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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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NASA NTRSDate not supplied

The NASA Open Science Data Repository: Biomedical Data, Analysis Tools, and Informatic Collaborations

Increased biomedical risks and challenges associated with deep space missions require knowledge discovery, health countermeasures, and biomedical support capabilities. Maximally open-access and reusable data is needed by developers, scientists, and engineers to develop these systems. The NASA Open Science Data Repository (OSDR) is a maximally open access and FAIR database (ie., findable, accessible, interoperable, and reusable), and meets various scientific, technical, and operational needs. It offers users and submitters the ability to upload, download, search, share, analyze, cite, and visualize data across ‘omics, physiological, phenotypic, payload, hardware, behavioral, bioimaging, video, and environmental monitoring telemetry datasets. OSDR is an expanded database, based upon the successes of NASA GeneLab. OSDR has >460 studies with datasets covering model organisms to non-NASA human astronauts. There are ~12 datasets from the Inspiration 4 (I4) mission, spanning metagenomics, comprehensive metabolic panels, clonal hematopoiesis, spatial transcriptomics, proteomics, and cytokine panels. In the interest of data privacy, two I4 datasets with raw files relating to the epitranscriptome, and a new request feature is live in OSDR (with a backend review process established) developed from industry norms. OSDR is collecting and curating biomedical human data from a new sub-orbital research flight and is open to more space life science/biomedical submissions from the international and commercial sectors. OSDR also recently began a collaboration with the European Space Agency (ESA) to collect and curate >200 terabytes of human and model organism data. The OSDR submission portal is designed to ingest and curate ~25 ‘omics and ~50 physiological-phenotypic-imaging assay data types. Tools available for OSDR users include: 1) an Environmental Data Application to compare radiation, CO2, relative humidity, temperature, and other telemetry across missions and subjects, 2) the RadLab database, a collaboration between NASA, ESA, the German and Italian Space Agencies, and the Bulgarian Academy of Sciences, and 3) a Multi-study visualization tool which enables users to look across and combine ‘omics datasets. There are ~600 volunteer OSDR Analysis Working Group (AWG) members providing feedback on scientific data/metadata standards and collaborating to mine-reuse OSDR in research. OSDR/GeneLab has enabled ~60 publications reusing data as of October 2023.

space biology↗
NASA NTRS1974

Basic research and data analysis for the National Geodetic Satellite Program and for the Earth and Ocean Physics Application Program

Accomplishments in the continuing programs are reported. The data were obtained in support of the following broad objectives: (1) to provide a precise and accurate geometric description of the earth's surface; (2) to provide a precise and accurate mathematical description of the earth's gravitational field; and (3) to determine time variations of the geometry of the ocean surface, the solid earth, the gravity field, and other geophysical parameters.

Source record↗
NASA NTRS1975

Development of solar wind shock models with tensor plasma pressure for data analysis

The development of solar wind shock models with tensor plasma pressure and the comparison of some of the shock models with the satellite data from Pioneer 6 through Pioneer 9 are reported. Theoretically, difficulties were found in non-turbulent fluid shock models for tensor pressure plasmas. For microscopic shock theories nonlinear growth caused by plasma instabilities was frequently not clearly demonstrated to lead to the formation of a shock. As a result no clear choice for a shock model for the bow shock or interplanetary tensor pressure shocks emerged.

Abraham-Shrauner, B.↗
NASA NTRS1978

An investigation of wing buffeting response at subsonic and transonic speeds. Phase 1: F-111A flight data analysis. Volume 2: Plotted power spectra

Volume 2 of this three volume report is presented. This volume presents plotted variations of power spectral density data with frequency for each structural response item for each data sampled and analyzed during the course of the investigation. Some of the information contained in Volume 1 are repeated to allow the reader to identify the specific conditions appropriate to each plot presented and to interpret the data.

Benepe, D. B.↗
NASA NTRS2006

A Whale of a Tale: Creating Spacecraft Telemetry Data Analysis Products for the Deep Impact Mission

This paper describes some of the challenges and lessons learned from the Deep Impact (DI) Mission Ground Data System's (GDS) telemetry data processing and product generation tool, nicknamed 'Whale.' One of the challenges of any mission is to analyze testbed and operational telemetry data. Methods to retrieve this data to date have required spacecraft subsystem members to become experts in the use of a myriad of query and plot tools. As budgets shrink, and the GDS teams grow smaller, more of the burden to understand these tools falls on the users. The user base also varies from novice to expert, and requiring them to become GDS tool experts in addition to spacecraft domain experts is an undue burden. The "Whale" approach is to process all of the data for a given spacecraft test, and provide each subsystem with plots and data products 'automagically.'.

