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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Ground state energy and magnetization curve of a frustrated magnetic system from real-time evolution on a digital quantum processor

Models of interacting many-body quantum systems that may realize new exotic phases of matter, notably quantum spin liquids, are challenging to study using even state-of-the-art classical methods such as tensor network simulations. Quantum computing provides a promising route for overcoming these difficulties to find ground states, dynamics, and more. In this paper, we argue that recently developed hybrid quantum-classical algorithms based on real-time evolution are promising methods for solving a particularly important model in the search for spin liquids, the antiferromagnetic Heisenberg model on the two-dimensional kagome lattice. We show how to construct efficient quantum circuits to implement time evolution for the model and to evaluate key observables on the quantum computer, and we argue that the method has favorable scaling with increasing system size. We then restrict to a 12-spin star plaquette from the kagome lattice and a related 8-spin system, and we give an empirical demonstration on these small systems that the hybrid algorithms can efficiently find the ground state energy and the magnetization curve. For these demonstrations, we use four levels of approximation: exact state vectors, exact state vectors with statistical noise from sampling, noisy classical emulators, and (for the 8-spin system only) real quantum hardware, specifically the Quantinuum H1-1 processor; for the noisy simulations and hardware demonstration, we also employ error mitigation strategies based on the symmetries of the Hamiltonian. Our results strongly suggest that these hybrid algorithms present a promising direction for studying quantum spin liquids and more generally for resolving important unsolved problems in condensed matter theory and beyond.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Towards Ab-Initio Simulations of Crystalline Defects at the Exascale Using Spectral Quadrature Density Functional Theory

Defects in crystalline solids play a crucial role in determining properties of materials at the nano, meso- and macroscales, such as the coalescence of vacancies at the nanoscale to form voids and prismatic dislocation loops or diffusion and segregation of solutes to nucleate precipitates, phase transitions in magnetic materials via disorder and doping. First principles Density Functional Theory (DFT) simulations can provide a detailed understanding of these phenomena. However, the number of atoms needed to correctly simulate these systems is often beyond the reach of many widely used DFT codes. The aim of this article is to discuss recent advances in first principles modeling of crystal defects using the spectral quadrature method. The spectral quadrature method is linear scaling with respect to the number of atoms, permits spatial coarse-graining, and is capable of simulating non-periodic systems embedded in a bulk environment, which allows the application of appropriate boundary conditions for simulations of crystalline defects. In this article, we discuss the state-of-the-art in ab-initio modeling of large metallic systems of the order of several thousand atoms that are suitable for utilizing exascale computing resourses.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Corroborative Evaluation of the Real-World Energy Saving Potentials of InfoRich Eco-Autonomous Driving (iREAD) System

There has been an increasing interest in exploring the potential to reduce energy consumption of future connected and automated vehicles. People have extensively studied various eco-driving implementations that leverage preview information provided by on-board sensors and connectivity, as well as the control authority enabled by automation. Quantitative real-world evaluation of eco-driving benefits is a challenging task. The standard regulatory driving cycles used for measuring exhaust emissions and fuel economy are not truly representative of real-world driving, nor for capturing how connectivity and automation might influence driving trajectories. To adequately consider real-world driving behavior and potential “off-cycle” impacts, this paper presents four collaborative evaluation methods: large-scale simulation, in-depth simulation, vehicle-in-the-loop testing, and vehicle road testing. These four approaches, spanning simulation and testing aspects, evaluate real-world fuel economy benefits with different ranges and resolutions. The large-scale simulations leverage an extensive real-world driving database to assess overall eco-driving benefits across a range of road network and driving scenarios. The real-world driving data are further leveraged to generate representative driving routes for deeper evaluation. Based on the representative routes, in-depth simulation relying on high-fidelity models investigates how different traffic scenarios can impact the eco-driving performance. The vehicle-in-the-loop setup reinforces the in-depth simulations by conducting tests with an actual vehicle operated on a chassis dynamometer; the measured energy savings were indeed found to agree with the in-depth simulation savings estimates. Finally, limited but representative road testing with the fully integrated vehicle will be conducted to demonstrate the eco-driving capability and conclude the overall evaluation regimen.

