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Results for “compressibility factor”

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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS1991

SAR data compression: Application, requirements, and designs

The feasibility of reducing data volume and data rate is evaluated for the Earth Observing System (EOS) Synthetic Aperture Radar (SAR). All elements of data stream from the sensor downlink data stream to electronic delivery of browse data products are explored. The factors influencing design of a data compression system are analyzed, including the signal data characteristics, the image quality requirements, and the throughput requirements. The conclusion is that little or no reduction can be achieved in the raw signal data using traditional data compression techniques (e.g., vector quantization, adaptive discrete cosine transform) due to the induced phase errors in the output image. However, after image formation, a number of techniques are effective for data compression.

Curlander, John C.↗
DOE OSTI2023

Compressive strength improvements from noncircular carbon fibers: A numerical study

The benefits of high-performance unidirectional carbon fiber composites are limited in many cost-driven industries due to the high cost relative to alternative reinforcement fibers. Low-cost carbon fibers have been previously proposed, but the longitudinal compressive strength continues to be a limiting factor or studies are based on simplifications that warrant further analysis. A micromechanical model is used to (1) determine if the longitudinal compressive strength of composites can be improved with noncircular carbon fiber shapes and (2) characterize why some shapes are stronger than others in compression. In comparison to circular fibers, the results suggest that the strength can be increased by 10%–13% by using a specific six-lobe fiber shape and by 6%–9% for a three-lobe fiber shape. A slight increase is predicted in the compressive strength of the study two-lobe fiber but has the highest uncertainty and sensitivity to fiber orientation and misalignment direction. The underlying mechanism governing the compressive failure of the composites was linked to the unique stress fields created by the lobes, particularly the pressure stress in the matrix. Importantly, this work provides mechanics-based evidence of strength improvements from noncircular fiber shapes and insight on how matrix yielding is altered with alternative fiber shapes.

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

High Performance Access to Archival Data Stored in HDF4 and HDF5 on Cloud Object Stores Without Reformatting the Files

Cloud computing offers numerous advantages for users of extensive Earth science data collections. These benefits encompass direct online access to data files and granules from any location, scalable access supporting parallel computing workflows, and flexible computing tools enabling innovative experimentation with processing techniques. However, older archival file formats designed for distinct computing systems hinder efficient access to decade-long time-series data when compared to data stored in modern cloud-optimized formats like Web Object Stores (WOS), exemplified by Amazon Web Services’ Simple Storage Service (S3). We describe DMR++ (Dataset Metadata Response plus plus), a technology facilitating efficient access to HDF5 (Hierarchical Data Format, version 5) and HDF4 files stored on WOS systems without requiring data reformatting. DMR++ achieves performance comparable to technologies like Zarr while preserving the original file structure, a substantial benefit considering the vast quantity of archival files held by organizations such as NASA. Moreover, DMR++ typically outperforms cloud-optimized versions of HDF5. Essentially an XML (Extensible Markup Language) document usually stored alongside the described data, DMR++ can also be generated on-the-fly but is generally created during data staging to the WOS. Archival files that use HDF4/5 often store large arrays of numerical data. The data in these files is often compressed, typically reducing their size by a factor of four or more. To achieve efficient access to portions of those arrays, they are 'chunked' into smaller sub-arrays, each individually compressed. The chunk size is a compromise, where spinning disks can efficiently access data in smaller chunks while S3 favors larger chunks. A simple optimization of aggregating smaller chunks that are stored adjacently, transferring them in a single access and then individually decompressing them will improve performance. NASA data pose an additional challenge: special Application Programmer Interface (API) libraries are often needed to compute some variables. These libraries are incompatible with WOS environments. Our solution involves storing computed values in the DMR++ document or a companion file, making them accessible like other variables and eliminating the need for specialized APIs. We outline specific optimizations for both satellite grid and swath data stored in HDF4-EOS2 (Earth Observing System).