Deep Impact↗
NASA NTRS1975

Pyrotechnic shock measurement and data analysis requirements

An investigation is described into the laboratory measurement and analysis of pyrotechnic shock which was prompted at JPL when two separate facilities generated discrepant pyrotechnic shock data while testing Mariner Jupiter/Saturn 1977 spacecraft hardware. Both of the testing facilities were surveyed. The only difference noted was in the FM tape recorders used to record the data. One facility used a tape recorder operating at 60 in./sec with a frequency response of 20 kHz; the other used a tape recorder operating at 120 in./sec with a frequency response of 80 kHz. The accelerometers, cables, charge amplifiers, and mechanical setups were identical.

Albers, L.↗
NASA NTRS1974

Statistical theory and methodology for remote sensing data analysis

A model is developed for the evaluation of acreages (proportions) of different crop-types over a geographical area using a classification approach and methods for estimating the crop acreages are given. In estimating the acreages of a specific croptype such as wheat, it is suggested to treat the problem as a two-crop problem: wheat vs. nonwheat, since this simplifies the estimation problem considerably. The error analysis and the sample size problem is investigated for the two-crop approach. Certain numerical results for sample sizes are given for a JSC-ERTS-1 data example on wheat identification performance in Hill County, Montana and Burke County, North Dakota. Lastly, for a large area crop acreages inventory a sampling scheme is suggested for acquiring sample data and the problem of crop acreage estimation and the error analysis is discussed.

Odell, P. L.↗
NASA NTRS1991

Oceanographic data analysis with NASA's SEAPAK software

The paper presents a case study of the interannual variability of vertical Ekman transport (upwelling) observed in the North Atlantic during the CZCS data collection period in order to illustrate SEAPAK's ancillary data handling functions. The study begins at the entire basin-scale for the North Atlantic and proceeds to a regional scale where much of the observed upwelling variability occurs. The analysis utilizes a variety of output types, including images, horizontal contour plots, time series, cross sections, and vertical profiles, produced on the VAX directly or by commercially available PC software packages. The SEAPAK software can be used just as effectively for global or basin-scale studies as for regional studies.

Firestone, James K.↗
NASA NTRS1985

Participation in the Mars Data Analysis Program: Analysis of cloud forms in Viking and Mariner 9 images

The first systematic account of the climate of Mars, based upon observations was produced. Cloud data were used to determine spatially and temporally varying near-surface wind direction, relative wind speed, static stability, and humidity conditions on a global scale. Existing models of meteorological processes were critically reexamined in light of the data, and more stringent constraints were set on global processes. Several discoveries were made, including the large extent and seasonal variability of the Mars equatorial Hadley cell, the failure of high latitude winds to reverse direction in early northern spring, the change in meridional wind component in southern midautum, and the almost constant cloud cover in the northern hemisphere, during spring and summer primarily by condensate clouds and in fall and winter by condensates and dust. The implications of these observations are discussed.

Gierasch, P.↗
NASA NTRS1998

Data Analysis of a Space Experiment: Common Software Tackles Uncommon Task

Presented here are the software adaptations developed by laboratory scientists to process the space experiment data products from three experiments on two International Microgravity Laboratory Missions (IML-1 and IML-2). The challenge was to accommodate interacting with many types of hardware and software developed by both European Space Agency (ESA) and NASA aerospace contractors, where data formats were neither commercial nor familiar to scientists. Some of the data had been corrupted by bit shifting of byte boundaries. Least-significant/most-significant byte swapping also occurred as might be expected for the various hardware platforms involved. The data consisted of 20 GBytes per experiment of both numerical and image data. A significant percentage of the bytes were consumed in NASA formatting with extra layers of packetizing structure. It was provided in various pieces to the scientists on magnetic tapes, Syquest cartridges, DAT tapes, CD-ROMS, analog video tapes, and by network FIP. In this paper I will provide some science background and present the software processing used to make the data useful in the months after the missions.