ARPA-E↗
DOE OSTI2021

Inpainting radar missing data regions with deep learning

Abstract. Missing and low-quality data regions are a frequent problem for weather radars. They stem from a variety of sources: beam blockage, instrument failure, near-ground blind zones, and many others. Filling in missing data regions is often useful for estimating local atmospheric properties and the application of high-level data processing schemes without the need for preprocessing and error-handling steps – feature detection and tracking, for instance. Interpolation schemes are typically used for this task, though they tend to produce unrealistically spatially smoothed results that are not representative of the atmospheric turbulence and variability that are usually resolved by weather radars. Recently, generative adversarial networks (GANs) have achieved impressive results in the area of photo inpainting. Here, they are demonstrated as a tool for infilling radar missing data regions. These neural networks are capable of extending large-scale cloud and precipitation features that border missing data regions into the regions while hallucinating plausible small-scale variability. In other words, they can inpaint missing data with accurate large-scale features and plausible local small-scale features. This method is demonstrated on a scanning C-band and vertically pointing Ka-band radar that were deployed as part of the Cloud Aerosol and Complex Terrain Interactions (CACTI) field campaign. Three missing data scenarios are explored: infilling low-level blind zones and short outage periods for the Ka-band radar and infilling beam blockage areas for the C-band radar. Two deep-learning-based approaches are tested, a convolutional neural network (CNN) and a GAN that optimize pixel-level error or combined pixel-level error and adversarial loss respectively. Both deep-learning approaches significantly outperform traditional inpainting schemes under several pixel-level and perceptual quality metrics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Metal chalcogenide synthesis method and applications

A method for synthesizing a metal chalcogenide nanocrystal (NC) material includes reacting a metal material and an ammonium chalcogenide material in an organic solvent material. The method provides that the metal chalcogenide nanocrystal material may be synthesized by a heating-up method at large scale (i.e., greater than 30 grams). Ammonium chalcogenide salts exhibit high reactivity and metal chalcogenide nanocrystals can be synthesized at low temperatures (i.e., less than 200° C.) with high conversion yields (i.e., greater than 90 percent).

36 MATERIALS SCIENCE↗
DOE OSTI2021

Accelerating Multigrid-based Hierarchical Scientific Data Refactoring on GPUs

Rapid growth in scientific data and a widening gap between computational speed and I/O bandwidth make it increasingly infeasible to store and share all data produced by scientific simulations. Instead, we need methods for reducing data volumes: ideally, methods that can scale data volumes adaptively so as to enable negotiation of performance and fidelity tradeoffs in different situations. Multigrid-based hierarchical data representations hold promise as a solution to this problem, allowing for flexible conversion between different fidelities so that, for example, data can be created at high fidelity and then transferred or stored at lower fidelity via logically simple and mathematically sound operations. However, the effective use of such representations has been hindered until now by the relatively high costs of creating, accessing, reducing, and otherwise operating on such representations. We describe here highly optimized data refactoring kernels for GPU accelerators that enable efficient creation and manipulation of data in multigrid-based hierarchical forms. We demonstrate that our optimized design can achieve up to 250 TB/s aggregated data refactoring throughput—83% of theoretical peak—on 1024 nodes of the Summit supercomputer. We showcase our optimized design by applying it to a large-scale scientific visualization workflow and the MGARD lossy compression software.

