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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 919 records · Page 51
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Prediction and compression of lattice QCD data using machine learning algorithms on quantum annealer

We present regression and compression algorithms for lattice QCD data utilizing the efficient binary optimization ability of quantum annealers. In the regression algorithm, we encode the correlation between the input and output variables into a sparse coding machine learning algorithm. The trained correlation pattern is used to predict lattice QCD observables of unseen lattice configurations from other observables measured on the lattice. In the compression algorithm, we define a mapping from lattice QCD data of floating-point numbers to the binary coefficients that closely reconstruct the input data from a set of basis vectors. Since the reconstruction is not exact, the mapping defines a lossy compression, but, a reasonably small number of binary coefficients are able to reconstruct the input vector of lattice QCD data with the reconstruction error much smaller than the statistical fluctuation. In both applications, we use D-Wave quantum annealers to solve the NP-hard binary optimization problems of the machine learning algorithms.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Microscopy X-ray imaging enriched with small angle X-ray scattering for few nanometer resolution reveals shock waves and compression in intense short pulse laser irradiation of solids

Understanding how laser pulses compress solids into high-energy-density states requires diagnostics that simultaneously resolve macroscopic geometry and nanometer-scale structure. Here we present a combined X-ray imaging (XRM) and small-angle X-ray scattering (SAXS) approach that bridges this diagnostic gap. Using the Matter in Extreme Conditions end station at LCLS, we irradiated 25 μm copper wires with 45 fs, 0.9 J, 800 nm pulses at 3.5 × 10 19 W/cm 2 while probing with 8.2 keV XFEL pulses. XRM visualizes the evolution of ablation, compression, and inward-propagating fronts with ∼ 200 nm resolution, while SAXS quantifies their nanometer-scale sharpness via the time-resolved evolution of scattering streaks. The joint analysis reveals that an initially smooth compression steepens into a nanometer-sharp shock front after t sh ≈ (18 ± 3) ps, consistent with an analytical steepening model and hydrodynamic simulations. The front reaches a velocity of c sh ≈ 25 k m / s and a lateral width of several tens of microns, demonstrating direct observation of shock formation and decay at solid density for the first time with few-nanometer precision. This integrated XRM–SAXS method establishes a quantitative, multi-scale diagnostic of laser-driven shocks in dense plasmas relevant to inertial confinement fusion, warm dense matter, and planetary physics.

Kluge, Thomas [Helmholtz-Zentrum Dresden-Rossendor↗
DOE OSTI2020

Increasing Compressed Gas Energy Storage Density Using CO2–N2 Gas Mixture

This paper demonstrates a new method by which the energy storage density of compressed air systems is increased by 56.8% by changing the composition of the compressed gas to include a condensable component. A higher storage density of 7.33 MJ/m3 is possible using a mixture of 88% CO2 and 12% N2 compared to 4.67 MJ/m3 using pure N2. This ratio of gases representing an optimum mixture was determined through computer simulations that considered a variety of different proportions from pure CO2 to pure N2. The computer simulations are based on a thermodynamic equilibrium model that predicts the mixture composition as a function of volume and pressure under progressive compression to ultimately identify the optimal mixture composition (88% CO2 + 12% N2). The model and simulations predict that the optimal gas mixture attains a higher energy storage density than using either of the pure gases.

25 ENERGY STORAGE↗
DOE OSTI2025

A Finite Element Method for Compressible and Turbulent Multiphase Flow Instabilities with Heat Transfer

We present a new finite element framework for modeling compressible, turbulent multiphase flows with heat transfer. For two-fluid systems with a free surface, the Volume of Fluid (VOF) method is implemented without the need for interface reconstruction, while turbulence is resolved using a dynamic Vreman large eddy simulation (LES) model. Unlike most two-phase VOF studies, which neglect heat transfer, the present approach incorporates energy transport equations within the VOF formulation to account for heat exchange, an effect particularly important in turbulent flows. Conjugate heat transfer is often challenging in finite volume methods, which require explicit specification of heat fluxes at the solid–fluid interface, limiting accuracy and predictive capability. By contrast, the finite element formulation does not require heat flux inputs, allowing more accurate and robust simulation of heat transfer between solids and fluids. The method is demonstrated through three representative cases. First, a two-fluid instability with a single-mode perturbation is simulated and validated against analytical growth rates. Second, conjugate heat transfer is examined in a high-temperature flow over a cold metal cylinder, with validation performed both quantitatively—via pressure coefficient comparisons with experimental data—and qualitatively using vector field topology. Finally, compressible spray injection and breakup are modeled, demonstrating the ability of the framework to capture interfacial dynamics and atomization under turbulent, high-speed conditions. In the compressible spray injection and breakup case, the results indicate that the finite element formulation achieved higher predictive accuracy and robustness than the finite-volume method. With the same mesh resolution, the FEM reduced the root mean square error (RMSE) and mean absolute percentage error (MAPE) from 6.96 mm and 26.0% (for the FVM) to 4.85 mm and 12.7%, respectively, demonstrating improved accuracy and robustness in capturing interfacial dynamics and heat transfer. The study also introduced vector field topology to visualize and interpret coherent flow structures and instabilities, offering insights beyond conventional scalar-field analyses.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Pressure Induced Densification and Compression in a Reprocessed Borosilicate Glass

