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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 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
NASA NTRS2005

Reducing costs of managing and accessing navigation and ancillary data by relying on the extensive capabilities of NASA's spice system

The SPICE system of navigation and ancillary data possesses a number of traits that make its use in modern space missions of all types highly cost efficient. The core of the system is a software library providing API interfaces for storing and retrieving such data as trajectories, orientations, time conversions, and instrument geometry parameters. Applications used at any stage of a mission life cycle can call SPICE APIs to access this data and compute geometric quantities required for observation planning, engineering assessment and science data analysis. SPICE is implemented in three different languages, supported on 20+ computer environments, and distributed with complete source code and documentation. It includes capabilities that are extensively tested by everyday use in many active projects and are applicable to all types of space missions - flyby, orbiters, observatories, landers and rovers. While a customer's initial SPICE adaptation for the first mission or experiment requires a modest effort, this initial effort pays off because adaptation for subsequent missions/experiments is just a small fraction of the initial investment, with the majority of tools based on SPICE requiring no or very minor changes.

ancillary data↗
NASA NTRS2015

Application of Data Cubes for Improving Detection of Water Cycle Extreme Events

As part of an ongoing NASA-funded project to remove a longstanding barrier to accessing NASA data (i.e., accessing archived time-step array data as point-time series), for the hydrology and other point-time series-oriented communities, "data cubes" are created from which time series files (aka "data rods") are generated on-the-fly and made available as Web services from the Goddard Earth Sciences Data and Information Services Center (GES DISC). Data cubes are data as archived rearranged into spatio-temporal matrices, which allow for easy access to the data, both spatially and temporally. A data cube is a specific case of the general optimal strategy of reorganizing data to match the desired means of access. The gain from such reorganization is greater the larger the data set. As a use case of our project, we are leveraging existing software to explore the application of the data cubes concept to machine learning, for the purpose of detecting water cycle extreme events, a specific case of anomaly detection, requiring time series data. We investigate the use of support vector machines (SVM) for anomaly classification. We show an example of detection of water cycle extreme events, using data from the Tropical Rainfall Measuring Mission (TRMM).

water cycle extreme events↗
NASA NTRS1990

A carrier sensed multiple access protocol for high data base rate ring networks

The results of the study of a simple but effective media access protocol for high data rate networks are presented. The protocol is based on the fact that at high data rates networks can contain multiple messages simultaneously over their span, and that in a ring, nodes used to detect the presence of a message arriving from the immediate upstream neighbor. When an incoming signal is detected, the node must either abort or truncate a message it is presently sending. Thus, the protocol with local carrier sensing and multiple access is designated CSMA/RN. The performance of CSMA/RN with TTattempt and truncate is studied using analytic and simulation models. Three performance factors, wait or access time, service time and response or end-to-end travel time are presented. The service time is basically a function of the network rate, it changes by a factor of 1 between no load and full load. Wait time, which is zero for no load, remains small for load factors up to 70 percent of full load. Response time, which adds travel time while on the network to wait and service time, is mainly a function of network length, especially for longer distance networks. Simulation results are shown for CSMA/RN where messages are removed at the destination. A wide range of local and metropolitan area network parameters including variations in message size, network length, and node count are studied. Finally, a scaling factor based upon the ratio of message to network length demonstrates that the results, and hence, the CSMA/RN protocol, are applicable to wide area networks.

Foudriat, E. C.↗
NASA NTRS2010

A Framework for Propagation of Uncertainties in the Kepler Data Analysis Pipeline