Wilkinson, R. Allen↗
NASA NTRS2018

Improving NASA Earth Science Data and Information Access Through Natural Language Processing Based Data Analysis and Visualization

NASA: The Research Access initiative is part of the agency's framework for increasing public access to scientific publications and digital scientific data. The initiative follows the release of White House Office of Science and Technology Policy's (OSTP) memorandum "Increasing Access to the Results of Federally Funded Research," to ensure federally funded research is available to the public within one year of publication. NASA answered the mandate by creating an agency plan entitled "NASA Plan for Increasing Access to the Results of Scientific Research" and associated policy, NPD 2230.1, Research Data and Publication Access. Principles in NASA SMD Strategic Plan for Scientific Data and Computing: Continued free and open access to scientific data for any use. Improved ease of use and discoverability. Enhanced science applications and new use cases. Incorporates best practices and "state of the art" through partnerships. Earth Data and Systems are Evolving: Increasing archive and file sizes. More complicated data structures. More user-friendly and data services. What is the future direction?

Liu, Zhong↗
NASA NTRS1975

Pyrotechnic shock measurement and data analysis requirements

An investigation of laboratory measurement and analysis of pyrotechnic shock is described which was prompted when two separate facilities produced discrepant pyrotechnic-shock data while testing Mariner Jupiter/Saturn 1977 spacecraft hardware. Both testing facilities are thoroughly examined to find a possible cause for the discrepancies, and it is noted that one facility incorporated an FM tape recorder operating at 60 in./sec with a frequency response of 20 kHz while the other incorporated a tape recorder operating at 120 in./sec with a frequency response of 80 kHz. It is found that the discrepancies were a direct result of the inadequate recording frequency response of the tape recorders. Other factors involved in obtaining more accurate data are discussed.

Albers, L.↗
NASA NTRS2007

Upward Flame Propagation and Wire Insulation Flammability: 2006 Round Robin Data Analysis

This viewgraph document reviews test results from tests of different material used for wire insulation for flame propagation and flammability. The presentation focused on investigating data variability both within and between laboratories; evaluated the between-laboratory consistency through consistency statistic h, which indicates how one laboratory s cell average compares with averages from other labs; evaluated the within-laboratory consistency through the consistency statistic k, which is an indicator of how one laboratory s within-laboratory variability compares with the variability of other labs combined; and extreme results were tested to determine whether they resulted by chance or from nonrandom causes (human error, instrument calibration shift, non-adherence to procedures, etc.)

Hirsch, David B.↗
NASA NTRS2000

Mars Global Surveyor Ka-Band Frequency Data Analysis

The Mars Global Surveyor (MGS) spacecraft, launched on November 7, 1996, carries an experimental space-to-ground telecommunications link at Ka-band (32 GHz) along with the primary X-band (8.4 GHz) downlink. The signals are simultaneously transmitted from a 1.5-in diameter parabolic high gain antenna (HGA) on MGS and received by a beam-waveguide (BWG) R&D 34-meter antenna located in NASA's Goldstone Deep Space Network (DSN) complex near Barstow, California. The projected 5-dB link advantage of Ka-band relative to X-band was confirmed in previous reports using measurements of MGS signal strength data acquired during the first two years of the link experiment from December 1996 to December 1998. Analysis of X-band and Ka-band frequency data and difference frequency (f(sub x)-f(sub ka)/3.8) data will be presented here. On board the spacecraft, a low-power sample of the X-band downlink from the transponder is upconverted to 32 GHz, the Ka-band frequency, amplified to I-W using a Solid State Power Amplifier, and radiated from the dual X/Ka HGA. The X-band signal is amplified by one of two 25 W TWTAs. An upconverter first downconverts the 8.42 GHz X-band signal to 8 GHz and then multiplies using a X4 multiplier producing the 32 GHz Ka-band frequency. The frequency source selection is performed by an RF switch which can be commanded to select a VCO (Voltage Controlled Oscillator) or USO (Ultra-Stable Oscillator) reference. The Ka-band frequency can be either coherent with the X-band downlink reference or a hybrid combination of the USO and VCO derived frequencies. The data in this study were chosen such that the Ka-band signal is purely coherent with the X-band signal, that is the downconverter is driven by the same frequency source as the X-band downlink). The ground station used to acquire the data is DSS-13, a 34-meter BWG antenna which incorporates a series of mirrors inside beam waveguide tubes which guide the energy to a subterranean pedestal room, providing a stable environment for the feed and electronics equipment. A dichroic plate is used to reflect the X-band energy and pass the Ka-band energy to another mirror. The RF energy for each band is then focused onto a feed horn and low-noise amplifier package. After amplification and RF/IF downconversion, the IF signals are sent to the Experimental Tone Tracker (ETT), a digital phase-lock-loop receiver, which simultaneously tracks both X-band and Ka-band carrier signals. Once a signal is detected, the ETT outputs estimates of the SNR in a I -Hz bandwidth (Pc/No), baseband phase and frequency of the signals every I -sec. Between December 1996 and December 1998, the Ka-band and X-band signals from MGS were tracked on a regular basis using the ETT. The Ka-band downlink frequencies described here were referenced to the spacecraft's on-board USO which was also the X-band frequency reference (f(sub ka)= 3.8 f(sub x)). The ETT estimates of baseband phase at I -second sampled time tags were converted to sky frequency estimates. Frequency residuals were then generated for each band by removing a model frequency from each observable frequency at each time tag. The model included Doppler and other effects derived from spacecraft trajectory files obtained from the MGS Navigation Team. A simple troposphere correction was applied to the data. In addition to residuals, the USO frequencies emitted by the spacecraft were estimated. For several passes, the USO frequencies were determined from X-band data and from Ka-band data (referred to X-band by dividing by 3.8) and were found to be in good agreement. In addition, X-band USO frequency estimates from MGS Radio Science data acquired from operational DSN stations were available for comparison and were found to agree within the I Hz level. The remaining sub-Hertz differences were attributed to the different models and software algorithms used by MGS Radio Science and KaBLE-11. A summary of the results of a linear fit of the USO frequency versus time (day of year) is presented in Table I for an initial segment of passes.