Pressure induced densification and compression of a reprocessed sample of borosilicate glass has been studied by X-ray radiography and energy dispersive X-ray diffraction using a Paris-Edinburgh (PE) press at a synchrotron X-ray source. The reprocessing of a commercial borosilicate glass was carried out by cyclical melting and cooling. Gold foil pressure markers were used to obtain the sample pressure by X-ray diffraction using its known equation of state, while X-ray radiography provided a direct measure of the sample volume at high pressure. The X-ray radiography method for volume measurements at high pressures was validated for a known sample of pure α-Iron to 6.3 GPa. A sample of reprocessed borosilicate glass was compressed to 11.4 GPa using the PE cell, and the flotation density of pressure recovered sample was measured to be 2.755 gm/cc, showing an increase in density of 24%, as compared to the starting sample. The initial compression of the reprocessed borosilicate glass measured by X-ray radiography resulted in a bulk modulus of 30.3 GPa in good agreement with the 32.9 GPa value derived from the known elastic constants. This method can be applied to variety of amorphous materials under high pressures.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Large-scale Compression Acceleration during Magnetic Reconnection in a Low- β Plasma

In solar flares and other astrophysical systems, a major challenge for solving the particle acceleration problem associated with magnetic reconnection is the enormous scale separation between kinetic scales and the observed reconnection scale. Because of this, it has been difficult to draw any definite conclusions by just using kinetic simulations. A particle acceleration model that solves the energetic particle transport equation can capture the main acceleration physics found in kinetic simulations and thus provide a practical way to make observable predictions and directly compare model results with observations. Here we study compression particle acceleration in magnetic reconnection by solving the Parker (diffusion–advection) transport equation using velocity and magnetic fields from two-dimensional magnetohydrodynamics (MHD) simulations of a low-β high-Lundquist-number reconnection layer. We show that the compressible reconnection layer can give significant particle acceleration, leading to the formation of power-law particle energy distributions. We analyze the acceleration rate and find that the acceleration in the reconnection layer is a mixture of first- and second-order Fermi processes. When including a guide field, we find that the spectrum becomes steeper and both the power-law cutoff energy and maximum particle energy decrease as plasma becomes less compressible. This model produces a 2D particle distribution that one can use to generate a radiation map and directly compare with solar flare observations. This provides a framework to explain particle acceleration at large-scale astrophysical reconnection sites, such as solar flares.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Anisotropic Energy Transfer and Conversion in Magnetized Compressible Turbulence

We present a spatial filtering (or coarse-graining) analysis on 3D magnetized magnetohydrodynamic (MHD) turbulence simulations. The filtered compressible MHD formulae show transfer of kinetic and magnetic energies from large to small scales, as well as energy conversion between kinetic, magnetic, and thermal energies. The anisotropic filtering enables separate analyses of the energy flows perpendicular and parallel to the global mean magnetic field. Anisotropy in energy cascade is demonstrated by the larger perpendicular energy cascade rate and also the larger perpendicular wavenumbers associated with the peak energy transfer rate. We also find that the “inertial range” along the parallel (perpendicular) direction in the anisotropic energy cascade formulation is no longer strictly dissipation-free, because it includes the dissipation in the perpendicular (parallel) direction. A change in the driving force (kinetic only versus kinetic and magnetic) affects the energy conversion between kinetic and magnetic energies. While the compressibility of the driving force changes the partition of different channels of energy transfer and conversion, and also increases the total energy transfer rate, the global energy flow remains unaffected by compressibility qualitatively. Our analysis can be applied to multispacecraft observations of turbulence in the solar wind or a planetary magnetosphere.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Temporal Properties of Compressible Magnetohydrodynamic Turbulence