The Kepler space telescope is designed to detect Earth-like planets around Sun-like stars using transit photometry by simultaneously observing 100,000 stellar targets nearly continuously over a three and a half year period. The 96-megapixel focal plane consists of 42 charge-coupled devices (CCD) each containing two 1024 x 1100 pixel arrays. Cross-correlations between calibrated pixels are introduced by common calibrations performed on each CCD requiring downstream data products access to the calibrated pixel covariance matrix in order to properly estimate uncertainties. The prohibitively large covariance matrices corresponding to the ~75,000 calibrated pixels per CCD preclude calculating and storing the covariance in standard lock-step fashion. We present a novel framework used to implement standard propagation of uncertainties (POU) in the Kepler Science Operations Center (SOC) data processing pipeline. The POU framework captures the variance of the raw pixel data and the kernel of each subsequent calibration transformation allowing the full covariance matrix of any subset of calibrated pixels to be recalled on-the-fly at any step in the calibration process. Singular value decomposition (SVD) is used to compress and low-pass filter the raw uncertainty data as well as any data dependent kernels. The combination of POU framework and SVD compression provide downstream consumers of the calibrated pixel data access to the full covariance matrix of any subset of the calibrated pixels traceable to pixel level measurement uncertainties without having to store, retrieve and operate on prohibitively large covariance matrices. We describe the POU Framework and SVD compression scheme and its implementation in the Kepler SOC pipeline.

Clarke, Bruce D.↗
NASA NTRS2002

Transition Documentation on a Three-Element High-Lift Configuration at High Reynolds Numbers--Database

A 2-D (two dimensional) high-lift system experiment was conducted in August of 1996 in the Low Turbulence Pressure Tunnel at NASA Langley Research Center, Hampton, VA. The purpose of the experiment was to obtain transition measurements on a three element high-lift system for CFD (computational fluid dynamics) code validation studies. A transition database has been created using the data from this experiment. The present report details how the hot-film data and the related pressure data are organized in the database. Data processing codes to access the data in an efficient and reliable manner are described and limited examples are given on how to access the database and store acquired information.

Bertelrud, Arild↗
NASA NTRS1987

Data Bus Adapts to Changing Traffic Level

Access becomes timed when collisions threaten. Two-mode scheme used to grant terminals access to data bus. Causes bus to alternate between random accessibility and controlled accessibility to optimize performance and adapt to changing data-traffic conditions. Bus is part of 100-Mb/s optical-fiber packet data system.

Lew, Eugene↗
NASA NTRS2006

The Echoes of Earth Science

NASA s Earth Observing System Data and Information System (EOSDIS) acquires, archives, and manages data from all of NASA s Earth science satellites, for the benefit of the Space Agency and for the benefit of others, including local governments, first responders, the commercial remote sensing industry, teachers, museums, and the general public. EOSDIS is currently handling an extraordinary amount of NASA scientific data. To give an idea of the volume of information it receives, NASA s Terra Earth-observing satellite, just one of many NASA satellites sending down data, sends it hundreds of gigabytes a day, almost as much data as the Hubble Space Telescope acquires in an entire year, or about equal to the amount of information that could be found in hundreds of pickup trucks filled with books. To make EOSDIS data completely accessible to the Earth science community, NASA teamed up with private industry in 2000 to develop an Earth science "marketplace" registry that lets public users quickly drill down to the exact information they need. It also enables them to publish their research and resources alongside of NASA s research and resources. This registry is known as the Earth Observing System ClearingHOuse, or ECHO. The charter for this project focused on having an infrastructure completely independent from EOSDIS that would allow for more contributors and open up additional data access options. Accordingly, it is only fitting that the term ECHO is more than just an acronym; it represents the functionality of the system in that it can echo out and create interoperability among other systems, all while maturing with time as industry technologies and standards change and improve.

Source record↗
NASA NTRS2004

ThermoBuild: Online Method Made Available for Accessing NASA Glenn Thermodynamic Data

The new Web site program "ThermoBuild" allows users to easily access and use the NASA Glenn Thermodynamic Database of over 2000 solid, liquid, and gaseous species. A convenient periodic table allows users to "build" the molecules of interest and designate the temperature range over which thermodynamic functions are to be displayed. ThermoBuild also allows users to build custom databases for use with NASA's Chemical Equilibrium with Applications (CEA) program or other programs that require the NASA format for thermodynamic properties. The NASA Glenn Research Center has long been a leader in the compilation and dissemination of up-to-date thermodynamic data, primarily for use with the NASA CEA program, but increasingly for use with other computer programs.