Chen, Jieyang↗
DOE OSTI2025

AFC FAST Status Report Fiscal Year 2025

The Fission Accelerated Steady-state Test (FAST) methodology has been used to test several innovative metallic fuel designs for use in Sodium?cooled Fast Reactors (SFRs). The FAST method utilizes geometrically scaled fuel pins to produce improved burnup rates for fuels while maintaining semi-prototypic thermal conditions. This report provides a summary description of the test matrix and test objectives for the AFC FAST irradiation campaign as well as details of the as-built conditions for all rodlets. This report also include status update on the irradiation conditions for the rodlets as well as post-irradiation examination (PIE) results on low to mid?range burnup fuel rodlets and a summary power history for those rodlets. A brief discussion provides some early interpretation of the results and whether or not FAST is producing results typical of metallic fuels. Lastly, an outlook for the work expected to be completed in fiscal year (FY) 2026 is also included.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Saccharide analysis of onion outer epidermal walls

Abstract Background Epidermal cell walls have special structural and biological roles in the life of the plant. Typically they are multi-ply structures encrusted with waxes and cutin which protect the plant from dehydration and pathogen attack. These characteristics may also reduce chemical and enzymatic deconstruction of the wall for sugar analysis and conversion to biofuels. We have assessed the saccharide composition of the outer epidermal wall of onion scales with different analytical methods. This wall is a particularly useful model for cell wall imaging and mechanics. Results Epidermal walls were depolymerized by acidic methanolysis combined with 2M trifluoracetic acid hydrolysis and the resultant sugars were analyzed by high-performance anion-exchange chromatography with pulsed amperometric detection (HPAEC-PAD). Total sugar yields based on wall dry weight were low (53%). Removal of waxes with chloroform increased the sugar yields to 73% and enzymatic digestion did not improve these yields. Analysis by gas chromatography/mass spectrometry (GC/MS) of per- O -trimethylsilyl (TMS) derivatives of the sugar methyl glycosides produced by acidic methanolysis gave a high yield for galacturonic acid (GalA) but glucose (Glc) was severely reduced. In a complementary fashion, GC/MS analysis of methyl alditols produced by permethylation gave substantial yields for glucose and other neutral sugars, but GalA was severely reduced. Analysis of the walls by 13 C solid-state NMR confirmed and extended these results and revealed 15% lipid content after chloroform extraction (potentially cutin and unextractable waxes). Conclusions Although exact values vary with the analytical method, our best estimate is that polysaccharide in the outer epidermal wall of onion scales is comprised of homogalacturonan (~ 50%), cellulose (~ 20%), galactan (~ 10%), xyloglucan (~ 10%) and smaller amounts of other polysaccharides. Low yields of specific monosaccharides by some methods may be exaggerated in epidermal walls impregnated with waxes and cutin and call for cautious interpretation of the results.

09 BIOMASS FUELS↗
DOE OSTI2022

Study of Self-Interaction Errors in Density Functional Calculations of Magnetic Exchange Coupling Constants Using Three Self-Interaction Correction Methods

We examine the role of self-interaction errors (SIE) removal on the evaluation of magnetic exchange coupling constants. In particular we analyze the effect of scaling down the self-interaction-correction (SIC) for three non-empirical density functional approximations (DFAs) namely, the local spin density approximation, the Perdew-Burke-Ernzerhof generalized gradient approximation, and recent SCAN family of meta-GGA functionals. To this end, we employ three one-electron SIC methods: Perdew-Zunger [Perdew, J. P.; Zunger, A. Phys. Rev. B, 1981, 23, 5048] SIC, the orbitalwise scaled SIC method [Vydrov, O. A. et al., J. Chem. Phys. 2006, 124, 094108], and the recent local scaling method [Zope, R. R. et al., J. Chem. Phys. 2019, 151, 214108]. We compute the magnetic exchange coupling constants using the spin projection and non projection approaches for sets of molecules composed of dinuclear and polynuclear H-He models, organic radical molecules, and chlorocuprate, and compare these results against accurate theories and experiment. Our results show that for the systems that mainly consist of single electron regions, PZSIC performs well but for more complex organic systems and the chlorcuprates, an overcorrecting tendency of PZSIC combined with the DFAs utilized in this work is more pronounced, and in such cases LSIC with kinetic energy density ratio performs better than PZSIC. Furthermore, analysis of the results in terms of SIC corrections to the density and to the total energy shows that both density and energy correction are required to obtain an improved prediction of magnetic exchange couplings.

