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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 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
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

A MHz X-ray diffraction set-up for dynamic compression experiments in the diamond anvil cell

An experimental platform for dynamic diamond anvil cell (dDAC) research has been developed at the High Energy Density (HED) Instrument at the European X-ray Free Electron Laser (European XFEL). Advantage was taken of the high repetition rate of the European XFEL (up to 4.5 MHz) to collect pulse-resolved MHz X-ray diffraction data from samples as they are dynamically compressed at intermediate strain rates (≤10 3 s −1 ), where up to 352 diffraction images can be collected from a single pulse train. The set-up employs piezo-driven dDACs capable of compressing samples in ≥340 µs, compatible with the maximum length of the pulse train (550 µs). Results from rapid compression experiments on a wide range of sample systems with different X-ray scattering powers are presented. A maximum compression rate of 87 TPa s −1 was observed during the fast compression of Au, while a strain rate of ∼1100 s −1 was achieved during the rapid compression of N 2 at 23 TPa s −1 .

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Spaced Orthocyclic Winding Pattern for Improved Die Compressed Coils

Winding fill, coil fill, or packing factor, is critical to the performance of many types of electromagnetic devices from electric machines to actuators, transformers, inductors, etc. One technique to increase the packing of conductors in the winding area is to compress round magnet wire conductors in a die, so that they deform and air voids between coil turns are removed. The winding layout of the coil turns on a bobbin before compression has a direct impact on the achievable coil fill and the damage to the coil insulation or conductors after compression. It is thought that winding the turns in an orthocyclic pattern on the bobbin before compression would minimize damage to the turns. This however causes turns to displace during the winding compression process. A new pre-compression winding pattern is proposed, a spaced orthocyclic winding, to minimize turn displacement and damage. A design of experiments study has been carried out to optimize this winding method and to compare it to the traditional orthocyclic winding.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Efficient Data Compression for 3D Sparse TPC via Bicephalous Convolutional Autoencoder

Real-time data collection and analysis in large experimental facilities present a great challenge across multiple domains, including high energy physics, nuclear physics, and cosmology. To address this, machine learning (ML)-based methods for real-time data compression have drawn significant attention. However, unlike natural image data, such as CIFAR and ImageNet that are relatively small-sized and continuous, scientific data often come in as three-dimensional 3D data volumes at high rates with high sparsity (many zeros) and non-Gaussian value distribution. This makes direct application of popular ML compression methods, as well as conventional data compression methods, suboptimal. To address these obstacles, this work introduces a dual-head autoencoder to resolve sparsity and regression simultaneously, called Bicephalous Convolutional AutoEncoder (BCAE). This method shows advantages both in compression fidelity and ratio compared to traditional data compression methods, such as MGARD, SZ, and ZFP. To achieve similar fidelity, the best performer among the traditional methods can reach only half the compression ratio of BCAE. Moreover, a thorough ablation study of the BCAE method shows that a dedicated segmentation decoder improves the reconstruction.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2018

Compression Analytics for Classification and Anomaly Detection within Network Communication

Here, the flexibility of network communication within Internet protocols is fundamental to network function, yet this same flexibility permits the possibility of malicious use. In particular, malicious behavior can masquerade as benign traffic, thus evading systems designed to catch misuse of network resources. However, perfect imitation of benign traffic is difficult, meaning that small unintentional deviations from normal can occur. Identifying these deviations requires that the defenders know what features reveal malicious behavior. Herein we present an application of compression-based analytics to network communication that can reduce the need for defenders to know a priori what features they need to examine. Motivating the approach is the idea that compression relies on the ability to discover and make use of predictable elements in information, thereby highlighting any deviations between expected and received content. We introduce a so-called “slice compression” score to identify malicious or anomalous communication in two ways. First, we apply normalized compression distances (NCDs) to classification problems and discuss methods for reducing the noise by excising application content (as opposed to protocol features) using slice compression. Second, we present a new technique for anomaly detection, referred to as slice compression for anomaly detection (SCADe). A diverse collection of datasets are analyzed to illustrate the efficacy of the proposed approaches. While our focus is network communication, other types of data are also considered to illustrate the generality of the method.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