McBride, Bonnie↗
NASA NTRS1980

LAMMR world data base documentation support and demonstrations

The primary purpose of the World Surface Map is to provide the LAMMR subsystem with world surface type classifications that are used to set up LAMMR LEVEL II process control. This data base will be accessed solely by the LAMMR subsystem. The SCATT and ALT subsystems will access the data base indirectly through the T sub b (Brightness Temperature) Data Bank, where the surface types were updated from a priori to current classification, and where the surface types were organized on an orbital subtrack basis. The single most important factor in the design of the World Surface Maps is the ease of access to the information while the complexity of generating these maps is of lesser importance because their generation is a one-time, off-line process. The World Surface Map provides storage of information with a resolution of 7 km necessary to set flags concerning the earth's features with a different set of maps for each month of the year.

Chin, R.↗
NASA NTRS2008

Using NASA's Giovanni Web Portal to Access and Visualize Satellite-based Earth Science Data in the Classroom

One of the biggest obstacles for the average Earth science student today is locating and obtaining satellite-based remote sensing data sets in a format that is accessible and optimal for their data analysis needs. At the Goddard Earth Sciences Data and Information Services Center (GES-DISC) alone, on the order of hundreds of Terabytes of data are available for distribution to scientists, students and the general public. The single biggest and time-consuming hurdle for most students when they begin their study of the various datasets is how to slog through this mountain of data to arrive at a properly sub-setted and manageable data set to answer their science question(s). The GES DISC provides a number of tools for data access and visualization, including the Google-like Mirador search engine and the powerful GES-DISC Interactive Online Visualization ANd aNalysis Infrastructure (Giovanni) web interface.

Lloyd, Steven↗
NASA NTRS2017

Limiting Data Friction by Reducing Data Download Using Spatiotemporally Aligned Data Organization Through STARE

Current data processing practice limits the volume and variety of relevant geoscience data that can practically be applied to important problems. File archives in centralized data centers are the principal means by which Earth Science data are accessed. This approach, however, requires laborious search, retrieval, and eventual customization/adaptation for the data to be used. Such fractionation makes it even more difficult to share outcomes, i.e. research artifacts and data products, hampering reusability and repeatability, since end users generally have their own research agenda and preferences as well as scarce resources. Thus, while finding and downloading data files from central data centers are already costly for end users working in their own field, using data products from other disciplines rapidly becomes prohibitive. This curtails scientific productivity, limits avenues of study, and endangers quality and reproducibility. The Spatio-Temporal Adaptive Resolution Encoding (STARE) is a unifying scheme that facilitates the indexing, access, and fusion of diverse Earth Science data. STARE implements an innovative encoding of geo-spatiotemporal information, originally developed for aligning datasets with diverse spatiotemporal characteristics in an array database. The spatial component of STARE recursively quadfurcates a root polyhedron, producing a hierarchical scheme for addressing geographic locations and regions. The temporal component of STARE uses conventional date-time units as an indexing hierarchy. The additional encoding of spatial and temporal resolution information in STARE enables comparisons and conditional selections across diverse datasets. Moreover, spatiotemporal set-operations, e.g. union and intersection, are mapped to efficient integer operations with STARE. Applied to existing data models (point, grid, spacecraft swath) and corresponding granules, STARE indexes provide a streamlined description usable as geo-spatiotemporal metadata. When coupled with large scale, distributed hardware and software, STARE-based data access reduces pre-analysis data preparation costs by offering a convenient means to align different datasets spatiotemporally without specialized effort in parallel computing or distributed data management.

