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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 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
NASA NTRS1972

Development of analysis techniques for remote sensing of vegetation resources

Various data handling and analysis techniques are summarized for evaluation of ERTS-A and supporting high flight imagery. These evaluations are concerned with remote sensors applied to wildland and agricultural vegetation resource inventory problems. Monitoring California's annual grassland, automatic texture analysis, agricultural ground data collection techniques, and spectral measurements are included.

Draeger, W. C.↗
DOE OSTI2025

Data as a Key Resource in Catalysis: A Community Account

The deployment of artificial intelligence (AI) is transforming the scientific fields central to interdisciplinary catalysis research. By enabling more effective use of data, AI (including simpler machine learning and data science tools) holds great promise for accelerating discoveries. However, progress has so far been modest, largely due to the lack of standardized, machine-readable, and openly shared catalysis data. This perspective, accounting for community insights emerging at conferences, analyses the underlying reasons for these challenges and proposes solutions to a future whereFAIR data management becomes an integral part of research in catalysis. In the short-term, we deem that mandatory FAIR data depositing prior to scientific publications along with consensualized top-down guidelines on data sharing powered by ease-to-use tools can make the necessary step change happen to catalyse data as key resource in our community.

36 - MATERIALS SCIENCE↗
NASA NTRS1975

Data collection system: Earth Resources Technology Satellite-1

Subjects covered at the meeting concerned results on the overall data collection system including sensors, interface hardware, power supplies, environmental enclosures, data transmission, processing and distribution, maintenance and integration in resources management systems.

Cooper, S.↗
NASA NTRS1972

The Nasa earth resources spectral information system: A data compilation, first supplement

The NASA Earth Resources Spectral Information System and the information contained therein are described. It is intended to be used as a supplement to the NASA Earth Resources Spectral Information System: A Data Compilation, N72-28366. This supplement includes approximately 500 rock and mineral, 100 soil, and 30 vegetation bidirectional and directional reflectance, transmittance, emittance, and degree-of-polarization curves in the optical region from 0.2 to 22.0 microns. The data have been categorized by subject and each curve plotted on a single graph. For some rocks and minerals, all curves of the same type, differing only in particle size, have been plotted on one grid as a composite plot. Each graph, composite or single, is fully titled to indicate curve source and is indexed by subject to facilitate user retrieval.

Leeman, V.↗
NASA NTRS1973

The NASA earth resources spectral information system: A data compilation, second supplement

The NASA Earth Resources Spectral Information System (ERSIS) and the information contained therein are described. It is intended for use as a second supplement to the NASA Earth Resources Spectral Information System: A Data Compilation, NASA CR-31650-24-T, May 1971. The current supplement includes approximately 100 rock and mineral, and 375 vegetation directional reflectance spectral curves in the optical region from 0.2 to 22.0 microns. The data were categorized by subject and each curve plotted on a single graph. Each graph is fully titled to indicate curve source and indexed by subject to facilitate user retrieval from ERSIS magnetic tape records.

Vincent, R. K.↗
DOE OSTI2022

CalWave - Open Water Demonstration - Field Testing Content Models (10/21 - 7/22)

Data for the CalWave - Open Water Demonstration, a submerged pressure differential Wave Energy Converter (WEC) Device. Device is moored to the seabed, and the motion of the waves causes the sea level to rise and fall above the device, inducing a pressure differential in the device. The alternating pressure pumps fluid through a system to generate electricity, which is transmitted to shore via bidirectional cables. Documentation and data here includes: Open Water Demonstration, including field testing content models for nearly 10 months of continuous ocean operation, from October 2021 through July 2022.

16 TIDAL AND WAVE POWER↗
DOE OSTI2017

Multiobjective Optimization of Regional and Teleseismic Data to Constrain the Source of the 12 September 2016 Mw 5.4 Earthquake in South Korea

