nuclear charges expands the space of computationally tractable electron systems that host competing electronic states. The emergence of competing electronic states from non-integer nuclear charges is exemplified in the simple 2-electron H 2 molecule and used to examine the microscopic structure of doped quasi-1D cuprate chains, showing how non-integer nuclear charges can open a window for first-principles calculations of difficult many-electron phenomena.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Approach to using 3D laser-induced breakdown spectroscopy (LIBS) data to explore the interaction of FLiNaK and FLiBe molten salts with nuclear-grade graphite

Nuclear graphite has historically been a key component of many nuclear reactor designs and has emerged as key to numerous advanced nuclear reactor design concepts. Molten salt reactors (MSRs) are one broad group of advanced reactor designs currently being pursued by industry for commercialization. Several MSR designs under consideration use graphitic materials that directly interface with a molten salt, whether it is a fuel salt, coolant salt, or both. Therefore, the interaction of graphite materials with molten salts must be understood. To gain this required understanding, a range of data is needed including porosity, strength, and composition as a function of different salt exposure parameters. In this study, a laser-induced breakdown spectroscopy (LIBS) measurement and data analysis methodology was developed to obtain spatially resolved elemental composition information for graphite samples exposed to a molten fluoride salt. Traditional univariate emission line analysis of atomic, ionic, and molecular optical emission signals was coupled via correlation analysis with spectral decomposition of the data using principal component analysis. Elemental depth profiling and elemental mapping were also performed to visualize salt–graphite interactions. LIBS was demonstrated to be useful for measuring key analytes such as fluorine and hydrogen, which are troublesome for other analysis techniques. Evidence for complex behavior was found, thereby demonstrating the usefulness of the developed approach for future systematic studies.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Modelling and analysis of nuclear reactor system coupled with a liquid metal battery

Traditionally, nuclear power plants in the U.S. provide baseload power to the power grid because they have less flexibility for ramping their output power than natural gas peaking plants. However, achieving climate goals to reduce the consumption of fossil‐based natural gas places pressure on nuclear power plants and other power generators to ramp up their power output to balance grid generation with demand. This paper presents the modelling and performance analysis of a nuclear reactor system (NRS) coupled to a liquid‐metal battery (LMB) to improve its dynamic response and enable its black start capability. The NRS and LMB thermal behaviour are modelled in Dymola, while the electrical dynamics of the LMB and power grid are modelled in RTDS‐RSCAD. Both simulation platforms are coupled and share their thermal and electrical data using a Transmission Control Protocol/Internet Protocol (TCP/IP) communication protocol. The dynamic performance of the NRS‐LMB integration is tested on the IEEE 9 bus, which demonstrates its ability to respond and provide frequency and voltage regulation. The black start capability of the NRS‐LMB is also evaluated by simulating a grid outage and using the LMB to supply the auxiliary loads required to bring the NRS back online as soon as possible. The results show that coupling an NRS to an LMB improves the system dynamic performance and enables it to black start after being disconnected from the grid for several days.

25 ENERGY STORAGE↗
DOE OSTI2022

Sensitivity Study of Type-I X-ray Bursts to Nuclear Reaction Rates

Type-I X-ray bursts are frequently occurring thermonuclear runaways on the surface of an accreting neutron star. The different nuclear reactions that empower the cataclysmic event play a key role in accurately comparing theoretical models and observations. We investigate the effect of the uncertainties in the nuclear reactions using a ONEZONE model for a set of different compositions and accretion rates that are within the range of the standard observed burst sources. A combination of a full-reaction network and a semi-analytic model is used to obtain the conditions at the time of X-ray burst ignition via simulating the settling process of the accreted material. We then evaluate the sensitivity of the X-ray burst model by varying the proton and alpha-induced reaction rates in JINA REACLIBV2.2 within representative nuclear physics uncertainties.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

Building bridges between nuclear structure and reactions

The past couple of decades have seen tremendous advances in nuclear structure and reaction theory. Innovative theory frameworks for describing the nuclear many-body system, increasingly powerful computers, and opportunities for confronting theory predictions with data on unstable nuclei, have been driving the field. An important goal is to move from phenomenological ingredients in reaction calculations to predictive theories based on microscopic frameworks. We discuss ongoing efforts aimed at integrating microscopic descriptions of nuclear structure into reaction predictions for medium-mass and heavy nuclei. This contribution highlights areas where Eric Bauge, a champion for building bridges, has made important contributions by encouraging and enabling collaborations between communities with complementary expertise.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

An introduction to Spent Nuclear Fuel decay heat for Light Water Reactors: a review from the NEA WPNCS