Kuo, Kwo-Sen↗
DOE OSTI2025

Barge Site - Avian Radar System / Derived Data

This is a combined data set of 67,410 bird/bat tracks from an avian radar system deployed on a research barge (MERLIN True3D, DeTect, Panama City, Florida, USA) and concurrent wind measurements from two scanning lidars (WindCube v2.1, Vaisala, Vantaa, Finland, and Halo XR+, Halo Photonics, Lannion, France). The research barge (16.5 m x 61 m) was deployed as part of the Wind Forecast Improvement Project (WFIP-3) off the northeast coast of the United States south of Massachusetts (40.9 deg N, 70.79 deg W). This data set comprises 5 weeks of data between August 27th 2024 and September 27th 2024. Radar data were provided by DeTect and Lidar data were accessed through the Wind Data Hub (wfip3/barg.WINDPROF.z01.a0) The data have been filtered and sorted into two size groups ("big" and "small") based on a clustering approach. See Snortland, A., Clerc, J., Hein, C., & Cotter, E. (2025). Wind as Driver of Bird and Bat Abundance, Flight Direction, Altitude, and Speed on the North Atlantic Shelf. arXiv preprint arXiv:2511.14983 for complete details. Data are provided in 2 files: "Birds" and "Birds_hourly" Birds: This file contains information about each of the 67,410 flying animal tracks detected by the radar during the data collection period, including parameters measured by the radar and wind information interpolated from the lidar wind measurements. We note that the raw radar dataset contained 301,618 tracks; tracks in this processed dataset were filtered based on the requirements described in Snortland et al. (2025). Birds_hourly: This file contains timeseries of the number of tracks detected per hour over the course of the data collection period, including wind conditions and sun position for each hour. These data were used for generalized additive modeling in Snortland et al. (2025).

17 WIND ENERGY↗
NASA NTRS1981

The role of pilots

The need for detailed specifications is addressed. Candidates for standardization include hardware interfaces, communication protocols, and data exchange services. Atmosphere, Ocean, and Resource pilot programs, utilization of current techniques and technologies in the use and exchange of data and to facilitate access to data are discussed. Pilot objectives aim to: (1) demonstrate the use of advanced technologies, (2) provide a test bed environment for data handling technique evaluation, (3) evolve requirements and capabilities, and (4) document validated methodologies as standards and guidelines for data systems planning use. A user oriented catalog system, data set management, a network communication system, and a user interface are also discussed.

Gary, J. P.↗
NASA NTRS1984

Data communication between data terminal equipment and the JPL administrative data base management system

Approaches to enabling an installed base of mixed data terminal equipment to access a data base management system designed to work with a specific terminal are discussed. The approach taken by the Jet Propulsion Laboratory is described. Background information on the Jet Propulsion Laboratory (JPL), its organization and a description of the Administrative Data Base Management System is included.

Iverson, R. W.↗
NASA NTRSDate not supplied

NASA’s Human Data Repositories: An In Depth Look at the New Data Request Process

As NASA transitions its focus to travel back to the moon and on to new destinations, the need to ensure the capture, analysis, and application of research and medical data is of greater urgency than at any other previous time. In this era of limited resources and challenging schedules, the Human Research Program (HRP), based at NASA’s Johnson Space Center (JSC), recognizes the need to extract the greatest possible amount of information from the data already captured. To this end, the HRP Chief Scientist Office (CSO), HRP Program Planning and Control (PP&C) Office, and the Space Medicine Operations Division have been working together to make reuse of both research data and medical monitoring data more accessible to the user community through the Life Science Data Archive (LSDA) and the Lifetime Surveillance of Astronaut Health (LSAH) Repositories. The task of both LSDA and LSAH repositories is to acquire, preserve, and distribute retrospective research (LSDA) and medical (LSAH) data and information both within the NASA community and to the science community at large, for knowledge discovery, retrospective analysis, and planning of future research studies. An additional goal is to encourage collaboration with non-NASA institutions also faced with enhancing human performance in extreme environments. In September 2022, the LSDA website and its contents transitioned to a new NASA Life Sciences Portal (https://nlsp.nasa.gov/explore/lsdahome). This site continues to feature publicly releasable information such as non-attributable datasets, experiment descriptions (from Project Mercury to ISS, as well as from multiple flight analog missions), descriptions of medical monitoring data, and LSAH newsletters (1992 - 2022). The website also provides an updated portal to request additional research and medical data not accessible from the public website. This presentation will provide an in-depth look at the new system as it relates to finding and requesting retrospective data. We will also detail processes from making a request to delivering data for different types of data requests (i.e., attributable, or non-attributable). This includes descriptions of various approval boards, what information and actions the requestor is responsible for, and key milestones in making data available for reuse.

