SEARCH · Search NASA

Results for “Compression”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 523 records · Page 29

All sources NASA NTRS DOE OSTI

NASA NTRS2005

Compression and Tensile Creep of Binary NiAl

Compression creep and long term tensile creep studies were conducted on cast and extruded binary NiAl in the temperature range 700-1200 K with the objectives of characterizing and understanding the creep mechanisms. Inverse and normal primary creep curves were observed in both compression and tension creep depending on stress and temperature although an asymmetrical response was observed under these two stress states. It was concluded that the primary creep of NiAl is limited by dislocation mobility. The stress exponents, n, for compression and tensile creep were similar varying between about 5 and 14. However, there were significant differences in the stress dependence of the activation energies for compression and tensile creep. The true activation energy for tensile creep, Q(sub c), was constant and equal to about 400 kJ/mol between 20 and 50 MPa but decreased to a constant value of 250 kJ/mol between 50 and 110 MPa. The activation energy was observed to be inversely stress dependent above 110 MPa. In contrast, Q(sub c) = 300 kJ/mol for compression creep was constant between 25 and 70 MPa and inversely dependent on the true stress above 70 MPa. A detailed discussion of the probable dislocation creep mechanisms governing compressive and tensile creep of NiAl is presented. It is concluded that the non-conservative motion of jogs on screw dislocations influenced the nature of the primary creep curves, where the climb of these jogs involves either the next nearest neighbor or the six-jump cycle vacancy diffusion mechanism. The probable natures of the atom-vacancy exchange that occur within the core of an edge dislocation undergoing climb in NiAl are schematically examined.

Raj, Sai V.↗

NASA NTRS2010

Reconfigurable Hardware for Compressing Hyperspectral Image Data

High-speed, low-power, reconfigurable electronic hardware has been developed to implement ICER-3D, an algorithm for compressing hyperspectral-image data. The algorithm and parts thereof have been the topics of several NASA Tech Briefs articles, including Context Modeler for Wavelet Compression of Hyperspectral Images (NPO-43239) and ICER-3D Hyperspectral Image Compression Software (NPO-43238), which appear elsewhere in this issue of NASA Tech Briefs. As described in more detail in those articles, the algorithm includes three main subalgorithms: one for computing wavelet transforms, one for context modeling, and one for entropy encoding. For the purpose of designing the hardware, these subalgorithms are treated as modules to be implemented efficiently in field-programmable gate arrays (FPGAs). The design takes advantage of industry- standard, commercially available FPGAs. The implementation targets the Xilinx Virtex II pro architecture, which has embedded PowerPC processor cores with flexible on-chip bus architecture. It incorporates an efficient parallel and pipelined architecture to compress the three-dimensional image data. The design provides for internal buffering to minimize intensive input/output operations while making efficient use of offchip memory. The design is scalable in that the subalgorithms are implemented as independent hardware modules that can be combined in parallel to increase throughput. The on-chip processor manages the overall operation of the compression system, including execution of the top-level control functions as well as scheduling, initiating, and monitoring processes. The design prototype has been demonstrated to be capable of compressing hyperspectral data at a rate of 4.5 megasamples per second at a conservative clock frequency of 50 MHz, with a potential for substantially greater throughput at a higher clock frequency. The power consumption of the prototype is less than 6.5 W. The reconfigurability (by means of reprogramming) of the FPGAs makes it possible to effectively alter the design to some extent to satisfy different requirements without adding hardware. The implementation could be easily propagated to future FPGA generations and/or to custom application-specific integrated circuits.

Aranki, Nazeeh↗

NASA NTRS2011

Alternative Compression Garments

Orthostatic intolerance after spaceflight is still an issue for astronauts as no in-flight countermeasure has been 100% effective. Future anti-gravity suits (AGS) may be similar to the Shuttle era inflatable AGS or may be a mechanical compression device like the Russian Kentavr. We have evaluated the above garments as well as elastic, gradient compression garments of varying magnitude and determined that breast-high elastic compression garments may be a suitable replacement to the current AGS. This new garment should be more comfortable than the AGS, easy to don and doff, and as effective a countermeasure to orthostatic intolerance. Furthermore, these new compression garments could be worn for several days after space flight as necessary if symptoms persisted. We conducted two studies to evaluate elastic, gradient compression garments. The purpose of these studies was to evaluate the comfort and efficacy of an alternative compression garment (ACG) immediately after actual space flight and 6 degree head-down tilt bed rest as a model of space flight, and to determine if they would impact recovery if worn for up to three days after bed rest.

