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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS1980

Interactive Astronomical Data Analysis Facility

A description is given of the Interactive Astronomical Data Analysis Facility (IADAF) which performs interactive analysis of astronomical data for resident and visiting scientists. The facilities include a Grant measuring engine, a PDS 1010A microdensitometer, a COMTAL image display system and a PDP 11/40 computer system. Both hardware and software systems are examined, including a description of thirteen overlay programs. Some uses of the IADAF are indicated.

Klinglesmith, D. A., III↗
NASA NTRS1997

Accelerometer Data Analysis and Presentation Techniques

The NASA Lewis Research Center's Principal Investigator Microgravity Services project analyzes Orbital Acceleration Research Experiment and Space Acceleration Measurement System data for principal investigators of microgravity experiments. Principal investigators need a thorough understanding of data analysis techniques so that they can request appropriate analyses to best interpret accelerometer data. Accelerometer data sampling and filtering is introduced along with the related topics of resolution and aliasing. Specific information about the Orbital Acceleration Research Experiment and Space Acceleration Measurement System data sampling and filtering is given. Time domain data analysis techniques are discussed and example environment interpretations are made using plots of acceleration versus time, interval average acceleration versus time, interval root-mean-square acceleration versus time, trimmean acceleration versus time, quasi-steady three dimensional histograms, and prediction of quasi-steady levels at different locations. An introduction to Fourier transform theory and windowing is provided along with specific analysis techniques and data interpretations. The frequency domain analyses discussed are power spectral density versus frequency, cumulative root-mean-square acceleration versus frequency, root-mean-square acceleration versus frequency, one-third octave band root-mean-square acceleration versus frequency, and power spectral density versus frequency versus time (spectrogram). Instructions for accessing NASA Lewis Research Center accelerometer data and related information using the internet are provided.

Rogers, Melissa J. B.↗
NASA NTRSDate not supplied

Improvements in VLBI Data Analysis for Advanced in Geodesy

I will provide an overview of advances in VLBI data analysis implemented at NASA GSFC. That include the use of B-splines for modeling non-linear station position evolution, the use of all non-tidal mass loadings in data reduction, the use of slant a priori path delays from the output of numerical weather models, the use of B-splines for evaluation of the Earth orientation parameters as a continuous function, the use of elevation-dependent weighting, processing both 24 hr and 1 hr experiments in a single least square solutions and other innovations. I will show how this changes in data analysis affect space geodesy results, such as estimation of station positions, Earth orientation parameters, and source coordinates.

Leonid Petrov↗
NASA NTRS1988

Rocketdyne automated dynamics data analysis and management system

An automated dynamics data analysis and management systems implemented on a DEC VAX minicomputer cluster is described. Multichannel acquisition, Fast Fourier Transformation analysis, and an online database have significantly improved the analysis of wideband transducer responses from Space Shuttle Main Engine testing. Leakage error correction to recover sinusoid amplitudes and correct for frequency slewing is described. The phase errors caused by FM recorder/playback head misalignment are automatically measured and used to correct the data. Data compression methods are described and compared. The system hardware is described. Applications using the data base are introduced, including software for power spectral density, instantaneous time history, amplitude histogram, fatigue analysis, and rotordynamics expert system analysis.

Tarn, Robert B.↗
NASA NTRS2008

Upgrades to Electronic Speckle Interferometer (ESPI) Operation and Data Analysis at NASA's Goddard Space Flight Center

The authors report operational upgrades and streamlined data analysis of a commissioned electronic speckle interferometer (ESPI) in a permanent in-house facility at NASA's Goddard Space Flight Center. Our ESPI was commercially purchased for use by the James Webb Space Telescope (JWST) development team. We have quantified and reduced systematic error sources, improved the software operability with a user-friendly graphic interface, developed an instrument simulator, streamlined data analysis for long-duration testing, and implemented a turn-key approach to speckle interferometry. We also summarize results from a test of the JWST support structure (previously published), and present new results from several pieces of test hardware at various environmental conditions.