Describing the temporal properties of compressible magnetohydrodynamic (MHD) turbulence is a fundamental problem that has important implications for particle acceleration and transport in astrophysical plasmas. Here, by carefully analyzing the spatial and temporal properties of compressible MHD turbulence, we derive a new spectral power density function that is supported by simulations. This new function reveals that the low-frequency fluctuations are dominated by modes with small parallel wavenumbers with respect to the mean background magnetic field. Furthermore, for fluctuations with dynamically significant parallel wavenumbers, broadening around their eigenfrequencies is described by this function, which is in close agreement with simulations. We use this formalism to present the scaling properties of individual MHD modes. Such broadening is a direct consequence of nonlinear processes and is different for the three fundamental MHD modes. Our results provide a new window to investigate the temporal properties of turbulence and will enable further studies on the interaction between compressible MHD turbulence and energetic plasmas.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

COMPRESSIBLE RELATIVISTIC MAGNETOHYDRODYNAMIC TURBULENCE IN MAGNETICALLY DOMINATED PLASMAS AND IMPLICATIONS FOR A STRONG-COUPLING REGIME

In this Letter, we report compressible mode effects on relativistic magnetohydrodynamic (RMHD) turbulence in Poynting-dominated plasmas using three-dimensional numerical simulations. We decomposed fluctuations in the turbulence into 3 MHD modes (fast, slow, and Alfvén) following the procedure of mode decomposition in Cho and Lazarian, and analyzed their energy spectra and structure functions separately. We also analyzed the ratio of compressible mode to Alfvén mode energy with respect to its Mach number. We found the ratio of compressible mode increases not only with the Alfvén Mach number, but also with the background magnetization, which indicates a strong coupling between the fast and Alfvén modes. It also signifies the appearance of a new regime of RMHD turbulence in Poynting-dominated plasmas where the fast and Alfvén modes are strongly coupled and, unlike the non-relativistic MHD regime, cannot be treated separately. This finding will affect particle acceleration efficiency obtained by assuming Alfvénic critical-balance turbulence and can change the resulting photon spectra emitted by non-thermal electrons.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

A dictionary learning algorithm for compression and reconstruction of streaming data in preset order

There has been an emerging interest in developing and applying dictionary learning (DL) to process massive datasets in the last decade. Many of these efforts, however, focus on employing DL to compress and extract a set of important features from data, while considering restoring the original data from this set a secondary goal. On the other hand, although several methods are able to process streaming data by updating the dictionary incrementally as new snapshots pass by, most of those algorithms are designed for the setting where the snapshots are randomly drawn from a probability distribution. In this paper, we present a new DL approach to compress and denoise massive dataset in real time, in which the data are streamed through in a preset order (instances are videos and temporal experimental data), so at any time, we can only observe a biased sample set of the whole data. Here, our approach incrementally builds up the dictionary in a relatively simple manner: if the new snapshot is adequately explained by the current dictionary, we perform a sparse coding to find its sparse representation; otherwise, we add the new snapshot to the dictionary, with a Gram-Schmidt process to maintain the orthogonality. To compress and denoise noisy datasets, we apply the denoising to the snapshot directly before sparse coding, which deviates from traditional dictionary learning approach that achieves denoising via sparse coding. Compared to full-batch matrix decomposition methods, where the whole data is kept in memory, and other mini-batch approaches, where unbiased sampling is often assumed, our approach has minimal requirement in data sampling and storage: i) each snapshot is only seen once then discarded, and ii) the snapshots are drawn in a preset order, so can be highly biased. Through experiments on climate simulations and scanning transmission electron microscopy (STEM) data, we demonstrate that the proposed approach performs competitively to those methods in data reconstruction and denoising.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Numerical Investigation of a Gasoline-Like Fuel in a Heavy-Duty Compression Ignition Engine Using Global Sensitivity Analysis