Stenger, M. B.↗

NASA NTRS2021

Role of Compressive Viscosity and Thermal Conductivity on the Damping of Slow Waves in Coronal Loops with and Without Heating–Cooling Imbalance

In the present article, we derive a new dispersion relation for slow magnetoacoustic waves invoking the effect of thermal conductivity, compressive viscosity, radiation, and an unknown heating term along with the consideration of heating–cooling imbalance from linearized MHD equations. We solve the general dispersion relation to understand the role of compressive viscosity and thermal conductivity in the damping of slow waves in coronal loops with and without heating–cooling imbalance. We have analyzed the wave damping for the range of loop length L=50--500 Mm, temperature T=5--30 MK, and density ρ=10^(−11)--10^(−9) kg/cu.m. It was found that the inclusion of compressive viscosity along with thermal conductivity significantly enhances the damping of the fundamental mode oscillations in shorter (e.g. L=50 Mm) and super-hot (T>10 MK) loops. However, the role of viscosity in the damping is insignificant in longer (e.g. L=500 Mm) and hot loops (T≤10 MK) where, instead, thermal conductivity along with the presence of heating–cooling imbalance plays a dominant role. For shorter loops at a super-hot regime of temperature, the increment in the loop density substantially enhances the damping of the fundamental modes due to thermal conductivity when viscosity is absent, however, when the compressive viscosity is added the increase in density substantially weakens the damping. Thermal conductivity alone is found to play a dominant role in longer loops at lower temperatures (T≤10 MK), while compressive viscosity dominates the damping at super-hot temperatures (T>10 MK) in shorter loops. The predicted scaling law between damping time (τ) and wave period (P) is found to better match the observed SUMER (Solar Ultraviolet Measurements of Emitted Radiation) oscillations when the heating–cooling imbalance is taken into account in addition to thermal conductivity and compressive viscosity for the damping of the fundamental slow mode oscillations.

Abhinav Prasad↗

NASA NTRS2022

Sub-Scale Adsorption and Compression CO2 Removal System Re-Design

This system is a re-design of NASA’s previously developed Thermally Coupled Temperature Swing Adsorption and Compression (TC-TSAC) systems, providing an air revitalization alternative to assist in the agency’s Moon to Mars exploration objectives. The system consists of two half-cycles whereby packed beds of regenerable bulk sorbents and heat cycles simultaneously adsorb and compress carbon dioxide. The team designed the adsorption and compression beds in a cylindrical shape to maximize airflow. A desiccant bed helps lower humidity and the sorbent Zeolite 13X is used to capture carbon dioxide. Both are monitored by sensors. There is a custom heater within the system that lies in the adsorption bed to regenerate the sorbent, and there is a cooler around the compression bed. The system produced for NASA modeling, experimental test results, and operational results to be able to be scaled up to 4kg CO2 removal per day. The system was found to be 1/16 scale for 1kg of CO2 removal per day. The adsorption and desorption processes were successful, however issues with making the compression bed airtight resulted in an inability to demonstrate full compression. The team provided design suggestions and alternative solutions given these results. This paper describes the final design, fabrication, assembly, and testing of the TC-TSAC re-design.