Connelly, Joseph↗
NASA NTRS1974

Model wall and recovery temperature effects on experimental heat transfer data analysis

Basic analytical procedures are used to illustrate, both qualitatively and quantitatively, the relative impact upon heat transfer data analysis of certain factors which may affect the accuracy of experimental heat transfer data. Inaccurate knowledge of adiabatic wall conditions results in a corresponding inaccuracy in the measured heat transfer coefficient. The magnitude of the resulting error is extreme for data obtained at wall temperatures approaching the adiabatic condition. High model wall temperatures and wall temperature gradients affect the level and distribution of heat transfer to an experimental model. The significance of each of these factors is examined and its impact upon heat transfer data analysis is assessed.

Throckmorton, D. A.↗
NASA NTRS1994

Data Analysis with Graphical Models: Software Tools

Probabilistic graphical models (directed and undirected Markov fields, and combined in chain graphs) are used widely in expert systems, image processing and other areas as a framework for representing and reasoning with probabilities. They come with corresponding algorithms for performing probabilistic inference. This paper discusses an extension to these models by Spiegelhalter and Gilks, plates, used to graphically model the notion of a sample. This offers a graphical specification language for representing data analysis problems. When combined with general methods for statistical inference, this also offers a unifying framework for prototyping and/or generating data analysis algorithms from graphical specifications. This paper outlines the framework and then presents some basic tools for the task: a graphical version of the Pitman-Koopman Theorem for the exponential family, problem decomposition, and the calculation of exact Bayes factors. Other tools already developed, such as automatic differentiation, Gibbs sampling, and use of the EM algorithm, make this a broad basis for the generation of data analysis software.

Buntine, Wray L.↗
NASA NTRS1968

Post-landing tracking data analysis

Surveyor 7 post-landing tracking data analysis, and determining selenocentric location of probe and geocentric locations of tracking stations

Winn, F. B.↗
NASA NTRS1969

OPLE data analysis

Omega position location equipment /OPLE/ experiment data analysis, obtaining quantitative measure of statistical performance of system

Obryant, R.↗
DOE OSTI2022

Open Reproducible Electron Microscopy Data Analysis

Electron microscopy (EM) is a cornerstone technique in the materials and biological sciences capable of imaging structures at nano- to atomic-scale resolution. Advances in technologies mean that one acquires datasets at increasing data rates and sizes. These advancements present enormous opportunities for researchers to understand complex systems. However, processing the resulting large-scale, complex data in a reproducible and shareable way is a real challenge for researchers. The building, managing, and maintaining complex workflows in a reproducible manner requires extensive knowledge in several areas outside the researchers’ core skill sets, such as software engineering, data science, and high-performance computing (HPC). Our work demonstrates an innovative approach to solving these problems, enabling reproducible EM data analysis through container encapsulated pipelines. Using modern container technologies, we encapsulate processing elements and connect them using shared memory. We expose user-friendly, advanced algorithms and tools to allow end users to utilize without expert programming skills. The platform enables reproducible, scalable, shareable pipelines for the analysis and visualization of EM data. Focusing on interoperability, we leverage the DOE and other agencies’ existing investments to provide a powerful software platform for EM data analysis.

Harris, Christopher↗
NASA NTRS2010

Stirling Convertor Extended Operation Testing and Data Analysis at Glenn Research Center

Extended operation of Stirling convertors is essential to the development of radioisotope power systems and their potential use for longduration missions. To document the reliability of the convertors, regular monitoring and analysis of the extended operation data is particularly valuable, allowing us to better understand and quantify long-life characteristics of the convertors. Furthermore, investigation and comparison of the extended operation data to baseline performance data provides an opportunity to understand system behavior should any off-nominal performance occur. Glenn Research Center (GRC) has tested 16 Stirling convertors under 24-hr unattended extended operation, including four that have operated in a thermal vacuum environment and two that are operating in the Advanced Stirling Radioisotope Generator Engineering Unit. Ten of the sixteen convertors are the Advanced Stirling Convertors (ASC) developed by Sunpower, Inc. with GRC. These are highly efficient (conversion efficiency of up to 38 percent for the ASC-1), low-mass convertors that have evolved through technologically progressive convertor builds. Six convertors at GRC are Technology Demonstration Convertors from Infinia Corporation. They have achieved greater than 27 percent conversion efficiency and have accumulated over 185,000 of the total 265,000 hr of extended operation at GRC. This paper presents the extended operation testing and data analysis of free-piston Stirling convertors at NASA GRC as well as how these tests have contributed to the Stirling convertor s progression toward flight.

