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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 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

XRTD: An X-Windows based, real-time radiometric display and analysis system

XRTD is a graphical user interface (GUI) based tool for monitoring real time radiometric spacecraft data. The tool is designed to allow the navigation analyst to both view and analyze the characteristics of Doppler and ranging data. This capability is critical if ground personnel wish to verify the correct performance of ongoing maneuvers. The raw tracking data is transferred from Deep Space Network (DSN) computers to a local workstation, where the predicted value for the observable is subtracted from the actual observed value to create a residual. The tool then allows the navigation analyst to rescale and replot the data using simple GUI techniques. The navigator may then perform a number of data analysis and modeling techniques on the resulting residuals to allow for the real time characterization of spacecraft events. These techniques include the modeling of maneuvers, the compression and differencing of data, and Fast Fourier transforms of the data. This tool has shortened the amount of time required for initial characterization of spacecraft maneuvers from several hours to a few minutes.

Pollmeier, Vincent M.↗
NASA NTRS1979

Computer image processing and recognition

A systematic introduction to the concepts and techniques of computer image processing and recognition is presented. Consideration is given to such topics as image formation and perception; computer representation of images; image enhancement and restoration; reconstruction from projections; digital television, encoding, and data compression; scene understanding; scene matching and recognition; and processing techniques for linear systems.

Hall, E. L.↗
NASA NTRS1974

Conical isogrid adapter structural test results. Appendix C: Cylindrical isogrid structures

Analysis techniques and data for evaluating the load carrying capabilities of cylindrical isogrid structures subjected to compression and body bending loads are presented. Structural tests were conducted on a 120-inch diameter by 37-inch long cylindrical adapter. Photographs and drawings of the flanged isogrid adapter structure are included. The subjects considered are: (1) summary of the test data resulting from structural analysis, (2) techniques for predicting local and general instability, (3) a method for predicting extended local instability, (4) the effects of basic parameter and constant variations in extended local stability analysis, and (5) evaluation of effective skin width and compression buckling of skin panels on the basis of test data.

Source record↗
NASA NTRS2015

Performance of a Discrete Wavelet Transform for Compressing Plasma Count Data and its Application to the Fast Plasma Investigation on NASA's Magnetospheric Multiscale Mission

Plasma measurements in space are becoming increasingly faster, higher resolution, and distributed over multiple instruments. As raw data generation rates can exceed available data transfer bandwidth, data compression is becoming a critical design component. Data compression has been a staple of imaging instruments for years, but only recently have plasma measurement designers become interested in high performance data compression. Missions will often use a simple lossless compression technique yielding compression ratios of approximately 2:1, however future missions may require compression ratios upwards of 10:1. This study aims to explore how a Discrete Wavelet Transform combined with a Bit Plane Encoder (DWT/BPE), implemented via a CCSDS standard, can be used effectively to compress count information common to plasma measurements to high compression ratios while maintaining little or no compression error. The compression ASIC used for the Fast Plasma Investigation (FPI) on board the Magnetospheric Multiscale mission (MMS) is used for this study. Plasma count data from multiple sources is examined: resampled data from previous missions, randomly generated data from distribution functions, and simulations of expected regimes. These are run through the compression routines with various parameters to yield the greatest possible compression ratio while maintaining little or no error, the latter indicates that fully lossless compression is obtained. Finally, recommendations are made for future missions as to what can be achieved when compressing plasma count data and how best to do so.

Particles↗
NASA NTRS1987

The Radar Ocean-Wave Spectrometer

The scanning-beam Radar Ocean-Wave Spectrometer (ROWS) technique is described. The derivation of a spectrum for the reflectivity modulation as a function of range is examined. The usefulness of the ROWS technique was initially validated using aircraft data obtained in 1978 with the GSFC Ku-band pulse-compression radar; additional examples of aircraft data which verify the effectiveness of the ROWS technique are presented. The development of a ROWS mode for Spectrasat is discussed. Consideration is given to the incidence angle, twin beam option for cross-section roll-off and wind vector determination, rotation rate, antenna and footprint dimensions, integration time, sphericity effects, and a processor configuration. A design for the ROWS-mode time-domain processor on Spectrasat is proposed. The performance of the system is evaluated, and it is determined that the system performs well.