Fuels in the gasoline auto-ignition range (Research Octane Number (RON) > 60) have been demonstrated to be effective alternatives to diesel fuel in compression ignition engines. Such fuels allow more time for mixing with oxygen before combustion starts, owing to longer ignition delay. Moreover, by controlling fuel injection timing, it can be ensured that the in-cylinder mixture is “premixed enough” before combustion occurs to prevent soot formation while remaining “sufficiently inhomogeneous” in order to avoid excessive heat release rates. Gasoline compression ignition (GCI) has the potential to offer diesel-like efficiency at a lower cost and can be achieved with fuels such as low-octane straight run gasoline which require significantly less processing in the refinery compared to today’s fuels. To aid the design and optimization of a compression ignition (CI) combustion system using such fuels, a global sensitivity analysis (GSA) was conducted to understand the relative influence of various design parameters on efficiency, emissions and heat release rate. The design parameters included injection strategies, exhaust gas recirculation (EGR) fraction, temperature and pressure at intake valve closure and injector configuration. These were varied simultaneously to achieve various targets of ignition timing, combustion phasing, overall burn duration, emissions, fuel consumption, peak cylinder pressure and maximum pressure rise rate. The baseline case was a three-dimensional closed-cycle computational fluid dynamics (CFD) simulation with a sector mesh at medium load conditions. Eleven design parameters were considered and ranges of variation were prescribed to each of these. These input variables were perturbed in their respective ranges using the Monte Carlo (MC) method to generate a set of 256 CFD simulations and the targets were calculated from the simulation results. GSA was then applied as a screening tool to identify the input parameters having the most significant impact on each target. The results were further assessed by investigating the impact of individual parameter variations on the targets. Overall, it was demonstrated that GSA can be an effective tool in understanding parameters sensitive to a low temperature combustion concept with novel fuels.

Pal, Pinaki↗
DOE OSTI2017

Advancements and Opportunities for On-board 700 bar Compressed Hydrogen Tanks in the Progression towards the Commercialization of Fuel Cell Vehicles

Fuel cell vehicles are entering the automotive market with significant potential to reduce harmful greenhouse emissions, facilitate energy security, and increase efficiency while providing expected driving range and fill times. One of the challenges for successful commercialization is transitioning the on-board fuel system from liquid gasoline to compressed hydrogen gas. Storing high pressurized hydrogen requires a specialized structural pressure vessel, significantly different in function from a gasoline container. In addition, the lower hydrogen energy combined with highly efficient fuel cell still requires a storage vessel that is four times the volume of a gasoline tank. In the late 1990s, the industry first developed hydrogen tanks based on traditional type 3 and 4 compressed natural gas (CNG) tanks designed for 250 bar service. As fuel cell vehicles developed along with the need for greater driving range, the OEMs increased the hydrogen storage pressure to 350 bar and then to 700 bar, which is currently the industry norm. However, the 700 bar pressure vessels continued to be manufactured using the materials and the design approach from the CNG tank technologies. In 2012 the U.S. Department of Energy, Office of Fuel Cell Technologies initiated a project to develop Enhanced Materials and Design Parameters for Reducing the Cost of Hydrogen Storage Tanks. The project took a holistic approach to improving performance by investigating: 1) the cost tradeoff of reduced composite mass at 500 bar versus the added insulation cost for cold gas operation at 200K, 2) using hybrid fiber layups to refine the tank composite design, 3) increasing the composite translation efficiency by adding nano-reinforcing particles to the resin, and 4) substituting a lower cost alternate resin in the filament winding process. This paper summarizes the effectiveness of these design modifications and considers the outlook for on-board 700 bar compressed hydrogen tank systems to achieve the commercialization goals for fuel cell vehicles.

Hydrogen storage, carbon fiber composite, compo, a↗
DOE OSTI2021

Fuel Effects on Advanced Compression Ignition Load Limits

In order to increase the efficiency of light-duty gasoline engines, the Co-Optimization of Fuels and Engines (Co-Optima) initiative from the U.S. Department of Energy is investigating multi-mode combustion strategies. Multi-mode combustion can be describe as using conventional spark-ignited combustion at high loads, and at the part-load operating conditions, various advanced compression ignition (ACI) strategies are being investigated to increase efficiency. Of particular interest to the Co-Optima initiative is the extent to which optimal fuel properties and compositions can enable higher efficiency ACI combustion over larger portions of the operating map. Extending the speed-load range of these ACI modes can enable greater part-load efficiency improvements for multi-mode combustion strategies. In this manuscript, we investigate fuel effects for six different fuels, including four with a research octane number (RON) of 98 and differing fuel chemistries, iso-octane, and a market representative E10 fuel, on the load limits for two different ACI strategies: spark-assisted compression ignition (SACI) and partial fuel stratification-gasoline compression ignition (PFS-GCI) operation. Experimental results show that limits to intake boosting limit high load operation for most fuels, but high smoke emissions for high particulate matter index (PMI) fuels under SACI conditions could also be a limitation. Contrastingly, low load is limited by combustion efficiency, but these effects have more pronounced variation with fuel chemistry for PFS-GCI than with SACI. Additional, distinct effects affecting autoignition timing and peak heat release at higher speeds were identified for fuels having different low temperature heat release (LTHR) propensities for both ACI modes.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2019