A General Framework for Progressive Data Compression and Retrieval

In scientific simulations, observations, and experiments, the transfer of data to and from disk and across networks has become a major bottleneck for data analysis and visualization. Compression techniques have been employed to tackle this challenge, but traditional lossy methods often demand conservative error tolerances to meet the numerical accuracy requirements of both anticipated and unknown data analysis tasks. Progressive data compression and retrieval has emerged as a promising solution, where each analysis task dictates its own accuracy needs. However, few analysis algorithms inherently support progressive data processing, and adapting compression techniques, file formats, client/server frameworks, and APIs to support progressivity can be challenging. Here, this paper presents a framework that enables progressive-precision data queries for any data compressor or numerical representation. Our strategy hinges on a multi-component representation that successively reduces the error between the original and compressed field, allowing each field in the progressive sequence to be expressed as a partial sum of components. We have implemented this approach with four established scientific data compressors and assessed its effectiveness using real-world data sets from the SDRBench collection. The results show that our framework competes in accuracy with the standalone compressors it is based upon. Additionally, (de)compression time is proportional to the number of components requested by the user. Finally, our framework allows for fully lossless compression using lossy compressors when a sufficient number of components are employed.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Large-Scale Compressibility in Rotating Flows of Astrophysical Plasma in the Shallow Water Approximation

Two systems of magnetohydrodynamic equations in the shallow water approximation are proposed as a basis for studies in the field of plasma astrophysics: the system of equations with a full allowance for the Coriolis force and the system of equations on the β-plane in which the changes of the Coriolis parameter are linear in coordinate. Both systems of equations take into account such fundamentally important phenomena in plasma astrophysics as the compressibility and external magnetic field effects, increasing significantly the potential for applying these equations to study astrophysical objects. Compressibility in plasma astrophysics is shown to change significantly the dispersion laws for magneto-Poincare, magnetostrophic, and magneto-Rossby waves. The same nonlinear interactions as those in the absence of compressibility have been found to be realized in the case of a compressible rotating plasma. Three-wave equations in the weak nonlinearity approximation, in which the interaction coefficients depend on plasma large-scale compressibility and thermodynamic characteristics, have been derived by the method of multiscale expansions. Expressions for the growth rates of the parametric instabilities of three-wave interactions with large-scale compressibility have been derived.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Error Analysis of ZFP Compression for Floating-Point Data

Compression of floating-point data will play an important role in high-performance computing as data bandwidth and storage become dominant costs. Lossy compression of floating-point data is powerful, but theoretical results are needed to bound its errors when used to store look-up tables, simulation results, or even the solution state during the computation. In this paper, we analyze the round-off error introduced by ZFP, a lossy compression algorithm. Here, the stopping criteria for ZFP depends on the compression mode specified by the user: fixed rate, fixed accuracy, or fixed precision [P. Lindstrom, ZFP 0.5.3 Documentation, 2018]. While most of our discussion is focused on the fixed precision mode of ZFP, we establish a bound on the error introduced by all three compression modes. In order to tightly capture the error, first we introduce a vector space that allows us to work with binary representations of components. Under this vector space, we define operators that implement each step of the ZFP compression and decompression to establish a bound on the error caused by ZFP. To conclude, numerical tests are provided to demonstrate the accuracy of the established bounds.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

The molecular architecture distinctions between compression, opposite and normal wood of Pinus radiata