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

Simulations of biomass pyrolysis using glued-sphere CFD-DEM with 3-D intra-particle models

The shape of biomass particles influences intra-particle heat transfer, particle-particle collisions, interphase momentum, heat transfer, and pyrolysis yield. In this research, the effects of these multi-scale phenomena are captured using a glued-sphere computational fluid dynamic discrete element method (CFD-DEM) with 3-D intra-particle models. The glued-spheres resolved the shapes of particles and intra-particle temperature and species distributions. The implementation was validated using the pyrolysis data of a spherical particle and a cylindrical particle. Then, the influences of biomass shapes and sizes on pyrolysis were investigated. The results revealed the significant influence of surface areas and mass distributions on interphase heat transfer and chemical reactions. The intra-particle heat transfer is neglectable for a Biot number smaller than 0.41. Finally, the pyrolysis of irregularly shaped biomass particles in a fixed bed, fluidized bed, and spouted bed was simulated. Analysis of conversion distributions showed the largest deviations in the fixed bed and the slowest conversion rate in the spouted bed. A good balance between uniform and fast conversion is achieved in the fluidized bed. The multi-scale method proposed in this research provides a tool for the evaluation of large irregular-shaped biomass particle pyrolysis in different types of reactors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

FX Hg Fogging Fixative Deployment for Mercury Vapor Suppression

Idaho National Laboratory’s (INL) FX Hg fixative solution was deployed at the Y-12 Complex in Oak Ridge, Tennessee to support disposal of mercury-contaminated metal debris. The fixative was dispensed via fogging. Fogging infiltrates non-line-of-sight areas improving fixative coating on complex geometries such as debris piles. FX Hg is the mercury vapor controlling derivative of INL’s FX2 fixative. FX2 was jointly developed with the National Nuclear Laboratory of the United Kingdom, and INL developed the FX Hg derivative to suppress mercury vapor generation. The Y-12 deployment was performed in concert with cleanup contractor UCOR. A dumpster filled with debris was fogged with FX Hg. The material was acceptable as municipal landfill waste, save for the mercury vapor levels measured. If the mercury vapor generation rate could be sufficiently reduced, disposal costs for this waste would be dramatically reduced. FX Hg had previously proven effective at significantly reducing mercury vapor generation rates in bench scale testing at INL. This deployment was the first field scale deployment of the method. Efficacy results were underwhelming, but interpretation of the outcome is complicated by a paucity of hard data. Methods for improving data capture and analysis are analyzed. Operational difficulties associated with scaling the process up and process improvements for future deployments are discussed.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

FX Hg Fogging Fixative Deployment for Mercury Vapor Suppression - 20410

Idaho National Laboratory's (INL) FX Hg fixative solution was deployed at the Y-12 National Security Complex in Oak Ridge, Tennessee to support disposal of mercury-contaminated metal debris. The fixative was dispensed via fogging. Fogging infiltrates non-line-of-sight areas improving fixative coating on complex geometries such as debris piles. FX Hg is the mercury vapor controlling derivative of INL's FX2 fixative. FX2 was jointly developed with the National Nuclear Laboratory of the United Kingdom, and INL developed the FX Hg derivative to suppress mercury vapor generation. The Y-12 deployment was performed in concert with UCOR (URS CH2M Oak Ridge), the cleanup contractor for Y-12. A dumpster filled with debris was fogged with FX Hg. The debris was acceptable as municipal landfill waste, save for the mercury vapor levels measured. If the mercury vapor generation rate could be sufficiently reduced, disposal costs for this waste would be dramatically reduced. FX Hg had previously proven effective at significantly reducing mercury vapor generation rates in bench scale testing at INL. This deployment was the first field-scale deployment of the method. Efficacy results were underwhelming, but interpretation of the outcome is complicated by a paucity of hard data. Methods for improving data capture and analysis are analyzed. Operational difficulties associated with scaling up the process and process improvements for future deployments are discussed. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Scaling dynamics in low-salt-rejection reverse osmosis for high-salinity produced water desalination: Mechanistic modeling and membrane autopsy