James Gallagher↗
DOE OSTI2020

Deep learning for in situ data compression of large turbulent flow simulations

As the size of turbulent flow simulations continues to grow, in situ data compression is becoming increasingly important for visualization, analysis, and restart checkpointing. For these applications, single-pass compression techniques with low computational and communication overhead are crucial. In this paper we present a deep-learning approach to in situ compression using an autoencoder architecture that is customized for three-dimensional turbulent flows and is well suited for contemporary heterogeneous computing resources. The autoencoder is compared against a recently introduced randomized single-pass singular value decomposition (SVD) for three different canonical turbulent flows: decaying homogeneous isotropic turbulence, a Taylor-Green vortex, and turbulent channel flow. Our proposed fully convolutional autoencoder architecture compresses turbulent flow snapshots by a factor of 64 with a single pass, allows for arbitrarily sized input fields, is cheaper to compute than the randomized single-pass SVD for typical simulation sizes, performs well on unseen flow configurations, and has been made publicly available. The results reported here show that the autoencoder dramatically outperforms a randomized single-pass SVD with similar compression ratio and yields comparable performance to a higher-rank decomposition with an order of magnitude less compression in regard to preserving a number of important statistical quantities such as turbulent kinetic energy, enstrophy, and Reynolds stresses.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

AEflow (Autoencoder fluid flow compression network) [SWR-22-29]

As the size of turbulent flow simulations continues to grow, in situ data compression is becoming increasingly important for visualization, analysis, and restart checkpointing. For these applications, single-pass compression techniques with low computational and communication overhead are crucial. In this paper we present a deep-learning approach to in situ compression using an autoencoder architecture that is customized for three-dimensional turbulent flows and is well suited for contemporary heterogeneous computing resources. The autoencoder is compared against a recently introduced randomized single-pass singular value decomposition (SVD) for three different canonical turbulent flows: decaying homogeneous isotropic turbulence, a Taylor-Green vortex, and turbulent channel flow. Our proposed fully convolutional autoencoder architecture compresses turbulent flow snapshots by a factor of 64 with a single pass, allows for arbitrarily sized input fields, is cheaper to compute than the randomized single-pass SVD for typical simulation sizes, performs well on unseen flow configurations, and has been made publicly available. The results reported here show that the autoencoder dramatically outperforms a randomized single-pass SVD with similar compression ratio and yields comparable performance to a higher-rank decomposition with an order of magnitude less compression in regard to preserving a number of important statistical quantities such as turbulent kinetic energy, enstrophy, and Reynolds stresses.

King, Ryan↗
NASA NTRS1919

Effect of Compression Ratio, Pressure, Temperature, and Humidity on Power

Among other factors which affect the horsepower of an airplane engine are the atmospheric pressure, and consequently the altitude at which the engine is working, and the compression ratio, or cylinder volume divided by clearance volume. The tests upon which this report is based were selected from a large number of runs made during the intercomparison of various gasolines to determine the variation of horsepower with altitude at three different compression ratios. The test results and conclusions are presented in this report.

Dickinson, H C↗
DOE OSTI2020

Two-Phase Fluid Flow Properties of Rough Fractures With Heterogeneous Wettability: Analysis With Lattice Boltzmann Simulations

Fractures are conduits for fluid flow in low-permeability geological formations. Multiphase flow properties of fractures are important in natural processes and in engineering applications such as the evaluation of the sealing capacity of caprocks and productivity of hydrocarbon-bearing tight rocks. Investigations of flow and transport through fractures typically focus on the effects of fracture geometric and mechanical factors such as aperture, roughness, and compressibility. The wettability of the fracture surfaces and its influence on microscale interfacial phenomena and macroscale effective transport properties are seldom studied. In this study, we investigated the effect of heterogeneous wetting properties on the displacement of water by supercritical CO2 through a series of lattice Boltzmann method simulations. The results show the evolution of the CO2 plume within a fracture is controlled by both the roughness of the aperture field and the wetting distribution. We combined these factors into a capillary pressure map that can be related to the macroscopic flow behavior of the fracture. We observed that heterogeneous wetting distributions promote the residual trapping of water where lower capillary pressures allowed for isolated water pockets in higher capillary pressure zones. Analysis of fracture unsteady relative permeability shows the effect of wetting on permeability evolution and provides support for the viscous-coupling relative permeability model. Finally, analysis of the steady-state relative permeability and saturation demonstrates a strong correlation between permeability and the standard deviation of the capillary pressure field. Thus, characterizing the distribution of wetting properties of fractures is crucial to understanding multiphase fracture flow and transport properties.