In gymnosperms compression wood is a specialised type of structural cell wall formed in response to biomechanical stresses. The differences in terms of gross structure, ultrastructure and chemistry are well-known. However, the differences between compression wood, normal wood, and opposite wood regarding the arrangements and interactions of the various polymers and water within their cell walls still needs to be established. The analysis of 13 C-labelled Pinus radiata by solid-state NMR spectroscopy and other complementary techniques revealed several new aspects of compression and opposite wood molecular architecture. Compared to normal wood, compression wood has a lower water content, its overall nanoporosity is reduced, and the water and matrix polymers have a lower molecular mobility. Galactan, which is a specific marker of compression wood, is broadly distributed within the cell wall, disordered, and not aligned with cellulose, and is found to be in close proximity to xylan. Dehydroabietic acid (a resin acid) is immobilised and close to the H-lignin only in compression wood. Although the overall molecular mobility of normal wood and opposite wood are similar, opposite wood has different arabinose conformations, a large increase in the amount of chain ends, contains significantly more galactan and has additional unassigned mobile components highlighting the different molecular arrangement of cell wall polymers in opposite and normal wood.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Error-Bounded Learned Scientific Data Compression with Preservation of Derived Quantities

Scientific applications continue to grow and produce extremely large amounts of data, which require efficient compression algorithms for long-term storage. Compression errors in scientific applications can have a deleterious impact on downstream processing. Thus, it is crucial to preserve all the “known” Quantities of Interest (QoI) during compression. To address this issue, most existing approaches guarantee the reconstruction error of the original data or primary data (PD), but cannot directly control the problem of preserving the QoI. In this work, we propose a physics-informed compression technique that is composed of two parts: (i) reduction of the PD with bounded errors and (ii) preservation of the QoI. In the first step, we combine tensor decompositions, autoencoders, product quantizers, and error-bounded lossy compressors to bound the reconstruction error at high levels of compression. In the second step, we use constraint satisfaction post-processing followed by quantization to preserve the QoI. To illustrate the challenges of reducing the reconstruction errors of the PD and QoI, we focus on simulation data generated by a large-scale fusion code, XGC, which can produce tens of petabytes in a single day. The results show that our approach can achieve a high compression amount while accurately preserving the QoI within scientifically acceptable bounds.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Exploring the High-Pressure Phases of Carbon through X-ray Diffraction of Dynamic Compression Experiments on Sandia’s Z Pulsed Power Facility

The carbon phase diagram is rich with polymorphs which possess very different physical and optical properties ideal for different scientific and engineering applications. An understanding of the dynamically driven phase transitions in carbon is particularly important for applications in inertial confinement fusion, as well as planetary and meteorite impact histories. Experiments on the Z Pulsed Power Facility at Sandia National Laboratories generate dynamically compressed high-pressure states of matter with exceptional uniformity, duration, and size that are ideal for investigations of fundamental material properties. X-ray diffraction (XRD) is an important material physics measurement because it enables direct observation of the strain and compression of the crystal lattice, and it enables the detection and identification of phase transitions. Several unique challenges of dynamic compression experiments on Z prevent using XRD systems typically utilized at other dynamic compression facilities, so novel XRD diagnostics have been designed and implemented. We performed experiments on Z to shock compress carbon (pyrolytic graphite) samples to pressures of 150–320 GPa. The Z-Beamlet Laser generated Mn-Heα (6.2 keV) X-rays to probe the shock-compressed carbon sample, and the new XRD diagnostics measured changes in the diffraction pattern as the carbon transformed into its high-pressure phases. Quantitative analysis of the dynamic XRD patterns in combination with continuum velocimetry information constrained the stability fields and melting of high-pressure carbon polymorphs.

36 MATERIALS SCIENCE↗
NASA NTRS2006

Low-Complexity Adaptive Lossless Compression of Hyperspectral Imagery

A low-complexity, adaptive predictive technique for lossless compression of hyperspectral imagery is described. This technique is designed to be suitable for implementation in hardware such as a field programmable gate array (FPGA); such an implementation could be used for high-speed compression of hyperspectral imagery onboard a spacecraft. The predictive step of the technique makes use of the sign algorithm, which is a relative of the least mean square (LMS) algorithm from the field of low-complexity adaptive filtering. The compressed data stream consists of prediction residuals encoded using a method similar to that of the JPEG-LS lossless image compression standard. Compression results are presented for several datasets including some raw Airborne Visible/ Infrared Imaging Spectrometer (AVIRIS) datasets and raw Atmospheric Infrared Sounder (AIRS) datasets. The compression effectiveness obtained with the technique is competitive with that of the best of previously described techniques with similar complexity.

