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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 1,567 records · Page 87
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

The development and operation of the international solar-terrestrial physics central data handling facility

The National Aeronautics and Space Administration (NASA) Goddard Space Flight Center (GSFC) International Solar-Terrestrial Physics (ISTP) Program is committed to the development of a comprehensive, multi-mission ground data system which will support a variety of national and international scientific missions in an effort to study the flow of energy from the sun through the Earth-space environment, known as the geospace. A major component of the ISTP ground data system is an ISTP-dedicated Central Data Handling Facility (CDHF). Acquisition, development, and operation of the ISTP CDHF were delegated by the ISTP Project Office within the Flight Projects Directorate to the Information Processing Division (IPD) within the Mission Operations and Data Systems Directorate (MO&DSD). The ISTP CDHF supports the receipt, storage, and electronic access of the full complement of ISTP Level-zero science data; serves as the linchpin for the centralized processing and long-term storage of all key parameters generated either by the ISTP CDHF itself or received from external, ISTP Program approved sources; and provides the required networking and 'science-friendly' interfaces for the ISTP investigators. Once connected to the ISTP CDHF, the online catalog of key parameters can be browsed from their remote processing facilities for the immediate electronic receipt of selected key parameters using the NASA Science Internet (NSI), managed by NASA's Ames Research Center. The purpose of this paper is twofold: (1) to describe how the ISTP CDHF was successfully implemented and operated to support initially the Japanese Geomagnetic Tail (GEOTAIL) mission and correlative science investigations, and (2) to describe how the ISTP CDHF has been enhanced to support ongoing as well as future ISTP missions. Emphasis will be placed on how various project management approaches were undertaken that proved to be highly effective in delivering an operational ISTP CDHF to the Project on schedule and within budget. Examples to be discussed include: the development of superior teams; the use of Defect Causal Analysis (DCA) concepts to improve the software development process in a pilot Total Quality Management (TQM) initiative; and the implementation of a robust architecture that will be able to support the anticipated growth in the ISTP Program science requirements with only incremental upgrades to the baseline system. Further examples include the use of automated data management software and the implementation of Government and/or industry standards, whenever possible, into the hardware and software development life-cycle. Finally, the paper will also report on several new technologies (for example, the installation of a Fiber Data Distribution Interface network) that were successfully employed.

Lehtonen, Kenneth↗
DOE OSTI2022

A Simple Standard for Sharing Ontological Mappings (SSSOM)

Abstract Despite progress in the development of standards for describing and exchanging scientific information, the lack of easy-to-use standards for mapping between different representations of the same or similar objects in different databases poses a major impediment to data integration and interoperability. Mappings often lack the metadata needed to be correctly interpreted and applied. For example, are two terms equivalent or merely related? Are they narrow or broad matches? Or are they associated in some other way? Such relationships between the mapped terms are often not documented, which leads to incorrect assumptions and makes them hard to use in scenarios that require a high degree of precision (such as diagnostics or risk prediction). Furthermore, the lack of descriptions of how mappings were done makes it hard to combine and reconcile mappings, particularly curated and automated ones. We have developed the Simple Standard for Sharing Ontological Mappings (SSSOM) which addresses these problems by: (i) Introducing a machine-readable and extensible vocabulary to describe metadata that makes imprecision, inaccuracy and incompleteness in mappings explicit. (ii) Defining an easy-to-use simple table-based format that can be integrated into existing data science pipelines without the need to parse or query ontologies, and that integrates seamlessly with Linked Data principles. (iii) Implementing open and community-driven collaborative workflows that are designed to evolve the standard continuously to address changing requirements and mapping practices. (iv) Providing reference tools and software libraries for working with the standard. In this paper, we present the SSSOM standard, describe several use cases in detail and survey some of the existing work on standardizing the exchange of mappings, with the goal of making mappings Findable, Accessible, Interoperable and Reusable (FAIR). The SSSOM specification can be found at http://w3id.org/sssom/spec. Database URL: http://w3id.org/sssom/spec

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2024

Where are the Data? Automating a Workflow for Carbon Storage Data Gap Analyses

This presentation demonstrates a spatial analysis workflow to assess data availability for the many components of geologic carbon storage technical viability. The workflow relies upon a knowledge-data framework that links the different components of GCS technical viability to the data types needed for evaluation. Using this contextual information, a combination of data science methods (e.g., natural language processing) and spatial analyses are applied to identify areas where sufficient data exists for a given component. The results are aggregated into maps illustrating data density and spatial gaps across all technical viability factors and data categories, as well as the individual component and category level for a more nuanced understanding. Presented at the FECM NETL Carbon Management Program Review Meeting 2024.