Jackson, Frederick C.↗
DOE OSTI2023

Data compression and inference in cosmology with self-supervised machine learning

ABSTRACT The influx of massive amounts of data from current and upcoming cosmological surveys necessitates compression schemes that can efficiently summarize the data with minimal loss of information. We introduce a method that leverages the paradigm of self-supervised machine learning in a novel manner to construct representative summaries of massive data sets using simulation-based augmentations. Deploying the method on hydrodynamical cosmological simulations, we show that it can deliver highly informative summaries, which can be used for a variety of downstream tasks, including precise and accurate parameter inference. We demonstrate how this paradigm can be used to construct summary representations that are insensitive to prescribed systematic effects, such as the influence of baryonic physics. Our results indicate that self-supervised machine learning techniques offer a promising new approach for compression of cosmological data as well as its analysis.

Astronomy & Astrophysics↗
NASA NTRS1975

Solution of the three-dimensional compressible, laminar, and turbulent boundary-layer equations with comparisons to experimental data

A technique for solving three-dimensional boundary-layer flows is presented. The governing equations are transformed to obtain a nondimensional form and a similarity-type transform is defined for the normal coordinate and velocity. The resulting equation is solved in an iterative mode using a finite difference technique suggested by Dwyer (1968). A simple mean field turbulence model is discussed and numerical data obtained in a test case are compared with experimental data.-

Harris, J. E.↗
DOE OSTI2025

An analysis of parameter compression and Full-Modeling techniques with Velocileptors for DESI 2024 and beyond

In anticipation of forthcoming data releases of current and future spectroscopic surveys, we present the validation tests and analysis of systematic effects within velocileptors modeling pipeline when fitting mock data from the AbacusSummit N-body simulations. We compare the constraints obtained from parameter compression methods to the direct fitting (Full-Modeling) approaches of modeling the galaxy power spectra, and show that the ShapeFit extension to the traditional template method is consistent with the Full-Modeling method within the standard ΛCDM parameter space. We show the dependence on scale cuts when fitting the different redshift bins using the ShapeFit and Full-Modeling methods. We test the ability to jointly fit data from multiple redshift bins as well as joint analysis of the pre-reconstruction power spectrum with the post-reconstruction BAO correlation function signal. We further demonstrate the behavior of the model when opening up the parameter space beyond ΛCDM and also when combining likelihoods with external datasets, namely the Planck CMB priors. Finally, we describe different parametrization options for the galaxy bias, counterterm, and stochastic parameters, and employ the halo model in order to physically motivate suitable priors that are necessary to ensure the stability of the perturbation theory.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1977

Skylab S-193 radar altimeter experiment analyses and results

The design of optimum filtering procedures for geoid recovery is discussed. Statistical error bounds are obtained for pointing angle estimates using average waveform data. A correlation of tracking loop bandwidth with magnitude of pointing error is established. The impact of ocean currents and precipitation on the received power are shown to be measurable effects. For large sea state conditions, measurements of sigma 0 deg indicate a distinct saturation level of about 8 dB. Near-nadir less than 15 deg values of sigma 0 deg are also presented and compared with theoretical models. Examination of Great Salt Lake Desert scattering data leads to rejection of a previously hypothesized specularly reflecting surface. Pulse-to-pulse correlation results are in agreement with quasi-monochromatic optics theoretical predictions and indicate a means for estimating direction of pointing error. Pulse compression techniques for and results of estimating significant waveheight from waveform data are presented and are also shown to be in good agreement with surface truth data. A number of results pertaining to system performance are presented.