58 GEOSCIENCES↗
DOE OSTI2022

Nonnegative canonical tensor decomposition with linear constraints: nnCANDELINC

Abstract There is an emerging interest for tensor factorization applications in big‐data analytics and machine learning. To speed up the factorization of extra‐large datasets, organized in multidimensional arrays (also known as tensors), easy to compute compression‐based tensor representations, such as, Tucker and tensor train formats, are used to approximate the initial large‐tensor. Further, tensor factorization is used to extract latent features that can facilitate discoveries of new mechanisms and signatures hidden in the data, where the explainability of the latent features is of principal importance. Nonnegative tensor factorization extracts latent features that are naturally sparse and parts of the data, which makes them easily interpretable. However, to take into account available domain knowledge and subject matter expertise, often additional constraints need to be imposed, which lead us to canonical decomposition with linear constraints (CANDELINC), a canonical polyadic decomposition with rank deficient factors. In CANDELINC, Tucker compression is used as a preprocessing step, which lead to a larger residual error but to more explainable latent features. Here, we propose a nonnegative CANDELINC (nnCANDELINC) accomplished via a specific nonnegative Tucker decomposition; we refer to as minimal or canonical nonnegative Tucker. We derive several results required to understand the specificity of nnCANDELINC, focusing on the difficulties of preserving the nonnegative rank of a tensor to its Tucker core and comparing the real valued to nonnegative case. Finally, we demonstrate nnCANDELINC performance on synthetic and real‐world examples.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Spindown of Pulsars Interacting with Companion Winds: The Impact of Magnetospheric Compression

Pulsars in binary systems with strong companion winds can have the magnetopause separating their magnetosphere from the wind located well within their light cylinder. This bow-like enclosure effectively creates a waveguide that confines the pulsar's electromagnetic fields and can significantly alter its spindown. In this paper, we study the spindown of compressed pulsar magnetospheres in such systems. We parameterize the confinement as the ratio between the equatorial position of the magnetopause (or standoff distance) R m and the pulsar's light cylinder R LC . Using particle-in-cell simulations, we quantify the pulsar spindown for a range of compressions, R m /R LC = 1/3–1, and inclination angles, χ = 0°...90°, between magnetic and rotation axes. Our strongly confined models (R m /R LC = 1/3) show two distinct limits. For χ = 0°, the spindown of a compressed pulsar magnetosphere is enhanced by approximately a factor of three compared to an isolated pulsar due to the increased number of open magnetic field lines. Conversely, for χ = 90°, the compressed pulsar spins down at less than 40% of the rate of an isolated reference pulsar due to the mismatch between the pulsar wind stripe wavelength and the waveguide size. We apply our analysis to the 2.77 s oblique rotator (χ = 60°) in the double-pulsar system PSR J0737-3039. With the numerically derived spindown estimate, we constrain its surface magnetic field to B* ≈ (7.3 ± 0.2) × 10 11 G. We discuss the time modulation of its period derivative, the effects of compression on its braking index, and implications for the radio eclipse in PSR J0737-3039.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Geomechanical properties of the Meletta sandstone - the high-temperature heat storage reservoir rock of DeepStor

The DeepStor project aims at storing excess heat at temperatures up to 140 °C in the depleted Leopoldshafen oil field at a depth of about 1300 m. In order to gain knowledge on the target horizons, the different layers of the Meletta sandstone, samples cored in a block retrieved in a quarry near Nussloch where the Meletta sandstone outcrops were studied. Several petrophysical properties were investigated including mineralogy, porosity, permeability, thermal conductivity, P- and S-wave velocities and quality factor. A mechanical study focused on compressive strength under uniaxial and triaxial stress conditions, tensile strength, critical pressure and stress-dependence of physical properties. Our results show that the Meletta sandstone is heterogeneous, anisotropic, mechanically weak, stress-sensitive and prone to water weakening. Petrophysical measurements on few Meletta sandstone cores retrieved in boreholes at about 1250 m depth showed that the outcrop samples are significantly less cohesive and weaker. Therefore, one should consider the Nussloch outcrop as a good reservoir analog only with great caution. Several models were applied to account for our experimental results on anisotropy, mechanical behavior and stress-dependence of the outcrop samples. Our study provides a valuable data set which can feed numerical models to simulate the behavior of the host formation during heat exchange operations in the DeepStor project.