This paper summarized the efforts performed to understand decay heat estimation from existing spent nuclear fuel (SNF), under the auspices of the Working Party on Nuclear Criticality Safety (WPNCS) of the OECD Nuclear Energy Agency. Needs for precise estimations are related to safety, cost, and optimization of SNF handling, storage, and repository. The physical origins of decay heat (a more correct denomination would be decay power) are then introduced, to identify its main contributors (fission products and actinides) and time-dependent evolution. Due to limited absolute prediction capabilities, experimental information is crucial; measurement facilities and methods are then presented, highlighting both their relevance and our need for maintaining the unique current full-scale facility and developing new ones. The third part of this report is dedicated to the computational aspect of the decay heat estimation: calculation methods, codes, and validation. Different approaches and implementations currently exist for these three aspects, directly impacting our capabilities to predict decay heat and to inform decision-makers. Finally, recommendations from the expert community are proposed, potentially guiding future experimental and computational developments. One of the most important outcomes of this work is the consensus among participants on the need to reduce biases and uncertainties for the estimated SNF decay heat. If it is agreed that uncertainties (being one standard deviation) are on average small (less than a few percent), they still substantially impact various applications when one needs to consider up to three standard deviations, thus covering more than 95% of cases. The second main finding is the need of new decay heat measurements and validation for cases corresponding to more modern fuel characteristics: higher initial enrichment, higher average burnup, as well as shorter and longer cooling time. Similar needs exist for fuel types without public experimental data, such as MOX, VVER, or CANDU fuels. A third outcome is related to SNF assemblies for which no direct validation can be performed, representing the vast majority of cases (due to the large number of SNF assemblies currently stored, or too short or too long cooling periods of interest). A few solutions are possible, depending on the application. For the final repository, systematic measurements of quantities related to decay heat can be performed, such as neutron or gamma emission. This would provide indications of the SNF decay heat at the time of encapsulation. For other applications (short- or long-term cooling), the community would benefit from applying consistent and accepted recommendations on calculation methods, for both decay heat and uncertainties. This would improve the understanding of the results and make comparisons easier.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Hybrid quantum-classical simulations of magic angle spinning dynamic nuclear polarization in very large spin systems

Solid-state nuclear magnetic resonance can be enhanced using unpaired electron spins with a method known as dynamic nuclear polarization (DNP). Fundamentally, DNP involves ensembles of thousands of spins, a scale that is difficult to match computationally. This scale prevents us from gaining a complete understanding of the spin dynamics and applying simulations to design sample formulations. We recently developed an ab initio model capable of calculating DNP enhancements in systems of up to ~1000 nuclei; however, this scale is insufficient to accurately simulate the dependence of DNP enhancements on radical concentration or magic angle spinning (MAS) frequency. We build on this work by using ab initio simulations to train a hybrid model that makes use of a rate matrix to treat nuclear spin diffusion. We show that this model can reproduce the MAS rate and concentration dependence of DNP enhancements and build-up time constants. Finally, we then apply it to predict the DNP enhancements in core–shell metal-organic-framework nanoparticles and reveal new insights into the composition of the particles’ shells.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

BISON: A Flexible Code for Advanced Simulation of the Performance of Multiple Nuclear Fuel Forms

BISON is a nuclear fuel performance application built using the Multiphysics Object-Oriented Simulation Environment (MOOSE) finite element library. One of its major goals is to have a great amount of flexibility in how it is used, including in the types of fuel it can analyze, the geometry of the fuel being modeled, the modeling approach employed, and the dimensionality and size of the models. Fuel forms that can be modeled include standard light water reactor fuel, emerging light water reactor fuels, tri-structural isotropic fuel particles, and metallic fuels. BISON is a platform for research in nuclear fuel performance modeling while simultaneously serving as a tool for the analysis of nuclear fuel designs. Recent research in BISON includes techniques such as the extended finite element method for fuel cracking, exploration of high-burnup light water reactor fuel behavior, swelling behavior of metallic fuels, and central void formation in mixed-oxide fuel. BISON includes integrated documentation for each of its capabilities, follows rigorous software quality assurance procedures, and has a growing set of rigorous verification and validation tests.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Nuclear Data Impact Assessment for the HTR-10 Pebble-Bed Reactor Using SCALE

The HTR-10 was used as a representative pebble-bed high-temperature gas-cooled reactor in this assessment of nuclear data’s impact on important reactor and spent fuel metrics, including safety-related quantities such as the effective multiplication factor (k eff ), temperature reactivity feedback, spent fuel inventory, and decay heat. Using the SCALE code system tools and ENDF/B-VII.1 nuclear data libraries, we quantify the effect of nuclear data uncertainties on these key performance metrics for both fresh fuel and equilibrium core configurations. For reactor core key parameters, important contributors to uncertainty include reactions of 235 U [$\bar{v}$, fission, (n, γ)], 238 U [elastic, (n, γ)], and graphite [elastic, (n, γ)]. Additional important contributors for the equilibrium core include reactions of higher actinides ( 239 Pu, 240 Pu) and fission products ( 135 Xe, 149 Sm). For spent fuel analysis, most nuclide inventory uncertainties remain below 5%. Higher uncertainties up to 11% are being observed for minor actinides like 243 Am and 244 Cm. Additionally, fission product uncertainties in 155 Eu and 155 Gd, of 25% and 23% respectively, are also significant and have implications for burnup credit applications. 110m Ag also shows high uncertainty of up to 11%, mainly due to fission product yield uncertainties. Decay heat relative uncertainties remain below 0.6% up to 10 years’ cooling time after fuel discharge. The highest relative uncertainty of 1.5% occurs at 500 years of cooling; however, because the decay heat value is very low at that time, the absolute uncertainty is not significant. This work demonstrates that extending assessments beyond fresh fuel k eff to include irradiated cores, nuclide inventories, and decay heat is essential in understanding the behavior of uncertainties as a function of fuel burnup and can support improvements of safety margins and spent fuel management.

Nuclear data impact↗
DOE OSTI2022

The Strategic Implications of the Evolving US-China Nuclear Balance

China is significantly expanding the size and sophistication of its nuclear forces. Over the summer of 2021, researchers using satellite imagery discovered three separate fields of intercontinental ballistic missile (ICBM) silos under construction in the deserts of north-central China. If each silo is eventually equipped with a missile, the Chinese nuclear arsenal capable of striking the continental US could triple in size. Furthermore, the US government estimates that China’s nuclear arsenal could number 1000 warheads by 2030, with at least 200 deployed on long-range platforms.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