D. M. Thomas↗
NASA NTRS2002

A model for live mission data systems using the OAIS reference model

Space sciences are confronted with overwhelming volume of data. The data rates are increasing, the granularity of registered observations is continuously refining, and computer technology allows producing terabytes of images and catalogs. The inexpensive emerging storage technologies, combined with the availability of high-speed communications will offer the infrastructure for extremely large data repositories to be accessible on-line. Mission data will be quickly accessible almost immediately after it has been collected from space observations. On-line science will demand for new tools and technologies for data access, data analysis, and data discovery. These trends will enhance the archival operational concepts mainly related to the long-term information preservation, placing an equally important emphasis on rapid data production, and dissemination to consumers.

mission data systems srchive system OAIS data mana↗
DOE OSTI2026

MINERvA s Open Data Product: A First for Neutrino Data Preservation

Access to information on neutrino nucleus interactions is critical to the success of all neutrino oscillation experiments. MINERvA's rich dataset covers a range of energies and nuclei unique amongst experiments, and as such is critical to the community in building the important shared knowledge needed to unravel the mysteries of the neutrino. In particular, its dataset provides the greatest statistical coverage in in the range of neutrino energies pertinent for DUNE until DUNE's near detector begins operation. Historically, such significant datasets in neutrino physics have been preserved primarily through their published results. While meaningful and useful, this limits the ability to explore the data to its fullest extent as new perspectives continue to form. MINERvA has undertaken a major effort to break this trend and preserve its data in a format to be as analyzable as possible from outside the collaboration. This has culminated in the officially-released MINERvA Open Data Product for the community to take advantage of and utilize. Maintaining direct access to the dataset in an analyzable form will allow new insights to continue to be extracted indefinitely. This talk will cover the contents of this product, the information included (and excluded), the tools provided to utilize the product effectively, the support MINERvA intends to provide in its use, and some lessons learned through the process.

Last, David [Rochester U.] (ORCID:0000000245147183↗
DOE OSTI2024

Enriching OpenStreetMap network data for transportation applications: Insights into the impact of urban congestion on accessibility

OpenStreetMap (OSM) data is a valuable open-source resource for various transportation, traffic, and planning applications. However, OSM network data lack operating traffic speed information, which is critical for transport planning and operations. Addressing this shortcoming, this study leverages commercial vendor data (to serve as ground truth) with exogenous, open-source variables characterizing local transport infrastructure, land use, and demographic information to predict average congested traffic speeds on OSM networks. Three machine-learning models were tested and estimated for OSM links with and without speed limit information in the Denver metropolitan region. Among these, XGBoost performed best, with mean absolute errors of 3.27 and 3.62 mph for links with and without speed limits, respectively. The developed models accurately predicted traffic speeds for different hours and days of the week compared to ground truth data. Using these predicted speeds, drive accessibility scores were computed for the Denver region for different time periods using the Mobility Energy Productivity (MEP) metric to understand the impact of congestion on energy-efficient accessibility. Results show that congestion-adjusted drive accessibility can be significantly lower compared to accessibility calculated using free flow speeds. Specifically, weekday evening hours saw a 42 % drop in accessibility due to reduced speeds, particularly around downtown Denver. Across the Denver metro region, approximately half as many opportunities and jobs are accessible in under 20 min by car during the evening peak period relative to free flow conditions. These findings underscore the importance of using congestion-adjusted operating speeds rather than speed limits in accessibility calculations, as reliance on speed limits can substantially overestimate energy-efficient drive accessibility in large, car-centric cities susceptible to significant congestion. In conclusion, the methodology presented here could further enrich OSM network data, making them useful for an even broader range of transportation applications.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