Membrane scaling remains a critical barrier to the reliable operation of desalination systems, particularly for hypersaline produced water (PW) treatment. This study fills the knowledge gap of autopsy-based model validation for PW desalination by elucidating scaling mechanisms in a Low-Salt-Rejection Reverse Osmosis (LSRRO) system through the integration of pilot-scale experimentation and complementary modeling approaches. A semi-empirical modeling framework was developed and applied to a multistage pilot LSRRO system equipped with nanofiltration and RO membranes treating high-salinity PW from the Permian Basin. Water quality analysis showed that total dissolved solids decreased from ~130,000 mg/L to ~1900 mg/L in the permeate, then further reduced to ~300 mg/L by a second-pass RO. Two different thermodynamic modeling approaches were evaluated: the first extends the LSRRO framework by incorporating system complexity and scaling phenomena, whereas the second method explicitly captures concentration polarization in localized supersaturation. Both methods illustrate the tendency for carbonate and sulfate scaling throughout the stages. Membrane autopsies revealed a silica-dominated deposit matrix, localized CaSO 4 at Stage 2, and minor barite/celestite despite their prominence in model predictions. Quantum-chemical calculations indicated silica scaling can be rationalized by favorable adsorption of H 4 SiO 4 on Fe-oxide surfaces (ΔG ≈ −44 kJ/mol), providing a kinetic pathway for interfacial inorganic polymerization even when bulk equilibrium predictions are conservative. Overall, the thermodynamic scaling modeling and membrane autopsy revealed heterogeneous, localized deposits with limited impact on LSRRO performance, while quantum analysis rationalized the thermodynamically unfavorable precipitation formation under bulk equilibrium, reconciling model–autopsy discrepancies. These insights support targeted pretreatment and silica-specific antiscalants to extend membrane lifetime and increase recovery, providing a transferable framework for hypersaline water desalination systems. The combined experimental–computational approach provides new mechanistic insight into scaling in hypersaline membrane systems and establishes a transferable framework for predicting and mitigating scaling in next-generation desalination technologies.

Low-salt-rejection reverse osmosis↗
DOE OSTI2020

Assessing Anomaly-Based Intrusion Detection Configurations for Industrial Control Systems

To reduce cost and ease maintenance, industrial control systems (ICS) have adopted Ethernetbased interconnections that integrate operational technology (OT) systems with information technology (IT) networks. This integration has made these critical systems vulnerable to attack. Security solutions tailored to ICS environments are an active area of research. Anomalybased network intrusion detection systems are well-suited for these environments. Often these systems must be optimized for their specific environment. In prior work, we introduced a method for assessing the impact of various anomaly-based network IDS settings on security. This paper reviews the experimental outcomes when we applied our method to a full-scale ICS test bed using actual attacks. Our method provides new and valuable data to operators enabling more informed decisions about IDS configurations.

Gillen, Rob↗
DOE OSTI2020

Application of Quantum Computing to Biochemical Systems: A Look to the Future

Chemistry is considered as one of the more promising applications to science of near-term quantum computing. Recent work in transitioning classical algorithms to a quantum computer has led to great strides in improving quantum algorithms and illustrating their quantum advantage. Because of the limitations of near-term quantum computers, the most effective strategies split the work over classical and quantum computers. There is a proven set of methods in computational chemistry and materials physics that has used this same idea of splitting a complex physical system into parts that are treated at different levels of theory to obtain solutions for the complete physical system for which a brute force solution with a single method is not feasible. These methods are variously known as embedding, multi-scale, and fragment techniques and methods. We review these methods and then propose the embedding approach as a method for describing complex biochemical systems, with the parts not only treated with different levels of theory, but computed with hybrid classical and quantum algorithms. Such strategies are critical if one wants to expand the focus to biochemical molecules that contain active regions that cannot be properly explained with traditional algorithms on classical computers. While we do not solve this problem here, we provide an overview of where the field is going to enable such problems to be tackled in the future.