Brown, G. S.↗
DOE OSTI2022

An Algorithmic and Software Pipeline for Very Large Scale Scientific Data Compression with Error Guarantees

Efficient data compression is becoming increasingly critical for storing scientific data because many scientific applications produce vast amounts of data. This paper presents an end-to-end algorithmic and software pipeline for data compression that guarantees both error bounds on primary data (PD) and derived data, known as Quantities of Interest (QoI).We demonstrate the effectiveness of the pipeline by compressing fusion data generated by a large-scale fusion code, XGC, which produces tens of petabytes of data in a single day. We demonstrate that the compression is conducted by setting aside computational resources known as staging nodes, and does not impact the simulation performance. For efficient parallel I/O, the pipeline uses ADIOS2, which many codes such as XGC already use for their parallel I/O. We show that our approach can compress the data by two orders of magnitude while guaranteeing high accuracy on both the PD and the QoIs. Further, the amount of resources required by compression is a few percent of the resources required by simulation while ensuring that the compression time for each stage is less than the corresponding simulation time.This pipeline consists of three main steps. The first step decomposes the data using domain decomposition into small subdomains. Each subdomain is then compressed independently to achieve a high level of parallelism. The second step uses existing techniques that guarantee error bounds on the primary data for each subdomain. The third step uses a post-processing optimization technique based on Lagrange multipliers to reduce the QoI errors for data corresponding to each subdomain. The Lagrange multipliers generated can be further quantized or truncated to increase the compression level. All of the above characteristics of our approach make it highly practical to apply on-the-fly compression while guaranteeing errors on QoIs that are critical to the scientists.

Banerjee, Tania↗
NASA NTRS1976

Turbulence measurements in a transonic boundary layer and free-shear flow using laser velocimetry and hot-wire anemometry techniques

Quantitative measurements of the turbulence fluctuations in velocity and mass flux have been obtained in Mach 0.6 and 0.8 turbulent boundary layer and free-shear layer flows by laser velocimetry and hot-wire anemometry techniques. To evaluate the effects of compressibility, these transonic data are compared to available incompressible and supersonic results. Based on some simplifying assumptions, estimates of the rms density fluctuations are made for which error bounds are given. In addition to these fluctuation data, the compressible mean velocity data obtained with the laser velocimeter are presented and compared to pitot tube results. The investigation was conducted in the Ames 6- by 6-Foot Supersonic Wind Tunnel at free-stream Mach numbers of 0.6 and 0.8 for a unit Reynolds number of about 10,000,000 per meter.

Johnson, D. A.↗
NASA NTRS1979

Block adaptive rate controlled image data compression

A block adaptive rate controlled (BARC) image data compression algorithm is described. It is noted that in the algorithm's principal rate controlled mode, image lines can be coded at selected rates by combining practical universal noiseless coding techniques with block adaptive adjustments in linear quantization. Compression of any source data at chosen rates of 3.0 bits/sample and above can be expected to yield visual image quality with imperceptible degradation. Exact reconstruction will be obtained if the one-dimensional difference entropy is below the selected compression rate. It is noted that the compressor can also be operated as a floating rate noiseless coder by simply not altering the input data quantization. Here, the universal noiseless coder ensures that the code rate is always close to the entropy. Application of BARC image data compression to the Galileo orbiter mission of Jupiter is considered.

Rice, R. F.↗
NASA NTRS1987

Spectral feature design for data compression in high dimensional multispectral data

Data transmission loads of high dimensional remote sensor systems can be greatly reduced by applying generalized Karhunen-Loeve transform as a feature design technique. Two spectral feature design approaches based upon the generalized K-L transform are developed to compress information effectively. Six sets of field data from Kansas and North Dakota on three different dates each are used to test the methods. Spatially, temporally and spatially/temporally combined data sets are formed in this paper to test the robustness property of the schemes. The probability of correct classification using Landsat MSS, Thematic Mapper bands and the proposed bands are found and compared. The comparison shows that the results are improved by the proposed methods, and they appear to be satisfactorily robust. The overall data compression ratio in this paper is about 100/16, i.e., about 6 to 1 with no loss in classification accuracy.