lossless data compression↗
DOE OSTI2022

High pressure phase transition and strength estimate in polycrystalline alumina during laser-driven shock compression

Alumina (Al 2 O 3 ) is an important ceramic material notable for its compressive strength and hardness. It represents one of the major oxide components of the Earth's mantle. Static compression experiments have reported evidence for phase transformations from the trigonal α-corundum phase to the orthorhombic Rh 2 O 3 (II)-type structure at ~90 GPa, and then to the post-perovskite structure at ~130 GPa, but these phases have yet to be directly observed under shock compression. In this work, we describe laser-driven shock compression experiments on polycrystalline alumina conducted at the Matter in Extreme Conditions endstation of the Linac Coherent Light Source. Ultrafast x-ray pulses (50 fs, 10 12 photons/pulse) were used to probe the atomic-level response at different times during shock propagation and subsequent pressure release. At 107 ± 8 GPa on the Hugoniot, we observe diffraction peaks that match the orthorhombic Rh 2 O 3 (II) phase with a density of 5.16 ± 0.03 g cm –3 . Upon unloading, the material transforms back to the α-corundum structure. Upon release to ambient pressure, densities are lower than predicted assuming isentropic release, indicating additional lattice expansion due to plastic work heating. Furthermore, using temperature values calculated from density measurements, we provide an estimate of alumina's strength on release from shock compression.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Demonstration of Better than Diesel Efficiency and Soot Emissions using Gasoline Compression Ignition in a Light Duty Engine with a Fuel Pressure Limitation

Increasing regulatory demand to reduce CO2 emissions has led to a focus on advanced combustion strategy development to improve overall engine efficiency. Gasoline compression ignition (GCI) has been demonstrated by others to have the potential to meet future CO2 regulations and emissions while achieving comparable to better efficiency than conventional diesel compression ignition (DCI). Soot and NOx emissions are also reduced significantly by using gasoline instead of diesel in compression ignition engines due to differences in composition, fuel properties, and reactivity. In comparison with diesel fuel, gasoline has a higher volatility and more resistance to autoignition, therefore, its longer ignition delay time will allow for better mixing of the air-fuel charge before combustion. In this study, a GCI combustion system has been tested in a Hyundai 2.2L engine as part of a US Department of Energy funded project. A double-injection strategy was tested from mid-to-high loads (5-20 bar BMEP) and for engine speeds in the range of 1200-3000 rpm. Up to 43.4% brake thermal efficiency was achieved using the GCI mode versus 41% using DCI mode. The GCI mode has demonstrated two distinct strategies that work at different load ranges, partially premixed compression ignition (PPCI) and mixing-controlled compression ignition (MCCI). Overall, this study shows that for similar engine-out NOx levels, GCI mode had higher brake thermal efficiency than DCI with lower fuel pressure and EGR required.