Geomechanics↗
NASA NTRS1989

An improved algorithm for the modeling of vapor flow in heat pipes

A heat pipe vapor flow algorithm suitable for use in codes on microcomputers is presented. The incompressible heat pipe vapor flow studies of Busse are extended to incorporate compressibility effects. The Busse velocity profile factor is treated as a function of temperature and pressure. The assumption of a uniform saturated vapor temperature determined by the local pressure at each cross section of the pipe is not made. Instead, a mean vapor temperature, defined by an energy integral, is determined in the course of the solution in addition to the pressure, saturation temperature at the wall, and the Busse velocity profile factor. For alkali metal working fluids, local species equilibrium is assumed. Temperature and pressure profiles are presented for several cases involving sodium heat pipes. An example for a heat pipe with an adiabatic section and two evaporators in sequence illustrates the ability to handle axially varying heat input. A sonic limit plot for a short evaporator falls between curves for the Busse and Levy inviscid sonic limits.

Tower, Leonard K.↗
NASA NTRS2024

Direct Ink Write 3D Printing of Fully Dense and Functionally Graded Liquid Metal Elastomer Foams

Liquid metal (LM) elastomer composites offer promising potential in soft robotics, wearable electronics, and human-machine interfaces. Direct ink write (DIW) 3D printing offers a versatile manufacturing technique capable of precise control over LM microstructures, yet challenges such as interfilament void formation in multilayer structures impact material performance. Here, a DIW strategy is introduced to control both LM microstructure and material architecture. Investigating three key process parameters–nozzle height, extrusion rate, and nondimensionalized nozzle velocity–it is found that nozzle height and velocity predominantly influence filament geometry. The nozzle height primarily dictates the aspect ratio of the filament and the formation of voids. A threshold print height based on filament geometry is identified; below the height, significant surface roughness occurs, and above the ink fractures, which facilitates the creation of porous structures with tunable stiffness and programmable LM microstructure. These porous architectures exhibit reduced density and enhanced thermal conductivity compared to cast samples. When used as a dielectric in a soft capacitive sensor, they display high sensitivity (gauge factor = 9.0), as permittivity increases with compressive strain. These results demonstrate the capability to simultaneously manipulate LM microstructure and geometric architecture in LM elastomer composites through precise control of print parameters, while maintaining geometric fidelity in the printed design.

Spencer Pak↗
NASA NTRS1972

Transport properties of liquid metal hydrogen under high pressures

A theory is developed for the compressibility and transport properties of liquid metallic hydrogen, near to its melting point and under high pressure. The interionic force law is assumed to be of the screened Coulomb type, because hydrogen has no core electrons. The random phase approximation is used to obtain the structure factor S(k) of the system in terms of the Fourier transform of this force law. The long wavelenth limit of the structure factor S(o) is related to the compressibility, which is much lower than that of alkali metals at their melting points. The diffusion constant at the melting point is obtained in terms of the Debye frequency, using a frequency spectrum analogous with the phonon spectrum of a solid. A similar argument is used to obtain the combined shear and bulk viscosities, but these depend also on S(o). The transport coefficients are found to be about the same size as those of alkali metals at their melting points.

Brown, R. C.↗
NASA NTRS1991

Data compression: The end-to-end information systems perspective for NASA space science missions

The unique characteristics of compressed data have important implications to the design of space science data systems, science applications, and data compression techniques. The sequential nature or data dependence between each of the sample values within a block of compressed data introduces an error multiplication or propagation factor which compounds the effects of communication errors. The data communication characteristics of the onboard data acquisition, storage, and telecommunication channels may influence the size of the compressed blocks and the frequency of included re-initialization points. The organization of the compressed data are continually changing depending on the entropy of the input data. This also results in a variable output rate from the instrument which may require buffering to interface with the spacecraft data system. On the ground, there exist key tradeoff issues associated with the distribution and management of the science data products when data compression techniques are applied in order to alleviate the constraints imposed by ground communication bandwidth and data storage capacity.