Joaquin Pesqueira↗

DOE OSTI2018

An L$_0$L$_1$-norm compressive sensing paradigm for the construction of sparse predictive lattice models using mixed integer quadratic programming

First-principles based lattice models allow the modeling of ab initio thermodynamics of crystalline mixtures for applications such as the construction of phase diagrams and the identification of ground state atomic orderings. The recent development of compressive sensing approaches for the construction of lattice models has further enabled the systematic construction of sparse physical models without the need for human intuition other than requiring the compactness of effective cluster interactions. However, conventional compressive sensing based on L1-norm regularization is strictly only applicable to certain classes of optimization problems and is otherwise not guaranteed to generate optimally sparse and transferable results, so that the method can only be applied to some materials science applications. In this paper, we illustrate a more robust L0L1-norm compressive-sensing method that removes the limitations of conventional compressive sensing and generally results in sparser lattice models that are at least as predictive as those obtained from L1-norm compressive sensing. Apart from the theory, a practical implementation based on state-of-the-art mixed-integer quadratic programming (MIQP) is proposed. The robustness of our methodology is illustrated for four different transition-metal oxides with relevance as battery cathode materials: Li2xTi2(1-x)O2, Li2xNi2yO2, MgxCr2O4, and NaxCrO2. This method provides a practical and robust approach for the construction of sparser and more predictive lattice models, improving on the compressive sensing paradigm and making it applicable to a much broader range of applications.

Huang, W↗

DOE OSTI2022

Compressing micro-operations in scheduler entries in a processor

An electronic device includes a processor having a micro-operation queue, multiple scheduler entries, and scheduler compression logic. When a pair of micro-operations in the micro-operation queue is compressible in accordance with one or more compressibility rules, the scheduler compression logic acquires the pair of micro-operations from the micro-operation queue and stores information from both micro-operations of the pair of micro-operations into different portions in a single scheduler entry. In this way, the scheduler compression logic compresses the pair of micro-operations into the single scheduler entry.

Boyer, Michael W.↗

DOE OSTI2023

Classical and quantum compression for edge computing: the ubiquitous data dimensionality reduction

Edge computing aims to address the challenges associated with communicating and transferring large amounts of data generated remotely to a data center in a timely and efficient manner. A central pillar of edge computing is local (i.e., at- or near-source) data processing capability so that data transfer to a data center for processing can be minimized. Data compression at the edge is therefore a natural component of edge workflows. Here we present a survey of data compression algorithms with a focus on edge computing. Not all compression algorithms can accommodate the data type heterogeneity, tight processing and communication time constraints, or energy efficiency requirement characteristics of edge computing. We discuss specific examples of compression algorithms that are being explored in the context of edge computing. We end our review with a brief survey of emerging quantum compression techniques that are of importance in quantum information processing, including the proposed concept of quantum edge computing.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Macro- and micro-compression testing of shales

Here, macro- and micro-geomechanical properties of shales were investigated at millimeter- and micrometer-scale using an example of the Woodford Shale. Geomechanical properties, such as uniaxial (unconfined) compressive strength and Young's modulus, were quantified at the millimeter-scale and compared with results from micro-compression testing experiments of FIB-SEM-nanofabricated micro-pillars. Size-scale and compositional/structural heterogeneity effect on elasto-plastic deformation and failure behavior of shales were investigated. Also, relationship between elemental/mineral composition and unconfined compressive strength and Young's modulus, at a micrometer-scale, was discussed. It was shown that geomechanical properties of shales are scale-dependent and are strongly affected by compositional/structural anisotropy. In particular, micro-compression testing experiments showed non-uniformly distributed compressive strength and Young's modulus within the investigated Woodford Shale rock samples. It was demonstrated, that geomechanical properties of shales, investigated at the micrometer-scale, tend to be affected by different minerals and/or pores, while the same properties, investigated at the millimeter-scale, are governed by different micro-facies (and/or micro-fractures) present within the rock. This shows that geomechanical properties of shales can be dramatically different depending on the scale of investigation and compositional/structural heterogeneity of these rocks, and therefore are not easily transferable across the scales.

