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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 991 records · Page 55
All sourcesNASA NTRSDOE OSTI
NASA NTRS2022

Application of Compressive Sensing for Gravitational Microlensing Events

Compressive sensing is a novel mathematical technique for simultaneous data acquisition and compression. This technique is particularly apt for time-series photometric measurements. In this work we apply compressive sensing to time-series photometric measurements specifically obtained due to gravitational microlensing events. We show through simulation modelling the error sensitivity for detecting microlensing event parameters. Particularly, we show the relation of the amount of error and its impact on the microlensing parameters of interest. We derive statistical error bounds to apply those as a baseline for analyzing the effectiveness of compressive sensing application. Our results conclude that for single and binary microlensing events we can obtain error less than 1% over a 3-pixel radius of the center of the microlensing star by using 25% Nyquist rate measurements.

Compressive Sensing↗
DOE OSTI2023

Spatiotemporally Adaptive Compression for Scientific Dataset with Feature Preservation – A Case Study on Simulation Data with Extreme Climate Events Analysis

Scientific discoveries are increasingly constrained by limited storage space and I/O capacities. For time-series simulations and experiments, their data often need to be decimated over timesteps to accommodate storage and I/O limitations. In this paper, we propose a technique that addresses storage costs while improving post-analysis accuracy through spatiotemporal adaptive, error-controlled lossy compression. We investigate the trade-off between data precision and temporal output rates, revealing that reducing data precision and increasing timestep frequency lead to more accurate analysis outcomes. Additionally, we integrate spatiotemporal feature detection with data compression and demonstrate that performing adaptive error-bounded compression in higher dimensional space enables greater compression ratios, leveraging the error propagation theory of a transformation-based compressor. To evaluate our approach, we conduct experiments using the well-known E3SM climate simulation code and apply our method to compress variables used for cyclone tracking. Our results show a significant reduction in storage size while enhancing the quality of cyclone tracking analysis, both quantitatively and qualitatively, in comparison to the prevalent timestep decimation approach. Compared to three state-of-the-art lossy compressors lacking feature preservation capabilities, our adaptive compression framework improves perfectly matched cases in TC tracking by 26.4-51.3% at medium compression ratios and by 77.3-571.1% at large compression ratios, with a merely 5–11% computational overhead.

Gong, Qian↗
NASA NTRS1985

ISCCP cloud algorithm intercomparison

Research related to the International Satellite Cloud Climatology Project (ISCCP) began with a pilot study initiated in late 1981 to evaluate currently available cloud analysis algorithms. Other objectives of this study are related to a test of the effects of data volume compression schemes and the design of the operational algorithms for ISCCP. The present paper summarizes the pilot study by focusing on the most fundamental step of any cloud algorithm, that of cloud detection. An outline is provided of the objectives and limitations of the pilot study, and a description is given of the criteria used to design the operational analysis algorithm. Attention is given to the pilot study data set, a cloud detection intercomparison, a cloud analysis, and ISCCP cloud algorithm design.

Rossow, W. B.↗
DOE OSTI2023

Direct prediction of inelastic neutron scattering spectra from the crystal structure*

Abstract Inelastic neutron scattering (INS) is a powerful technique to study vibrational dynamics of materials with several unique advantages. However, analysis and interpretation of INS spectra often require advanced modeling that needs specialized computing resources and relevant expertise. This difficulty is compounded by the limited experimental resources available to perform INS measurements. In this work, we develop a machine-learning based predictive framework which is capable of directly predicting both one-dimensional INS spectra and two-dimensional INS spectra with additional momentum resolution. By integrating symmetry-aware neural networks with autoencoders, and using a large scale synthetic INS database, high-dimensional spectral data are compressed into a latent-space representation, and a high-quality spectra prediction is achieved by using only atomic coordinates as input. Our work offers an efficient approach to predict complex multi-dimensional neutron spectra directly from simple input; it allows for improved efficiency in using the limited INS measurement resources, and sheds light on building structure-property relationships in a variety of on-the-fly experimental data analysis scenarios.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Cascade of transitions in twisted and non-twisted graphene layers within the van Hove scenario

Abstract Motivated by measurements of compressibility and STM spectra in twisted bilayer graphene, we analyze the pattern of symmetry breaking for itinerant fermions near a van Hove singularity. Making use of an approximate SU(4) symmetry of the Landau functional, we show that the structure of the spin/isospin order parameter changes with increasing filling via a cascade of transitions. We compute the feedback from different spin/isospin orders on fermions and argue that each order splits the initially 4-fold degenerate van Hove peak in a particular fashion, consistent with the STM data and compressibility measurements, providing a unified interpretation of the cascade of transitions in twisted bilayer graphene. Our results follow from a generic analysis of an SU(4)-symmetric Landau functional and are valid beyond a specific underlying fermionic model. We argue that an analogous van Hove scenario explains the cascade of phase transitions in non-twisted Bernal bilayer and rhombohedral trilayer graphene.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