02 PETROLEUM↗
DOE OSTI2021

Changes in rock matrix compressibility during deep CO 2 storage

Geologic carbon storage projects aim to permanently trap large volumes of CO 2 in reservoir rock sealed with low permeability layers. As high-pressure supercritical or liquid CO 2 is injected, hydromechanical and chemical processes caused by the reaction between the rock and acidic mixture of brine and CO 2 are initiated. The compressibility of reservoir rock needs to be properly characterized in order to assess the deformation and stability of the host formations, and there are a number of factors to be considered, including the matrix structure, solid, pores, and fluid. Here this study triggers from a fundamental question whether CO 2 treatment affects the compressibility of the rock matrix and its dominant composing solid minerals. Three different reservoir representatives are selected: Berea sandstone for silica-rich rock, and Apulian limestone and Indiana limestone for calcite-rich rock. Quartz and calcite are the main composing minerals of the reservoir rock, and their crystals are separately examined. Experimental methods are introduced for high-pressure CO 2 treatment of water-saturated materials, and measurements of the unjacketed and solid compressibilities are conducted. No change in the solid compressibility of the sandstone and quartz after CO 2 treatment is observed, whereas it increases by 18–21% for the limestones and by 15% for calcite. The latter observation is inconsistent with the ultrasonic wave velocities measurements and is believed to be due to the local dissolution of the calcite crystal surface. Our results show that only the solid matrix of the limestones becomes more compressible after CO 2 treatment. Consequent microimaging and mercury intrusion porosimetry analyses allowed observations of dissolution and precipitation of calcite, and creation of new connected and non-connected pores. Finally, the changes in limestone solid compressibilities and pore structure could significantly affect the rock properties and behavior during and after CO 2 injection and should be accounted for in the reservoir models.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Development of a compressive failure model for carbon fiber composites and associated uncertainties.

An approach to increase the value of carbon fiber for wind turbines blades, and other compressive strength driven designs, is to identify pathways to increase its cost-specific compressive strength. A finite element model has been developed to evaluate the predictiveness of current finite element methods and to lay groundwork for future studies that focus on improving the cost-specific compressive strength. Parametric studies are conducted to understand which uncertainties in the model inputs have the greatest impact on compressive strength predictions. Furthermore, a statistical approach is also presented that enables the micromechanical model, which is deterministic, to efficiently account for statistical variability in the fiber misalignment present in composite materials; especially if the results from the hexagonal and square pack models are averaged. The model was found to agree well with experimental results for a Zoltek PX-35 pultrusion. The sensitivity studies suggest that the fiber packing and the interface shear strength have the greatest impact on compressive strength prediction for the fiber reinforced polymer studied here. Based on the performance of the modeling approach presented in this work, it is deemed sufficient for future work which will seek to identify carbon fiber composites with improved cost-specific compressive strength.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Shiga Toxin Induces Lipid Compression: A Mechanism for Generating Membrane Curvature

We report biomembranes are hard to compress laterally, and membrane area compressibility has not been associated with biological processes. Using X-ray surface scattering, we observed that bacterial Shiga toxin compresses lipid packing in a gel phase monolayer upon binding to its cellular receptor, the glycolipid Gb 3 . This toxin-induced reorganization of lipid packing reached beyond the immediate membrane patch that the protein was bound to, and linkers separating the Gb 3 carbohydrate and ceramide moieties modulated the toxin’s capacity to compress the membrane. Within a natural membrane, asymmetric compression of the toxin-bound leaflet could provide a mechanism to initiate narrow membrane bending, as observed upon toxin entry into cells. Such lipid compression and long-range membrane reorganization by glycolipid-binding proteins represent novel concepts in membrane biology that have direct implications for the construction of endocytic pits in clathrin-independent endocytosis.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Structural transitions and hysteresis in clump- and stripe-forming systems under dynamic compression

In using numerical simulations, we study the dynamical evolution of particles interacting via competing long-range repulsion and short-range attraction in two dimensions. The particles are compressed using a time-dependent quasi-one dimensional trough potential that controls the local density, causing the system to undergo a series of structural phase transitions from a low density clump lattice to stripes, voids, and a high density uniform state. The compression proceeds via slow elastic motion that is interrupted with avalanche-like bursts of activity as the system collapses to progressively higher densities via plastic rearrangements. The plastic events vary in magnitude from small rearrangements of particles, including the formation of quadrupole-like defects, to large-scale vorticity and structural phase transitions. In the dense uniform phase, the system compresses through row reduction transitions mediated by a disorder-order process. We also characterize the rearrangement events by measuring changes in the potential energy, the fraction of sixfold coordinated particles, the local density, and the velocity distribution. At high confinements, we find power law scaling of the velocity distribution during row reduction transitions. We observe hysteresis under a reversal of the compression when relatively few plastic rearrangements occur. The decompressing system exhibits distinct phase morphologies, and the phase transitions occur at lower compression forces as the system expands compared to when it is compressed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