In this paper, we propose a new approach for source inversion with automatic criteria for the station selection process and using a multiobjective optimization scheme combining teleseismic body-wave and regional surface-wave observations. To illustrate the approach, we determine the source parameters of the 12 September 2016 M w 5.4 South Korea earthquake, as well as its foreshock (same day) and its main aftershock on 19 September 2016. Available teleseismic (short period and broadband) and regional (broadband) seismograms from the Incorporated Research Institutions for Seismology International–Federation of Digital Seismograph Networks (IRIS-FDSN) webservice are selected (see Data and Resources). First, all teleseismic data with signal-to-noise ratio (SNR) above 2 in the 0.3–1.5 Hz frequency band are selected and a cepstrum function is blindly applied to help detect reflected wave arrivals inside a P coda. This method allows the identification of records with weak P-coda and clear depth phase (pP, sP) arrivals and can be used to select an optimal set of teleseismic seismograms to be used for the inversion. Second, regional seismograms are selected according to the fit between their observed and theoretical dispersion curves extracted from local 1D velocity model. Depending on the epicentral distance, two frequency bands are proposed for regional data: 15–50 s for epicentral distances smaller than 2° and 30–80 s otherwise. Finally, we explore the space parameters from exhaustive grid searches for the two objective functions Tf and Rf for teleseismic and regional data, respectively. We show that the seismic moment parameters can be exclusively derived from Rf and can be fixed for Tf. However, the depth parameter is not sensitive to Rf and can be simultaneously inverted from both. The selection of the optimal solution satisfying both cost functions uses the optimum Pareto front that allows a decrease in epistemic uncertainty. Lastly, we discuss the advantage of this approach for improving the characterization of moderate earthquake sources in areas with limited regional instrumentation.

58 GEOSCIENCES↗
DOE OSTI2016

University of Oregon: GPS-based Precipitable Water Vapor (PWV)

A partnership with the University of Oregon and U.S. Department of Energy's National Renewable Energy Laboratory (NREL) to collect Precipitable Water Vapor (PWV) data to complement existing resource assessment data collection by the university.

17 WIND ENERGY↗
NASA NTRS1980

Earth observation data systems in the 1980's

The requirements for future data systems for earth resource observation data are examined. Estimates are made for both expected data volumes and data delivery requirements. Research and development activities presently underway are described, including (1) high-speed processors such as the massively parallel processor; (2) data storage systems, including optical disk configurations and (3) distributed data systems such as high-speed local networks and the applications data service system.

Bracken, P. A.↗
DOE OSTI2015

Fencing data transfers in a parallel active messaging interface of a parallel computer

Fencing data transfers in a parallel active messaging interface (`PAMI`) of a parallel computer, the PAMI including data communications endpoints, each endpoint comprising a specification of data communications parameters for a thread of execution on a compute node, including specifications of a client, a context, and a task, the compute nodes coupled for data communications through the PAMI and through data communications resources including a deterministic data communications network, including initiating execution through the PAMI of an ordered sequence of active SEND instructions for SEND data transfers between two endpoints, effecting deterministic SEND data transfers; and executing through the PAMI, with no FENCE accounting for SEND data transfers, an active FENCE instruction, the FENCE instruction completing execution only after completion of all SEND instructions initiated prior to execution of the FENCE instruction for SEND data transfers between the two endpoints.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Fencing data transfers in a parallel active messaging interface of a parallel computer

Fencing data transfers in a parallel active messaging interface (`PAMI`) of a parallel computer, the PAMI including data communications endpoints, each endpoint comprising a specification of data communications parameters for a thread of execution on a compute node, including specifications of a client, a context, and a task, the compute nodes coupled for data communications through the PAMI and through data communications resources including a deterministic data communications network, including initiating execution through the PAMI of an ordered sequence of active SEND instructions for SEND data transfers between two endpoints, effecting deterministic SEND data transfers; and executing through the PAMI, with no FENCE accounting for SEND data transfers, an active FENCE instruction, the FENCE instruction completing execution only after completion of all SEND instructions initiated prior to execution of the FENCE instruction for SEND data transfers between the two endpoints.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2013

NASA Prediction of Worldwide Energy Resource High Resolution Meteorology Data For Sustainable Building Design

A primary objective of NASA's Prediction of Worldwide Energy Resource (POWER) project is to adapt and infuse NASA's solar and meteorological data into the energy, agricultural, and architectural industries. Improvements are continuously incorporated when higher resolution and longer-term data inputs become available. Climatological data previously provided via POWER web applications were three-hourly and 1x1 degree latitude/longitude. The NASA Modern Era Retrospective-analysis for Research and Applications (MERRA) data set provides higher resolution data products (hourly and 1/2x1/2 degree) covering the entire globe. Currently POWER solar and meteorological data are available for more than 30 years on hourly (meteorological only), daily, monthly and annual time scales. These data may be useful to several renewable energy sectors: solar and wind power generation, agricultural crop modeling, and sustainable buildings. A recent focus has been working with ASHRAE to assess complementing weather station data with MERRA data. ASHRAE building design parameters being investigated include heating/cooling degree days and climate zones.