Creason, Christopher↗
DOE OSTI2024

Where are the Data? Automating a Workflow for Carbon Storage Data Gap Analyses

This presentation demonstrates a spatial analysis workflow to assess data availability for the many components of geologic carbon storage technical viability. The workflow relies upon a knowledge-data framework that links the different components of GCS technical viability to the data types needed for evaluation. Using this contextual information, a combination of data science methods (e.g., natural language processing) and spatial analyses are applied to identify areas where sufficient data exists for a given component. The results are aggregated into maps illustrating data density and spatial gaps across all technical viability factors and data categories, as well as the individual component and category level for a more nuanced understanding. Presented at the Geological Society of America Connects 2024 Annual Meeting in Anaheim, California, 22-25 September 2024.

Creason, Christopher↗
DOE OSTI2018

HESS Opinions: Incubating deep-learning-powered hydrologic science advances as a community

Recently, deep learning (DL) has emerged as a revolutionary and versatile tool transforming industry applications and generating new and improved capabilities for scientific discovery and model building. The adoption of DL in hydrology has so far been gradual, but the field is now ripe for breakthroughs. This paper suggests that DL-based methods can open up a complementary avenue toward knowledge discovery in hydrologic sciences. In the new avenue, machine-learning algorithms present competing hypotheses that are consistent with data. Interrogative methods are then invoked to interpret DL models for scientists to further evaluate. However, hydrology presents many challenges for DL methods, such as data limitations, heterogeneity and co-evolution, and the general inexperience of the hydrologic field with DL. The roadmap toward DL-powered scientific advances will require the coordinated effort from a large community involving scientists and citizens.Integrating process-based models with DL models will help alleviate data limitations. The sharing of data and baseline models will improve the efficiency of the community as a whole. Open competitions could serve as the organizing events to greatly propel growth and nurture data science education in hydrology, which demands a grassroots collaboration. The area of hydrologic DL presents numerous research opportunities that could, in turn,stimulate advances in machine learning as well.

58 GEOSCIENCES↗
NASA NTRS1974

Report on active and planned spacecraft and experiments

Information dealing with active and planned spacecraft and experiments known to the National Space Science Data Center (NSSDC) is presented. Included is information concerning a wide range of disciplines: astronomy, earth sciences, meteorology, planetary sciences, aeronomy, particles and fields, solar physics, life sciences, and material sciences. These spacecraft represent the efforts and funding of individual countries, as well as cooperative arrangements among different countries.

Brecht, J. J.↗
NASA NTRS1978

User's guide to the Nimbus-4 backscatter ultraviolet experiment data sets

The first year's data from the Nimbus 4 backscatter ultraviolet (BUV) experiment have been archived in the National Space Science Data Center (NSSDC). Backscattered radiances in the ultraviolet measured by the satellite were used to compute the global total ozone for the period April 1970 - April 1971. The data sets now in the NSSDC are the results obtained by the Ozone Processing Team, which has processed the data with the purpose of determining the best quality of the data. There are four basic sets of data available in the NSSDC representing various stages in processing. The primary data base contains organized and cleaned data in telemetry units. The radiance data has had most of the engineering calibrations performed. The detailed total ozone data is the result of computations to obtain the total ozone; the Compressed Total Ozone data is a convenient condensation of the detailed total ozone. Product data sets are also included.

Lowrey, B. E.↗
NASA NTRS1982

User's guide for the Solar Backscattered Ultraviolet (SBUV) instrument first year ozone-S data set

Total-ozone and ozone vertical profile results for Solar Backscattered Ultraviolet/Total Ozone Mapping Spectrometer (SBUV/TOMS) Nimbus 7 operation from November 1978 to November 1979 are available. The algorithm used have been thoroughly tested, the instrument performance has been examined in details, and the ozone results have been compared with Dobson, Umkehr, balloon, and rocket observations. The accuracy and precision of the satellite ozone data are good to at least within the ability of the ground truth to check and are self-consistent to within the specifications of the instrument. The 'SBUV User's Guide' describes the SBUV experiment and algorithms used. Detailed information on the data available on computer tape is provided including how to order tapes from the National Space Science Data Center.

Fleig, A. J.↗
NASA NTRS1984

Planetary Data Workshop, Part 2

Technical aspects of the Planetary Data System (PDS) are addressed. Methods and tools for maintaining and accessing large, complex sets of data are discussed. The specific software and applications needed for processing imaging and non-imaging science data are reviewed. The need for specific software that provides users with information on the location and geometry of scientific observations is discussed. Computer networks and user interface to the PDS are covered along with Computer hardware available to this data system.