HPCAT: A Static Compression Science Sector at the Advance Photon Source

Static compression is a useful tool to investigate the materials properties and phase behavior both under uniaxial stress and hydrostatic pressure. From evaluation of the equation of state (P-V-T relationship) to a discovery of near-room temperature superconductivity, the use of diamond anvil cells (DAC) and large-volume presses (LVP) as devices for static compression experiments that couple with synchrotron-based x-ray diffraction, spectroscopy, and imaging techniques achieved pioneering, paradigm defining scientific advancements in multidisciplinary fields for the past two decades. High-Pressure Collaborative Access Team (HPCAT) is a sector at the Advanced Photon Source dedicated to developing multiple synchrotron-based x-ray techniques to maximize the utility of DAC and portable-LVP techniques to advance compression science. The beamlines are optimized to adapt various sample environments under extreme P-T conditions. HPCAT is comprised of two insertion device beamlines, one for diffraction and the other for spectroscopy, and two bending magnet beamlines, one for general purpose and the other for white-beam application, respectively. As a result, each beamline’s specification and applications are introduced.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Power plant including an exhaust gas recirculation system for injecting recirculated exhaust gases in the fuel and compressed air of a gas turbine engine

A power plant is provided and includes a gas turbine engine having a combustor in which compressed gas and fuel are mixed and combusted, first and second supply lines respectively coupled to the combustor and respectively configured to supply the compressed gas and the fuel to the combustor and an exhaust gas recirculation (EGR) system to re-circulate exhaust gas produced by the gas turbine engine toward the combustor. The EGR system is coupled to the first and second supply lines and configured to combine first and second portions of the re-circulated exhaust gas with the compressed gas and the fuel at the first and second supply lines, respectively.

42 ENGINEERING↗
DOE OSTI2015

Compressive stress system for a gas turbine engine

The present application provides a compressive stress system for a gas turbine engine. The compressive stress system may include a first bucket attached to a rotor, a second bucket attached to the rotor, the first and the second buckets defining a shank pocket therebetween, and a compressive stress spring positioned within the shank pocket.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2015

Comparison of ring compression testing to three point bend testing for unirradiated ZIRLO cladding

Safe shipment and storage of nuclear reactor discharged fuel requires an understanding of how the fuel may perform under the various conditions that can be encountered. One specific focus of concern is performance during a shipment drop accident. Tests at Savannah River National Laboratory (SRNL) are being performed to characterize the properties of fuel clad relative to a mechanical accident condition such as a container drop. Unirradiated ZIRLO tubing samples have been charged with a range of hydride levels to simulate actual fuel rod levels. Samples of the hydrogen charged tubes were exposed to a radial hydride growth treatment (RHGT) consisting of heating to 400°C, applying initial hoop stresses of 90 to 170 MPa with controlled cooling and producing hydride precipitates. Initial samples have been tested using both a) ring compression test (RCT) which is shown to be sensitive to radial hydride and b) three-point bend tests which are less sensitive to radial hydride effects. Hydrides are generated in Zirconium based fuel cladding as a result of coolant (water) oxidation of the clad, hydrogen release, and a portion of the released (nascent) hydrogen absorbed into the clad and eventually exceeding the hydrogen solubility limit. The orientation of the hydrides relative to the subsequent normal and accident strains has a significant impact on the failure susceptability. In this study the impacts of stress, temperature and hydrogen levels are evaluated in reference to the propensity for hydride reorientation from the circumferential to the radial orientation. In addition the effects of radial hydrides on the Quasi Ductile Brittle Transition Temperature (DBTT) were measured. The results suggest that a) the severity of the radial hydride impact is related to the hydrogen level-peak temperature combination (for example at a peak drying temperature of 400°C; 800 PPM hydrogen has less of an impact/ less radial hydride fraction than 200 PPM hydrogen for the same thermal history) and b) for critical strains in post drying handling, storage and accident conditions the 3 point bend strain tolerance is less affected by radial hydrides than the conventional ring compression test (the radial hydride related Quasi DBTT associated with a three point bend straining is lower (better) than that measured by the ring compression tests).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2017

ZFP compression plugin (filter) for HDF5

H5Z-ZFP is a compression plugin (filter) for the HDF5 library based upon the ZFP-0.5.0 compression library. It supports 4- or 8-byte integer or floating point HDF5 datasets of any dimension but partitioned in 1, 2, or 3 dimensional chunks. It supports ZFP's four fundamental modes of operation; rate, precision, accuracy or expert. It is a lossy compression plugin.

Miller, Mark C.↗