Morabito, D.↗
NASA NTRS1977

Two-dimensional wind-tunnel tests of a NASA supercritical airfoil with various high-lift systems. Volume 1: Data analysis

High-lift systems for a NASA, 9.3%, method for calculating the viscous flow about two-dimensional multicomponent airfoils was evaluated by comparing its predictions with test data. High-lift systems derived from supercritical airfoils were compared in terms of performance to high-lift systems derived from conventional airfoils. The high-lift systems for the supercritical airfoil were designed to achieve maximum lift and consisted of: a single-slotted flap; a double-slotted flap and a leading-edge slat; and a triple-slotted flap and a leading-edge slat. Agreement between theoretical predictions and experimental results are also discussed.

Omar, E.↗
NASA NTRS1994

A data analysis assistant

This paper discusses the use of a domain-independent planner, COLLAGE, as a software assistant to Earth scientists working with remotely-sensed and ground based data sets. The planner can be viewed as an advisory agent that helps scientists select appropriate data and creates a suitable plan for data-processing that meets stated scientific requirements.

Lansky, Amy L.↗
NASA NTRS2016

UAS Integration in the NAS Project: Flight Test 3 Data Analysis of JADEM-Autoresolver Detect and Avoid System

The Unmanned Aircraft Systems Integration in the National Airspace System project, or UAS Integration in the NAS, aims to reduce technical barriers related to safety and operational challenges associated with enabling routine UAS access to the NAS. The UAS Integration in the NAS Project conducted a flight test activity, referred to as Flight Test 3 (FT3), involving several Detect-and-Avoid (DAA) research prototype systems between June 15, 2015 and August 12, 2015 at the Armstrong Flight Research Center (AFRC). This report documents the flight testing and analysis results for the NASA Ames-developed JADEM-Autoresolver DAA system, referred to as 'Autoresolver' herein. Four flight test days (June 17, 18, 22, and July 22) were dedicated to Autoresolver testing. The objectives of this test were as follows: 1. Validate CPA prediction accuracy and detect-and-avoid (DAA, formerly known as self-separation) alerting logic in realistic flight conditions. 2. Validate DAA trajectory model including maneuvers. 3. Evaluate TCAS/DAA interoperability. 4. Inform final Minimum Operating Performance Standards (MOPS). Flight test scenarios were designed to collect data to directly address the objectives 1-3. Objective 4, inform final MOPS, was a general objective applicable to the UAS in the NAS project as a whole, of which flight test is a subset. This report presents analysis results completed in support of the UAS in the NAS project FT3 data review conducted on October 20, 2015. Due to time constraints and, to a lesser extent, TCAS data collection issues, objective 3 was not evaluated in this analysis.

flight test↗