Cornell, Peggy A.↗
NASA NTRS2012

Calibration and Data Analysis of the MC-130 Air Balance

Design, calibration, calibration analysis, and intended use of the MC-130 air balance are discussed. The MC-130 balance is an 8.0 inch diameter force balance that has two separate internal air flow systems and one external bellows system. The manual calibration of the balance consisted of a total of 1854 data points with both unpressurized and pressurized air flowing through the balance. A subset of 1160 data points was chosen for the calibration data analysis. The regression analysis of the subset was performed using two fundamentally different analysis approaches. First, the data analysis was performed using a recently developed extension of the Iterative Method. This approach fits gage outputs as a function of both applied balance loads and bellows pressures while still allowing the application of the iteration scheme that is used with the Iterative Method. Then, for comparison, the axial force was also analyzed using the Non-Iterative Method. This alternate approach directly fits loads as a function of measured gage outputs and bellows pressures and does not require a load iteration. The regression models used by both the extended Iterative and Non-Iterative Method were constructed such that they met a set of widely accepted statistical quality requirements. These requirements lead to reliable regression models and prevent overfitting of data because they ensure that no hidden near-linear dependencies between regression model terms exist and that only statistically significant terms are included. Finally, a comparison of the axial force residuals was performed. Overall, axial force estimates obtained from both methods show excellent agreement as the differences of the standard deviation of the axial force residuals are on the order of 0.001 % of the axial force capacity.

Booth, Dennis↗
NASA NTRS1987

Gravity data analysis

Work on three different efforts related to gravity data analysis is discussed. The reduction of raw Doppler data from the Apollo 15 subsatellite to produce acceleration profiles as a function of latitude, longitude and altitude; an investigation related to fitting long arcs of Pioneer Venus Orbiter tracking data; and a study of gravity/topography ratios which were found to have a linear trend with longitude are discussed.

Sjogren, William L.↗
NASA NTRS1976

Data analysis and noise prediction for the QF-1B experimental fan stage

The results of a fan noise data analysis and prediction effort using experimental data obtained from tests on the QF-1B research fan are described. Surface pressure measurements were made with flush mounted sensors installed on selected rotor blades and stator vanes and noise measurements were made by microphones located at the far field. Power spectral density analysis, time history studies, and calculation of coherence functions were made. The emphasis of these studies was on the characteristics of tones in the spectra. The amplitude behavior of spectral tones was found to have a large, often predominant, random component, suggesting that turbulent processes play an important role in the generation of tonal as well as broadband noise. Inputs from the data analysis were used in a prediction method which assumes that acoustic dipoles, produced by unsteady blade and van forces, are the important source of fan noise.

Bliss, D. B.↗
DOE OSTI2020

Interlaboratory Reproducibility of Contour Method Data Analysis and Residual Stress Calculation

While the contour method for residual stress assessment has developed rapidly, no published study documents its interlaboratory reproducibility. Objective: Here we report an initial reproducibility experiment focused on contour method data analysis and residual stress calculation. The experiment uses surface topography data from a physical process simulation of elastic-plastic beam bending. The simulation provides surface topography, for input to the contour method data analysis, as well as a known residual stress field with 130 MPa peak magnitude. Additionally, to increase realism, noise and specific artifacts are added to the topography data. A group of participants received the topography data (without the known residual stress), independently analyzed the data, and submitted results as a two-dimensional residual stress field. Analysis of submissions provides a group average residual stress field and the spatial distribution of reproducibility standard deviation. The group average residual stress agrees with the known stress in magnitude and spatial trend. The reproducibility standard deviation ranges from 2 to 54 MPa over the measurement plane, with an average of 5.4 MPa. Reproducibility standard deviation is smaller in the cross-section interior (≤ 5 MPa), modest near local extrema in the stress field (5 to 10 MPa), and larger near the cross-section boundaries (10 to 30 MPa). Overall, the largest values of reproducibility standard deviation (up to 54 MPa) occur in limited areas where artifacts had been added to the topography data; while some participants identified and removed these artifacts, some did not, leading to systematic differences that elevated the standard deviation.