Tai, Wallace↗
DOE OSTI2020

Strong mutual increase in the efficiency of isotope-selective laser IR dissociation of molecules under nonequilibrium thermodynamic conditions of the compression shock under irradiation in a bimolecular mixture

We have revealed a strong (by a factor of 2 to 5) mutual increase in the yield of IR molecular dissociation (by the example of CF{sub 2}HCl and CF{sub 3}Br) and a significant (by a factor of 1.5 to 3) lowering of dissociation thresholds in the nonequilibrium thermodynamic conditions of compression shock in the irradiation of the molecules by resonance IR laser radiation in the bimolecular mixture in comparison with their individual irradiation. This opens up the possibility to perform efficient isotope-selective IR dissociation of molecules at lower excitation energy densities (Φ ⩽ 1.5 – 2.0 J cm{sup −2}) and thereby to improve the dissociation selectivity. This was demonstrated by the example of chlorine- and bromine-isotope selective dissociation of the specified molecules, which are characterised by quite small (less than 0.25 cm{sup −1}) isotope shifts in the IR vibrational absorption spectra excited by laser radiation. The enrichment coefficients K {sub enr}({sup 35}Cl / {sup 37}Cl) = 0.90 ± 0.05 in the residual CF{sub 2}HCl gas and K {sub enr}({sup 79}Br / {sup 81}Br) in the resultant Br{sub 2} product are obtained when the CF{sub 2}HCl : CF{sub 3}Br = 1 : 1 molecular mixture and CF{sub 3}Br molecules, respectively, are irradiated by the 9R(30) CO{sub 2} laser line (frequency, 1084.635 cm{sup −1}) at an energy density Φ ≈ 1.3 J cm{sup −2}. (laser isotope separation)

36 MATERIALS SCIENCE↗
NASA NTRS1988

Magnetic ULF fluctuations in the compressional zone of AMPTE's artificial comets

The two Ba releases in the solar wind, termed artificial comets (the first in interplanetary space, the second in the terrestrial magnetosheath), showed a number of common magnetic features. Both times a magnetic cavity was detected and a field pile-up observed with magnitudes several times the ambient field strength upstream of the cavity. The magnetic fluctuations in the compressed region are generally enhanced by a factor comparable to the amount of field pile-up. There is a peak in the spectra of both events around 0.1 Hz in the component which is perpendicular to the solar-wind velocity vector and almost field-aligned. This magnetosonic wave has been interpreted as the fundamental mode of resonance oscillations of the compression zone. For frequencies beyond 2 Hz the spectra decrease more steeply in the case of the second 'comet' than in the first. This is due to the interaction of the supersonic solar wind with the first comet. The spectra obtained during the first comet at the solar-wind/ion-cloud interface are identical to those observed during bow-shock crossings.

Kloecker, N.↗
NASA NTRS1993

Dynamics of large scale impacts on Venus and Earth

Large scale impacts are a key aspect of the accretion and growth of the planets, the evolution of their atmospheres, and the viability of their life forms. We have performed an extensive series of numerical calculations that examined the mechanics of impacts over a broad range of conditions and are now extending these to account for the effects of the planetary atmosphere. We have examined the effects of large scale impacts in which the trapping and compression of an atmosphere during impact is a significant factor in the transfer of energy to the atmosphere. The various energy transfer regimes and where conventional drag and trapping and subsequent compression of atmosphere between the bolide and planetary surface are significant are shown.

Okeefe, John D.↗
DOE OSTI2021

DNTTD (Distributed Non-Negative Tensor Train Decomposition)

The era of exascale computing opens new venues for innovations and discoveries in many scientific, engineering, and commercial fields. However, with the exa flops also come the extra-large high-dimensional data generated by high performance computing. High-dimensional data is presented as multidimensional arrays, aka tensors. The presence of latent (not directly observable) structures in the tensor allows a unique representation and compression of the data by classical tensor factorization techniques. However, the classical tensor methods are not always stable or they can be exponential in their memory requirements, which makes them not suitable for high-dimensional tensors. Tensor train (TT) is a state-of-the-art tensor network introduced for factorization of high-dimensional tensors. TT transforms the initial high-dimensional tensor in a network of three-dimensional tensors that requires only a linear storage. Many real-world data, such as, density, temperature, population, probability, etc., are non-negative and for an easy interpretation, the algorithms preserving non-negativity are preferred. Here, we introduce a distributed non-negative tensor-train and demonstrate its scalability and the compression on synthetic and real world big datasets.

Bhattarai, Manish↗