Source record↗
NASA NTRS1987

Evolution of the Southern Oscillation as observed by the Nimbus-7 ERB experiment

The Nimbus-7 satellite has been in a 955-km, sun-synchronous orbit since October 1978. The Earth Radiation Budget (ERB) experiment has taken approximately 8 years of high-quality data during this time, of which seven complete years have been archived at the National Space Science Data Center. A final reprocessing of the wide-field-of-view channel dataset is underway. Error analyses indicate a long-term stability of 1 percent better over the length of the data record. As part of the validation of the ERB measurements, the archived 7-year Nimbus-7 ERB dataset is examined for the presence and accuracy of interannual variations including the Southern Oscillation signal. Zonal averages of broadband outgoing longwave radiation indicate a terrestrial response of more than 2 years to the oceanic and atmospheric manifestations of the 1982-83 El Nino/Southern Oscillation (ENSO) event, especially in the tropics. This signal is present in monthly and seasonal averages and is shown here to derive primarily from atmospheric responses to adjustments in the Pacific Ocean. The calibration stability of this dataset thus provides a powerful new tool to examine the physics of the ENSO phenomena.

Ardanuy, Philip E.↗
NASA NTRS1992

Deep-space navigation applications of improved ground-based optical astrometry

Improvements in ground-based optical astrometry will eventually be required for navigation of interplanetary spacecraft when these spacecraft communicate at optical wavelengths. Although such spacecraft may be some years off, preliminary versions of the astrometric technology can also be used to obtain navigational improvements for the Galileo and Cassini missions. This article describes a technology-development and observational program to accomplish this, including a cooperative effort with U.S. Naval Observatory Flagstaff Station. For Galileo, Earth-based astrometry of Jupiter's Galilean satellites may improve their ephemeris accuracy by a factor of 3 to 6. This would reduce the requirements for onboard optical navigation pictures, so that more of the data transmission capability (currently limited by high-gain antenna deployment problems) can be used for science data. Also, observations of European Space Agency (ESA) Hipparcos stars with asteroid 243 Ida may provide significantly improved navigation accuracy for a planned August 1993 Galileo spacecraft encounter.

Null, G. W.↗
NASA NTRS1992

Registering and resampling images in STSDAS

Registering different images can be difficult, especially if the images to be registered are images at different wavelengths, where features in one image may look entirely different or be absent from the second image. Using two new packages soon to be added to the STSDAS package, REGISTER and RESAMPLE, this job is done automatically. The REGISTER package allows the user to determine the amount of translation, rotation, and/or magnification needed to make two images, spectra, or time series congruent. The methods implemented to compute the registration parameters use: a set of the pixel coordinates of the same features identified in two files, or the FITS coordinate transformation parameters in the headers of two data files, or a single feature identified as the peak of a cross-correlation between two vectors. The coefficients describing the registration are defined by the equations (for a two-dimensional image): x = a + bx + cy, y = d + ex + fy, where (X,Y) are the pixel coordinates of a feature in the reference image, (x,y) are the pixel coordinates of a feature in the secondary image, and the computed coefficients are a, b, c, d, e, and f. Results may be produced by linking the output of REGISTER to RESAMPLE in a command language procedure. The output from REGISTER and the input to RESAMPLE consists of a matrix of coefficients (a through f above) fully specifying the registration. The RESAMPLE package resamples simple vector or image data for a given amount of translation, rotation (images only), and magnification, or reflection of the science data. Specific options included are: image rotation about the FITS reference pixel; scale changes, i.e. magnification or demagnification (for images, independently on both axes); simple translation; reflection (for images, about one or both axes); and resampling and registration to a reference data set. Output from the RESAMPLE task is the resampled image which may then be displayed and compared with the reference image.

Williamson, R. L., II↗
NASA NTRS2002

Optimal Extraction with Sub-sampled Line-Spread Functions

STIS long-slit medium resolution spectra reduced in CALSTIS extended-source mode with narrow extraction heights (GWIDTH=3 pixels) show photometric uncertainties of +/- 3% relative to point-source extractions. These uncertainties are introduced through interpolation in the spectral image rectification processing stage, and are correlated with the number of pixel crossings the spectral profile core encounters in the spatial direction. The line-spread-function may be determined as a function of pixel crossing- position from calibration data sub-sampled in the spatial direction. This line spread function will be applied to science data to perform optimal extractions and point- source de-blending. Wavelength and breathing effects will be studied. Viability of the method to de-convolve extended source 'blobs' will be investigated.

Collins, Nicholas R.↗
NASA NTRS2003

Sensor Calibration and Ocean Products for TRMM Microwave Radiometer

During the three years of finding, we have carefully corrected for two sensor/platform problems, developed a physically based retrieval algorithm to calculate SST, wind speed, water vapor, cloud liquid water and rain rates, validated these variables, and demonstrated that satellite microwave radiometers can provide very accurate SST retrievals through clouds. Prior to this, there was doubt by some scientists that the technique of microwave SST retrieval from satellites is a viable option. We think we have put these concerns to rest, and look forward to making microwave SSTs a standard component of the Earth science data sets. Our TMI SSTs were featured on several network news broadcasts and were reported in Science magazine. Additionally, we have developed a SST algorithm for VIRS to facilitate IR/MW inter-comparisons and completed research into diurnal cycles and air-sea interactions.