Chen, C.-C. Thomas↗
DOE OSTI2024

Framework of compressive sensing and data compression for 4D-STEM

Four-dimensional Scanning Transmission Electron Microscopy (4D-STEM) is a powerful technique for high-resolution and high-precision materials characterization at multiple length scales, including the characterization of beam-sensitive materials. However, the field of view of 4D-STEM is relatively small, which in absence of live processing is limited by the data size required for storage. Furthermore, the rectilinear scan approach currently employed in 4D-STEM places a resolution- and signal-dependent dose limit for the study of beam sensitive materials. Improving 4D-STEM data and dose efficiency, by keeping the data size manageable while limiting the amount of electron dose, is thus critical for broader applications. Here we introduce a general method for reconstructing 4D-STEM data with subsampling in both real and reciprocal spaces at high fidelity. The approach is first tested on the subsampled datasets created from a full 4D-STEM dataset, and then demonstrated experimentally using random scan in real-space. The same reconstruction algorithm can also be used for compression of 4D-STEM datasets, leading to a large reduction (100 times or more) in data size, while retaining the fine features of 4D-STEM imaging, for crystalline samples.

4D-STEM↗
NASA NTRS1991

Burst-Compression And -Expansion For TDMA Communication

Burst-compression and -expansion technique enables interconnection of users transmitting and receiving data at rates asynchronous with respect to clocks within ground terminals of satellite-switched, time-division-multiple-access (TDMA) communication network. Matrix switch aboard satellite routes bursts of data from source users received on uplink antennas to downlink antennas illuminating ground areas containing destination users. TDMA ground terminal compresses streams of data from source users into rapid bursts for transmission and reexpands bursts of received data into slower streams of data for delivery to destination users. Greater flexibility in interconnecting widely dispersed users achieved by use of hopping beams.

Budinger, James M.↗
DOE OSTI2024

Accurate Ultrasonic Thickness Measurement for Arbitrary Time-Variant Thermal Profile

Ultrasonic thickness measurement of mechanical structures is one of the most popular and commonly used nondestructive methods for various kinds of process control and corrosion monitoring. With ultrasonic propagation speed being temperature-dependent, the thickness measurement can be performed reliably only when the thermal profile is completely known. Most conventional techniques assume the temperature of the test structure is uniform and at room temperature across its thickness. Such assumptions may lead to large errors in the thickness measurement, especially when there are significant temperature variations across the thickness. State-of-the-art techniques use external temperature measurements or implement iterative methods to compensate for the unknown thermal profiles. However, such techniques produce unsatisfactory results when the heat distribution is complex or varies rapidly with time. In this work, we propose a two-sensors technique, using both compressive and shear excitations, with a non-iterative rapid data processing method for accurate thickness measurement under arbitrary time-variant thermal profile. The independent behavior of shear and compressive waves is used to formulate a real-time thickness estimation technique. The developed technique is experimentally validated on a steel plate with fixed acoustic sensors. Test results show that the error in thickness estimation can be reduced by up to 98% compared to conventional thickness gauging methods.

36 MATERIALS SCIENCE↗
NASA NTRS1989

Context dependent prediction and category encoding for DPCM image compression

Efficient compression of image data requires the understanding of the noise characteristics of sensors as well as the redundancy expected in imagery. Herein, the techniques of Differential Pulse Code Modulation (DPCM) are reviewed and modified for information-preserving data compression. The modifications include: mapping from intensity to an equal variance space; context dependent one and two dimensional predictors; rationale for nonlinear DPCM encoding based upon an image quality model; context dependent variable length encoding of 2x2 data blocks; and feedback control for constant output rate systems. Examples are presented at compression rates between 1.3 and 2.8 bits per pixel. The need for larger block sizes, 2D context dependent predictors, and the hope for sub-bits-per-pixel compression which maintains spacial resolution (information preserving) are discussed.

Beaudet, Paul R.↗