58 GEOSCIENCES↗

DOE OSTI2015

Behavior of sodium borosilicate glasses under compression using molecular dynamics

We have performed classical molecular dynamics simulations in order to study the changes under compression in the local and medium range structural properties of three sodium borosilicate glasses with varying sodium content. These glasses have been isostatically compressed up to 20 GPa and then decompressed in order to analyze the different mechanisms that affect densification, alongside with the permanent modifications of the structure after a full compression/decompression cycle. The results show that the atomic packing is the prominent characteristic that governs the amount of densification in the glass, as well as the setup of the permanent densification. During compression, the bulk modulus increases linearly up to approximately 15 GPa and more rapidly for higher pressures, a behavior which is reflected on the rate of increase of the average coordination for B and Na. Radial distribution functions at different pressures during the cycle help to quantify the amount of distortions in the elementary structural units, with a pronounced shortening of the Na–Na and Na–O bond lengths during compression. A subsequent decomposition of the glassy matrix into elementary Voronoi volumes verifies the high compressibility of Na-rich regions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Massive compression for high data rate macromolecular crystallography (HDRMX): impact on diffraction data and subsequent structural analysis

New higher-count-rate, integrating, large-area X-ray detectors with framing rates as high as 17400 images per second are beginning to be available. These will soon be used for specialized macromolecular crystallography experiments but will require optimal lossy compression algorithms to enable systems to keep up with data throughput. Some information may be lost. Can we minimize this loss with acceptable impact on structural information? To explore this question, we have considered several approaches: summing short sequences of images, binning to create the effect of larger pixels, use of JPEG-2000 lossy wavelet-based compression, and use of Hcompress, which is a Haar-wavelet-based lossy compression borrowed from astronomy. We also explore the effect of the combination of summing, binning, and Hcompress or JPEG-2000. In each of these last two methods one can specify approximately how much one wants the result to be compressed from the starting file size. These provide particularly effective lossy compressions that retain essential information for structure solution from Bragg reflections.

47 OTHER INSTRUMENTATION↗

DOE OSTI2023

Progressive Tree-Based Compression of Large-Scale Particle Data

Scientific simulations and observations using particles have been creating large datasets that require effective and efficient data reduction to store, transfer, and analyze. However, current approaches either compress only small data well while being inefficient for large data, or handle large data but with insufficient compression. Toward effective and scalable compression/decompression of particle positions, we introduce new kinds of particle hierarchies and corresponding traversal orders that quickly reduce reconstruction error while being fast and low in memory footprint. Our solution to compression of large-scale particle data is a flexible block-based hierarchy that supports progressive, random-access, and error-driven decoding, where error estimation heuristics can be supplied by the user. For low-level node encoding, we introduce new schemes that effectively compress both uniform and densely structured particle distributions. Our proposed methods thus target all three phases of a tree-based particle compression pipeline, namely tree construction, tree traversal, and node encoding. In conclusion, the improved efficacy and flexibility of these methods over existing compressors are demonstrated through extensive experimentation, using a wide range of scientific particle datasets.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Physics-Driven Convolutional Autoencoder Approach for CFD Data Compressions: Preprint

With the growing size and complexity of turbulent flow models, data compression approaches are of the utmost importance to analyze, visualize, or restart the simulations. Recently, in-situ autoencoder-based compression approaches have been proposed and shown to be effective at producing reduced representations of turbulent flow data. However, these approaches focus solely on training the model using point-wise sample reconstruction losses that do not take advantage of the physical properties of turbulent flows. In this paper, we show that training autoencoders with additional physics-informed regularizations, e.g., enforcing incompressibility and preserving enstrophy, improves the compression model in three ways: (i) the compressed data better conform to known physics for homogeneous isotropic turbulence without negatively impacting point-wise reconstruction quality, (ii) inspection of the gradients of the trained model uncovers changes to the learned compression mapping that can facilitate the use of explainability techniques, and (iii) as a performance byproduct, training losses are shown to converge up to 12x faster than the baseline model.

auto-encoders↗

DOE OSTI2017

Cancellation of Raman self-frequency shift for compression of optical pulses

We study to which extent a fiber soliton can be manipulated by a specially chosen continuous pump wave. A group velocity matched pump scatters at the soliton, which is compressed due to the energy/momentum transfer. As the pump scattering is very sensitive to the velocity matching condition, soliton compression is quickly destroyed by the soliton self-frequency shift (SSFS). This is especially true for ultrashort pulses: SSFS inevitably impairs the degree of compression. We demonstrate numerically that soliton enhancement can be restored to some extent and the compressed soliton can be stabilized, provided that SSFS is canceled by a second pump wave. Still the available compression degree is considerably smaller than that in the Raman-free nonlinear fibers.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2021