42 ENGINEERING↗
NASA NTRS2011

Hurricane Data Analysis Tool

In order to facilitate Earth science data access, the NASA Goddard Earth Sciences Data Information Services Center (GES DISC) has developed a web prototype, the Hurricane Data Analysis Tool (HDAT; URL: http://disc.gsfc.nasa.gov/HDAT), to allow users to conduct online visualization and analysis of several remote sensing and model datasets for educational activities and studies of tropical cyclones and other weather phenomena. With a web browser and few mouse clicks, users can have a full access to terabytes of data and generate 2-D or time-series plots and animation without downloading any software and data. HDAT includes data from the NASA Tropical Rainfall Measuring Mission (TRMM), the NASA Quick Scatterometer(QuikSCAT) and NECP Reanalysis, and the NCEP/CPC half-hourly, 4-km Global (60 N - 60 S) IR Dataset. The GES DISC archives TRMM data. The daily global rainfall product derived from the 3-hourly multi-satellite precipitation product (3B42 V6) is available in HDAT. The TRMM Microwave Imager (TMI) sea surface temperature from the Remote Sensing Systems is in HDAT as well. The NASA QuikSCAT ocean surface wind and the NCEP Reanalysis provide ocean surface and atmospheric conditions, respectively. The global merged IR product, also known as, the NCEP/CPC half-hourly, 4-km Global (60 N -60 S) IR Dataset, is one of TRMM ancillary datasets. They are globally-merged pixel-resolution IR brightness temperature data (equivalent blackbody temperatures), merged from all available geostationary satellites (GOES-8/10, METEOSAT-7/5 & GMS). The GES DISC has collected over 10 years of the data beginning from February of 2000. This high temporal resolution (every 30 minutes) dataset not only provides additional background information to TRMM and other satellite missions, but also allows observing a wide range of meteorological phenomena from space, such as, hurricanes, typhoons, tropical cyclones, mesoscale convection system, etc. Basic functions include selection of area of interest and time, single imagery, overlay of two different products, animation,a time skip capability and different image size outputs. Users can save an animation as a file (animated gif) and import it in other presentation software, such as, Microsoft PowerPoint. Since the tool can directly access the real data, more features and functionality can be added in the future.

Liu, Zhong↗
NASA NTRS1985

Development of the variational SEASAT data analysis technique

Surface winds are closely associated with the surface pressure gradient. The variational SEASAT data analysis technique was designed to improve the sea level pressure analysis in the data sparse areas. The SEASAT-derived surface wind data were compared with observations from the Joint Air Sea Interaction Experiment (JASIN) and it was found that the satellite-derived sea surface wind has an accuracy of up to + or - 2 m/s in speed and + or - 20 deg in direction. These numbers are considered characteristic of the retrieved SEASAT wind field. By combining the densely spaced SEASAT-derived wind data with the sparsely distributed sea-level pressure observation via a variational adjustment technique subject to some appropriate physical constraint(s), an improvement in the sea-level pressure analysis is expected. It is demonstrated that a simple marine boundary layer scheme in conjunction with a variational adjustment technique can be developed to help improve the sea-level pressure analysis by the SEASAT-derived wind of a limited-area domain in the ocean.

Sasaki, Y. K.↗
DOE OSTI2025

BatteryPro: A Python Toolkit for Battery Data Analysis and Machine Learning Predictions

Analyzing battery test data for research & development can be time-consuming since battery tests often run on the order of months to years, generating large volumes of data. BatteryPro is a comprehensive Python package and software designed to facilitate advanced analysis and performance predictions for battery test data. Developed for battery researchers, it supports data types from widely used battery testing instruments, including MACCOR and Biologic cycling systems. The software provides a variety of tools for extracting and plotting key battery parameters such as time, voltage, capacity, current, and pressure. In addition to its extensive data analysis capabilities, BatteryPro features a dedicated machine learning module that employs a Bayesian Gaussian Mixture Model (GMM) to predict battery performance and degradation. Users can generate synthetic capacity fade data, calculate fade metrics, and leverage predictive models to forecast long-term battery behavior. The software's graphical user interface (GUI) enhances usability, allowing researchers to upload, merge, and analyze multiple data files with full customizability. The GUI also supports machine learning predictions, enabling users to fit models and make predictions based on selected data and parameters. BatteryPro is built using QtDesigner, scikit-learn, matplotlib, and pandas, ensuring a high level of customization, flexibility, and accuracy in battery data analysis. This tool aims to empower researchers with the ability to perform detailed battery analysis and make informed predictions, ultimately advancing the field of battery research.

25 - ENERGY STORAGE↗