Mesoscale Numerical Characterization of Kevlar and Carbon–Kevlar Hybrid Plain-Woven Fabric Compression Behavior

A mesoscale finite element model (FEM) of the plain-woven fabric representative elementary volume (REV/unit cell) is developed. The developed FEM is used to predict the nonlinear compaction behavior of monolithic and intraply hybrid fabric made of high-strength carbon and Kevlar fibers. For geometrical modeling of the fabric REV, TexGen, an open-source geometrical modeling software (developed at Nottingham University), is utilized, and for mechanical characterization, FE simulation tool Abaqus{sup ®} is used. Geometrical nonlinearity of the fabric, including periodic boundary conditions and yarn interactions, is incorporated in the REV FE model. Material nonlinearity caused by transversely isotropic behavior of fibrous yarns is implemented through the user material subroutine form in FE simulation along with local orientation assigned to each yarn in the REV. Material properties of fibers are extracted from the literature and supplier data. The compression behavior of monolithic Kevlar and hybrid carbon–Kevlar (carbon warp and Kevlar weft yarns, C–K) fabric is predicted using the proposed FE model. FEM-predicted results were found to have good agreement with the experimentally obtained ones. Results depict that C–K hybrid fabrics have improved compression strength. Hybridization effect is governed by yarns mutual interaction, yarn area at crossovers, and transverse in-plane properties of the interyarn hybridized fabric. The proposed FE model can be used to predict the mechanical behavior of woven fabrics with different weaving patterns, unit cell geometry, material properties, and loading conditions.

36 MATERIALS SCIENCE↗
NASA NTRS1998

Self-Similar Compressible Free Vortices

Lie group methods are used to find both exact and numerical similarity solutions for compressible perturbations to all incompressible, two-dimensional, axisymmetric vortex reference flow. The reference flow vorticity satisfies an eigenvalue problem for which the solutions are a set of two-dimensional, self-similar, incompressible vortices. These solutions are augmented by deriving a conserved quantity for each eigenvalue, and identifying a Lie group which leaves the reference flow equations invariant. The partial differential equations governing the compressible perturbations to these reference flows are also invariant under the action of the same group. The similarity variables found with this group are used to determine the decay rates of the velocities and thermodynamic variables in the self-similar flows, and to reduce the governing partial differential equations to a set of ordinary differential equations. The ODE's are solved analytically and numerically for a Taylor vortex reference flow, and numerically for an Oseen vortex reference flow. The solutions are used to examine the dependencies of the temperature, density, entropy, dissipation and radial velocity on the Prandtl number. Also, experimental data on compressible free vortex flow are compared to the analytical results, the evolution of vortices from initial states which are not self-similar is discussed, and the energy transfer in a slightly-compressible vortex is considered.

vonEllenrieder, Karl↗
NASA NTRS1994

Galileo mission planning for Low Gain Antenna based operations

The Galileo mission operations concept is undergoing substantial redesign, necessitated by the deployment failure of the High Gain Antenna, while the spacecraft is on its way to Jupiter. The new design applies state-of-the-art technology and processes to increase the telemetry rate available through the Low Gain Antenna and to increase the information density of the telemetry. This paper describes the mission planning process being developed as part of this redesign. Principal topics include a brief description of the new mission concept and anticipated science return (these have been covered more extensively in earlier papers), identification of key drivers on the mission planning process, a description of the process and its implementation schedule, a discussion of the application of automated mission planning tool to the process, and a status report on mission planning work to date. Galileo enhancements include extensive reprogramming of on-board computers and substantial hard ware and software upgrades for the Deep Space Network (DSN). The principal mode of operation will be onboard recording of science data followed by extended playback periods. A variety of techniques will be used to compress and edit the data both before recording and during playback. A highly-compressed real-time science data stream will also be important. The telemetry rate will be increased using advanced coding techniques and advanced receivers. Galileo mission planning for orbital operations now involves partitioning of several scarce resources. Particularly difficult are division of the telemetry among the many users (eleven instruments, radio science, engineering monitoring, and navigation) and allocation of space on the tape recorder at each of the ten satellite encounters. The planning process is complicated by uncertainty in forecast performance of the DSN modifications and the non-deterministic nature of the new data compression schemes. Key mission planning steps include quantifying resource or capabilities to be allocated, prioritizing science observations and estimating resource needs for each, working inter-and intra-orbit trades of these resources among the Project elements, and planning real-time science activity. The first major mission planning activity, a high level, orbit-by-orbit allocation of resources among science objectives, has already been completed; and results are illustrated in the paper. To make efficient use of limited resources, Galileo mission planning will rely on automated mission planning tools capable of dealing with interactions among time-varying downlink capability, real-time science and engineering data transmission, and playback of recorded data. A new generic mission planning tool is being adapted for this purpose.