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

Impact of Increased Latent Generations on Sensitivity Calculations with SCALE

Analyses of cross section sensitivity data from systems with fissile material allow analysts to associate an importance for each material, nuclide, reaction, and neutron energy by simulating real world criticality scenarios. Although criticality safety validation efforts can be guided by the cross-section sensitivity and uncertainty data generated for a particular system, these calculations can often be computationally expensive and sometimes cumbersome without proper guidance. The TSUNAMI suite within the SCALE code package has several methods for generating sensitivity data, including multigroup and continuous energy (CE) capabilities. The release of SCALE 6.3 has three different CE methods for generating cross section sensitivity data: (1) the Iterated Fission Probability (IFP) method with the KENO Monte Carlo transport solver, (2) the IFP method with the Shift Monte Carlo transport solver, and (3) the Contributon-Linked eigenvalue sensitivity/Uncertainty estimation via Tracklength importance CHaracterization (CLUTCH) method with the KENO Monte Carlo transport solver. Although the CLUTCH method has additional parameters for generating sensitivity data files relative to the IFP method, all three methods use latent generations, which are the generations between an event (i.e., fission) and the assessment of importance based on the asymptotic population of progeny neutrons. Increasing the number of latent generations in a calculation leads to increased discrimination of the sensitivity coefficients but at the cost of the increased uncertainty associated with those generated values. Analysts must balance the accuracy of the sensitivity calculations and its uncertainty with the associated computational cost involved in generating the values. This paper discusses the impact of adjusting the latent generation parameter for a range of sensitivity values and how these changes compare with the direct perturbation values obtained from a change of ±0.5% Δ k in both benchmark and safety application models. Two benchmarks from the International Handbook of Evaluated Criticality Safety Benchmark Experiments and the MPC-32 dual purpose canister for spent nuclear fuel are used for analysis.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Reliable voltage scaled links for compressed data

Systems, apparatuses, and methods for reliably transmitting data over voltage scaled links are disclosed. A computing system includes at least first and second devices connected via a link. In one implementation, if a data block can be compressed to less than or equal to half the original size of the data block, then the data block is compressed and sent on the link in a single clock cycle rather than two clock cycles. If the data block cannot be compressed to half the original size, but if the data block can be compressed enough to include error correction code (ECC) bits without exceeding the original size, then ECC bits are added to the compressed block which is sent on the link at a reduced voltage. The ECC bits help to correct for any errors that are generated as a result of operating the link at the reduced voltage.

42 ENGINEERING↗
DOE OSTI2020

Reducing communication in algebraic multigrid with multi-step node aware communication

Algebraic multigrid (AMG) is often viewed as a scalable [Formula: see text] solver for sparse linear systems. Yet, AMG lacks parallel scalability due to increasingly large costs associated with communication, both in the initial construction of a multigrid hierarchy and in the iterative solve phase. This work introduces a parallel implementation of AMG that reduces the cost of communication, yielding improved parallel scalability. It is common in Message Passing Interface (MPI), particularly in the MPI-everywhere approach, to arrange inter-process communication, so that communication is transported regardless of the location of the send and receive processes. Performance tests show notable differences in the cost of intra- and internode communication, motivating a restructuring of communication. In this case, the communication schedule takes advantage of the less costly intra-node communication, reducing both the number and the size of internode messages. Node-centric communication extends to the range of components in both the setup and solve phase of AMG, yielding an increase in the weak and strong scaling of the entire method.

Computer Science↗