Wentz, Frank J.↗
NASA NTRS2003

Sensor Calibration and Ocean Products for TRMM Microwave Radiometer

During the three years of fundin& we have carefully corrected for two sensor/platform problems, developed a physically based retrieval algorithm to calculate SST, wind speed, water vapor, cloud liquid water and rain rates, validated these variables, and demonstrated that satellite microwave radiometers can provide very accurate SST retrievals through clouds. Prior to this, there was doubt by some scientists that the technique of microwave SST retrieval from satellites is a viable option. We think we have put these concerns to rest, and look forward to making microwave SSTs a standard component of the Earth science data sets. Our TMI SSTs were featured on several network news broadcasts and were reported in Science magazine. Additionally, we have developed a SST algorithm for VIRS to facilitate IR/MW inter-comparisons and completed research into diurnal cycles and air-sea interactions.

Lawrence, Richard J.↗
NASA NTRS2014

The Importance of Data Visualization: Incorporating Storytelling into the Scientific Presentation

From its inception in 2000, one of the primary tasks of the Biomedical Data Reduction Analysis (BDRA) group has been translation of large amounts of data into information that is relevant to the audience receiving it. BDRA helps translate data into an integrated model that supports both operational and research activities. This data integrated model and subsequent visual data presentations have contributed to BDRA's success in delivering the message (i.e., the story) that its customers have needed to communicate. This success has led to additional collaborations among groups that had previously not felt they had much in common until they worked together to develop solutions in an integrated fashion. As more emphasis is placed on working with "big data" and on showing how NASA's efforts contribute to the greater good of the American people and of the world, it becomes imperative to visualize the story of our data to communicate the greater message we need to share. METHODS To create and expand its data integrated model, BDRA has incorporated data from many different collaborating partner labs and other sources. Data are compiled from the repositories of the Lifetime Surveillance of Astronaut Health and the Life Sciences Data Archive, and from the individual laboratories at Johnson Space Center that support collection of data from medical testing, environmental monitoring, and countermeasures, as designated in the Medical Requirements Integration Documents. Ongoing communication with the participating collaborators is maintained to ensure that the message and story of the data are retained as data are translated into information and visual data presentations are delivered in different venues and to different audiences. RESULTS We will describe the importance of storytelling through an integrated model and of subsequent data visualizations in today's scientific presentations and discuss the collaborative methods used. We will illustrate the discussion with examples of graphs from BDRA's past work supporting operations and/or research efforts.

Babiak-Vazquez, A.↗
NASA NTRS2017

Restoration of the Apollo 15 Heat Flow Experiment Data from 1975 to 1977

The Apollo 15 Heat Flow Experiment (HFE) was conducted from July 1971 through January 1977. Two heat flow probes were deployed roughly 8.5 meters apart. Probe 1 and Probe 2 penetrated to 1.4-meters and 1-meter depths into the lunar regolith, respectively. Temperatures at different depths and the surface were logged with 7.25-minute intervals and transmitted to Earth. At the conclusion of the experiment, only data obtained from July 1971 through December 1974 were processed and archived at the National Space Science Data Center (NSSDC) by the principal investigator of the experiment, Marcus Langseth of Columbia University. Langseth died in 1997. It is not known what happened to the HFE data tapes he used. Current researchers have strong interests in re-examining the HFE data for the full duration of the experiment. We have recovered and processed large portions of the Apollo 15 HFE data from 1975 through 1977 by assembling data and metadata from various sources.

HFE↗
NASA NTRS2015

Trajectory Dispersion Control for the Cassini Grand Finale Mission

The Cassini Grand Finale Mission, which consists of 22 ballistic orbits, will begin on April 22, 2017 after the last targeted Titan flyby. It will end on September 15, 2017 when the spacecraft dives into Saturn's atmosphere and be permanently captured. High volumes of unique science data from various onboard instruments are expected from the mission. To ensure its success and facilitate science planning, the trajectory dispersion needs to be controlled below 250 km (root-mean-square spatial deviation at the 68th percentile level) for a few segments of trajectory in the mission. This paper reports the formulation and solution of this dispersion control problem. We consider various sources of uncertainties including flyby error, orbit determination error, maneuver execution error, thruster firing control error, and uncertainty in Saturn's atmospheric model. A non-linear Monte Carlo Trajectory Dispersion tool is developed and employed for the analysis. It is found that a total of three Orbit Trim Maneuvers with a 99% (Delta)V usage of less than 2 m/s will adequately control the trajectory.

orbit determination↗