Gershman, R.↗
NASA NTRS1992

Fast Vector-Quantizing Data Compressor

Proposed encoding digital electronic data-processing system compresses 7-Mb/s input stream of data into 1-Mb/s output stream. Intended to reduce flow of data from orbiting synthetic-aperture-radar (SAR) system to rate low enough for transmission to ground. Features include reliability, light weight, and low power. Proves advantageous in such terrestrial applications as compression of speech and of video signals.

Chang, Chi-Yung↗
NASA NTRS1989

A defect stream function, law of the wall/wake method for compressible turbulent boundary layers

The application of the defect stream function to the solution of the two-dimensional, compressible boundary layer is examined. A law of the wall/law of the wake formulation for the inner part of the boundary layer is presented which greatly simplifies the computational task near the wall and eliminates the need for an eddy viscosity model in this region. The eddy viscosity model in the outer region is arbitrary. The modified Crocco temperature-velocity relationship is used as a simplification of the differential energy equation. Formulations for both equilibrium and nonequilibrium boundary layers are presented including a constrained zero-order form which significantly reduces the computational workload while retaining the significant physics of the flow. A formulation for primitive variables is also presented. Results are given for the constrained zero-order and second-order equilibrium formulations and are compared with experimental data. A compressible wake function valid near the wall has been developed from the present results.

Barnwell, Richard W.↗
NASA NTRS1994

A Motion-Compensating Image-Compression Scheme

Chrominance used (in addition to luminance) in estimating motion. Variable-rate digital coding scheme for compression of color-video-image data designed to deliver pictures of good quality at moderate compressed-data rate of 1 to 2 bits per pixel, or of fair quality at rate less than 1 bit per pixel. Scheme, in principle, implemented by use of commercially available application-specific integrated circuits. Incorporates elements of some prior coding schemes, including motion compensation (MC) and discrete cosine transform (DCT).

Wong, Carol↗
DOE OSTI2020

ROOT I/O compression improvements for HEP analysis

We overview recent changes in the ROOT I/O system, increasing performance and enhancing it and improving its interaction with other data analysis ecosystems. Both the newly introduced compression algorithms, the much faster bulk I/O data path, and a few additional techniques have the potential to significantly to improve experiment's software performance. The need for efficient lossless data compression has grown significantly as the amount of HEP data collected, transmitted, and stored has dramatically increased during the LHC era. While compression reduces storage space and, potentially, I/O bandwidth usage, it should not be applied blindly: there are significant trade-offs between the increased CPU cost for reading and writing files and the reduce storage space.

Shadura, Oksana↗
DOE OSTI2021

Poisson’s ratio of eTPU molded bead foams in compression via in situ synchrotron X-ray microtomography

In situ synchrotron X-ray microtomography was used to characterize the bulk deformation behavior by computing the Poisson's ratio of expanded thermoplastic polyurethane (eTPU) molded bead foams used in footwear midsole during compression. Quantitative data on morphological characteristics were obtained using an iterative image processing workflow. Image correlation on the 4D datasets using DVC was performed to calculate the volumetric and axial strain to estimate the Poisson ratio. Strain maps from DVC showed the influence of variability in ligament thickness distribution on the global mechanical behavior exhibited which dominated the response seen in these bead foams. Lastly, our results showed a strong correlation between Poisson ratio and distribution of ligament thickness in foams.

36 MATERIALS SCIENCE↗
NASA NTRS2011

Review and Implementation of the Emerging CCSDS Recommended Standard for Multispectral and Hyperspectral Lossless Image Coding

A new standard for image coding is being developed by the MHDC working group of the CCSDS, targeting onboard compression of multi- and hyper-spectral imagery captured by aircraft and satellites. The proposed standard is based on the "Fast Lossless" adaptive linear predictive compressor, and is adapted to better overcome issues of onboard scenarios. In this paper, we present a review of the state of the art in this field, and provide an experimental comparison of the coding performance of the emerging standard in relation to other state-of-the-art coding techniques. Our own independent implementation of the MHDC Recommended Standard, as well as of some of the other techniques, has been used to provide extensive results over the vast corpus of test images from the CCSDS-MHDC.