Chandler, William S.↗
NASA NTRS2010

The Crustal Dynamics Data Information System: A Resource to Support Scientific Analysis Using Space Geodesy

Since 1982. the Crustal Dynamics Data Information System (CDDIS) has supported the archive and distribution of geodetic data products acquired by the National Aeronautics and Space Administration (NASA) as well as national and international programs. The CDDIS provides easy, timely, and reliable access to a variety of data sets, products, and information about these data. These measurements. obtained from a global network of nearly 650 instruments at more than 400 distinct sites, include DORIS (Doppler Orbitography and Radiopositioning Integrated by Satellite), GNSS (Global Navigation Satellite System), SLR and LLR (Satellite and Lunar Laser Ranging), and VLBI (Very Long Baseline Interferometry). The CDDIS data system and its archive have become increasingly important to many national and international science communities, particularly several of the operational services within the International Association of Geodesy (IAG) and its observing system the Global Geodetic Observing System (GGOS), including the International DORIS Service (IDS), the International GNSS Service (IGS). the International Laser Ranging Service (ILRS), the International VLBI Service for Geodesy and Astrometry (IVS). and the International Earth rotation and Reference frame Service (IERS), Investigations resulting from the data and products available through the CDDIS support research in many aspects of Earth system science and global change. Each month, the CDDIS archives more than one million data and derived product files totaling over 90 Gbytes in volume. In turn. the global user community downloads nearly 1.2 TBytes (over 10.5 million files) of data and products from the CDDIS each month. The requirements of analysts have evolved since the start of the CDDIS; the specialized nature of the system accommodates the enhancements required to support diverse data sets and user needs. This paper discusses the CDDIS. including background information about the system and its. user communities. archive contents. available metadata, and future plans.

Noll. Carey E.↗
NASA NTRS1982

Image-data-processing for earth resources - An overview

A total remote-sensing system comprises four distinct operations: data-acquisition, archiving, production, and dissemination of individual products, and extraction of the required information. The Landsat satellite system acquires data in several spectral bands, with a ground resolution of 80 meters (currently) or 30 meters (future). Radiometric and geometric corrections are normally applied, after which the data may be enhanced for photointerpretation or analyzed by computer. The accuracy of the analysis model for either is important. The extraction of information from remotely sensed data will generally be dependent on the use of it with other data such as maps or, perhaps, weather information. Methods are being developed to use the various data together in geographic data systems. The availability of remotely sensed data has encouraged the development of new models or analysis procedures for the use of this information.

Billingsley, F. C.↗
DOE OSTI2017

Data for Known Geothermal Resource Areas (KGRA) and Identified Hydrothermal Resource Areas (IHRA) in Southern Idaho and Southeastern Oregon

The presented database includes water chemistry data and structural rating values for various geothermal features used for performing principal component (PC) and cluster analyses work to identify promising KGRAs and IHRAs in southern Idaho and southeastern Oregon. A brief note on various KGRAs/IHRAs is also included herewith. Results of PC and cluster analyses are presented as a separate paper (Lindsey et al., 2017) that is, as of the time of this submission, in 'revision' status.

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

Resource Management for Processing Wide Area Data Streams on Supercomputers

Modern scientific instruments generate enormous amount of data. Typically, the data collected from the instruments are stored in one or more files that are then moved to a distant supercomputer for processing. The final results are sent back to the user. In order to make effective use of the time on expensive instruments, experimenters want to process the data as they are generated. They want to stream the data from instruments' memory directly to a supercomputer's memory for analysis. Since the compute nodes in a supercomputer are not connected directly to the wide area network, the data streams need to be passed through intermediate gateway nodes. As opposed to the best effort file transfers, data streaming applications require resources at a specific time for a specific period. In this paper, we present a system model for enabling data streaming through gateway nodes and an algorithm to efficiently allocate gateway node resources along with compute nodes. We evaluate the algorithm using real-world traces on the Chameleon Cloud. The results show that our system can schedule compute and gateway resources efficiently for streaming analysis.

data streaming↗