Effect of particle characteristics on the evolution of particle size, particle morphology, and fabric of sands loaded under uniaxial compression

This work presents the results and analyses of uniaxial compression experiments performed on three silica sands. The sands have comparable particle-size distributions, but their particles differ in morphology and strength. Cylindrical samples of the three sands were compressed in a loading device placed inside an X-ray microscope (XRM) and scanned at multiple stress levels during uniaxial compression. 3D tomography data of the samples obtained from the XRM at different stress levels were then analyzed to obtain the distributions of particle size, particle morphology, and interparticle contact normals within the sample. Results indicate that: (1) the compressibility of the sands loaded under uniaxial compression is closely tied to particle morphology and strength and (2) the anisotropy in the orientations of interparticle contact normals generally increases with axial stress; however, this increase is limited by the occurrence of particle crushing in the sample.

3D X-ray computed tomography↗

DOE OSTI2020

Impacts of swinging door lossy compression of synchrophasor data

As the number of operational Phasor Measurement Units (PMUs) is increasing, compression is becoming crucial for efficiently transferring and storing enormous amount of synchrophasor data continuously measured from a power system. Some utilities in the U.S. have already adopted a nonlinear compression technique, called Swinging Door Algorithm (SDA), assuming compressed data meets technical and regulatory requirements without resulting in any degradation of the measurements. This paper studies impacts of this compression algorithm on field measured and simulated PMU data, and presents results from spectral analyses of raw and decompressed measurements. The results show blind application of the SDA compression alters frequency content in the measurements and introduces false harmonics and aliasing. These can lead to false conclusions being drawn from the measurements about the power system condition.

42 ENGINEERING↗

DOE OSTI2021

Transport of Compressed Woody Biomass: Correlating Rheology and Microcompounder Measurements

Transport of milled solid biomass can be problematic in biomass conversion processes due to the material’s high cohesiveness, low bulk density, and poor flowability. Here, the goal is to investigate the flow behavior of compressed biomass under conditions similar to compression-screw feeders. To mimic the flow of woody biomass inside a compression-screw feeder, two lignocellulosic biomass feedstocks were fed to a co-rotating twin-screw microcompounder. Force and screw speed from the microcompounder were correlated to viscosity in a traditional rheometer, where low-density polyethylene served as a control. The deformation of compressed biomass in a lab-scale compounder is strongly dependent on screw speed and moisture content. Shear stress in woody biomass decreased with the shear rate, indicating negative plastic viscosity. Moreover, viscosity decreased one order of magnitude as screw speed increased from 10 to 90 rpm. Increasing moisture from 10 to 50% reduced the viscosity of the compressed biomass by 60%.

09 BIOMASS FUELS↗

DOE OSTI2026

An Algorithm for Atom-Centered Lossy Compression of the Atomic Orbital Basis in Density Functional Theory Calculations

Large atomic-orbital (AO) basis sets of at least triple and preferably quadruple-ζ (QZ) size are required to adequately converge Kohn–Sham density functional theory (DFT) calculations toward the complete basis set limit. However, incrementing the cardinal number by one nearly doubles the AO basis dimension, and the computational cost scales as the cube of the AO dimension, so this is very computationally demanding. Here, in this work, we develop and test a threshold-based natural atomic orbital (NAO) scheme in which ϵ-NAOs are obtained as eigenfunctions of atomic blocks of the density matrix in a one-center orthogonalized representation. This enables compression of the AO basis that is optimal for a given threshold, 10 –ϵ , by discarding NAOs with occupation numbers below that threshold. Extensive pilot test calculations using the Hartree–Fock functional and taking the converged density matrix as input suggest that a threshold of 10 –5 can yield a compression factor (ratio of AO to compressed ϵ-NAO dimension) between 2.5 and 4.5 for the QZ pc-3 basis. The errors in relative energies are typically less than 0.1 kcal/mol when the compressed basis is used instead of the uncompressed basis. Between 10 and 100 times smaller errors (i.e., usually less than 0.01 kcal/mol) can be obtained with a threshold 10 –7 , while the compression factor is typically between 2 and 2.5.

basis sets↗