hyperspectral images↗
DOE OSTI2018

A comparative study of multi-material data structures for computational physics applications

The data structures used to represent the multi-material state of a computational physics application can have a significant impact on its performance. Here, we look at efficient data structures for applications where there may be many materials overall, but where most computational cells contain only one or a few of these materials. We develop simple performance models for selecting possible data structures and programming patterns. We verify the analytic performance models with a small test program of the representative cases. We discuss the impact of these techniques and analysis for multi-material physics applications, which are also applicable to a wide range of sparse computational data structures.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

The Complicated Link Between Material Properties and Microfracture Density for an Underground Explosion in Granite

Geophysical techniques are often implemented as quick and inexpensive ways to locate and characterize fractures in the subsurface, which is important for a number of geoscience fields. Seismic velocities are the most widely used proxies for identification of fractures, but the correlation is not always well-defined. In this study we present material property data: unconfined compressive strength (UCS), bulk density (ρ), Young's modulus (E), Poisson's ratio (ν), P wave velocity (V p ), and S wave velocity (V s ), in conjunction with microfracture densities measured on samples of granite collected before and after underground chemical explosions. Results indicate the relationship between fractures and material properties is complex, even in this single-lithology environment. We interpret that this complexity arises from varying fracture mechanisms (e.g. dilation-inducing fractures vs compression-inducing fractures) in different parts of the core, due to differences in stress conditions. Additional complexity may result from chemical interactions between the fresh fractures and the fluids in the area. Water content appears to have a significant, if not dominant, role in the unconfined compressive strength (UCS) of the samples. We suggest caution when using elastic property measurements as a proxy for fracturing in areas of explosion-induced damage, or in other areas where a variety of mechanisms induce fracturing.

58 GEOSCIENCES↗
DOE OSTI2023

Cosmological constraints from the Subaru Hyper Suprime-Cam year 1 shear catalogue lensing convergence probability distribution function

Here we utilize the probability distribution function (PDF) of normalized convergence maps reconstructed from the Subaru Hyper Suprime-Cam (HSC) year 1 shear catalogue, in combination with the power spectrum, to measure the matter clustering amplitude S 8 = σ 8 $\sqrt {Ω_{m}/0.3}$. The large-scale structure’s statistical properties are incompletely described by the traditional two-point statistics, motivating our investigation of the PDF—a complementary higher-order statistic. By defining the PDF over the standard-deviation-normalized convergence map, we are able to isolate the non-Gaussian information. We use tailored simulations to compress the data vector and construct a likelihood approximation. We mitigate the impact of survey and astrophysical systematics with cuts on smoothing scales, redshift bins, and data vectors. We find S 8 = $0.860^{+0.066}_{–0.109}$ from the PDF alone and S 8 = 0.798$^{+0.029}_{–0.042}$ from the combination of the PDF and power spectrum (68% confidential level (CL)). The PDF improves the power-spectrum-only constraint by about 10%.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Pressure-temperature equation of state of Al 2 ⁢O 3 up to 14 Mbar and 40 kK

Sapphire (Al 2 ⁢O 3 ), known for its remarkable incompressibility at ambient conditions, plays a pivotal role in both static and dynamic compression research. Accurately characterizing its equation of state (EoS) is essential for these applications. Here, we present a complete Hugoniot of Al 2 ⁢ O 3 as locus of experimentally assessed, high-precision, pressure, density and temperature states up to 14 Mbar and 43 kK. The Hugoniot is established with single shock experiments using magnetically launched hyper velocity flyers on the Z Accelerator at Sandia National Laboratories. We explore principal Hugoniot states at very high shock 𝑇 and 𝑝 in the solid phase, tracking the solid-liquid boundary and culminating at 2.4-fold compression, where data provides a direct constraint on the liquid phase. Corresponding shock release data probe thermodynamic states complementary to the Hugoniot and place additional constraints on tabular EoS models. Our findings indicate a significant deviation from existing tabular EoS models for Al 2 ⁢ O 3 dictating a comprehensive overhaul. We develop two advanced EoSs for Al 2 ⁢ O 3 the SESAME 97412 model, featuring an extensive phase diagram that includes three solid phases and the liquid phase, and the updated LEOS 2200m2 model. EoS development is assisted with Quantum Molecular Dynamics simulations. Our experimental data allows for stringent testing of our EoSs. Both models accurately capture the Hugoniot of Al 2 ⁢O 3 up to the highest pressures and temperatures. Rigorous experimental determination of extreme pressures and temperatures, paired with sophisticated models, advances the frontier of EoS development beyond 1 terapascal.

Kalita, Patricia [Sandia National Laboratories (SN↗