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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 NTRS2015

The Open Data Repositorys Data Publisher

Data management and data publication are becoming increasingly important components of researcher's workflows. The complexity of managing data, publishing data online, and archiving data has not decreased significantly even as computing access and power has greatly increased. The Open Data Repository's Data Publisher software strives to make data archiving, management, and publication a standard part of a researcher's workflow using simple, web-based tools and commodity server hardware. The publication engine allows for uploading, searching, and display of data with graphing capabilities and downloadable files. Access is controlled through a robust permissions system that can control publication at the field level and can be granted to the general public or protected so that only registered users at various permission levels receive access. Data Publisher also allows researchers to subscribe to meta-data standards through a plugin system, embargo data publication at their discretion, and collaborate with other researchers through various levels of data sharing. As the software matures, semantic data standards will be implemented to facilitate machine reading of data and each database will provide a REST application programming interface for programmatic access. Additionally, a citation system will allow snapshots of any data set to be archived and cited for publication while the data itself can remain living and continuously evolve beyond the snapshot date. The software runs on a traditional LAMP (Linux, Apache, MySQL, PHP) server and is available on GitHub (http://github.com/opendatarepository) under a GPLv2 open source license. The goal of the Open Data Repository is to lower the cost and training barrier to entry so that any researcher can easily publish their data and ensure it is archived for posterity.

Astrobiology data↗
NASA NTRS1997

The future of bibliographic standards in a networked information environment

The main mission of the CENDI Cataloging Working Group is to provide guidelines for cataloging practices that support the sharing of database records among the CENDI agencies, and that incorporate principles based on cost effectiveness and efficiency. Recent efforts include the extension of COSATI Guidelines for the Cataloging of Technical Reports to include non-print materials, and the mapping of each agency's export file structure to USMARC. Of primary importance is the impact of electronic documents and the distributed nature of the networked information environment. Topics discussed during the workshop include the following: Trade-offs in Cataloging and Indexing Internet Information; The Impact on Current and Future Standards; A Look at WWW Metadata Initiatives; Standards for Electronic Journals; The Present and Future Search Engines; The Roles for Text Analysis Software; Advanced Search Engine Meets Metathesaurus; Locator Schemes for Internet Resources; Identifying and Cataloging Web Document Types; In Search of a New Bibliographic Record. The videos in this set include viewgraphs of charts and related materials of the workshop.

Source record↗
NASA NTRS2000

Possibilities of Using MARSES Instrument for Long-Term Monitoring and Subsurface Studies in Arctic and Arid Lands

The Mars Electromagnetic Sounding Experiment (MARSES) is the sounding instrument developed of searching for groundwater, water-ice or permafrost layers existing in some depth under the visible surface in the dry lands of Mars. One of the more important challenges facing natural resource managers today is how to identify, measure and monitoring the cumulative impacts of land use decisions across space and time. The secondary task is to measure the soil properties of Martian subsurface, which includes porosity, electrical resistance of the liquid phase, thermal conductivity, temperature dependence. A main task of the MARSES monitoring system is to examine changes in the subsurface properties of local areas regolith on the Martian surface on the base of the database of various soil slices in terrestrial conditions. Additional information is contained in the original extended abstract.

Ozorovich, Y. R.↗
NASA NTRS2000

Spectral Anomalies in the 11 and 12 micron Region From the Mariner Mars 7 Infrared Spectrometer

Two hundred-forty infrared spectra acquired by the 1969 Mariner Mars 7 Infrared Spectrometer (IRS), spanning the wavelength region 1.8-14.4 micron (5550-690/cm), have recently been recovered and calibrated in both wavelength and intensity. An examination of these IRS spectra has revealed absorptions at 11.25 and 12.5 micron that have not previously been reported for Mars. A search of the literature and spectral data bases shows that materials that exhibit a doublet at 11.25 and 12.5 micron are rare. In this paper we examine potential causes for these features and include a detailed discussion of carbonates, goethite, CO2 ice, and water ice. CO2 ice and water ice measured in transmission do not exhibit bands that match those recorded at 11.25 and 12.5 micron for Mars, which indicates that CO2 or water ice clouds are not the source of these features. Since these bands show no clear correlation with atmospheric path length, they are most likely caused by a surface material. In the IRS database they appear to be exceptionally intense in the western part of the Hellas basin. Goethite exhibits bands that are a good spectral match, but confirming whether goethite causes the features will require additional studies of the 20-50 micron region. These studies will require laboratory measurements of weathering coatings and an examination of spectra recorded of Mars by the 1971 Mariner Mars Infrared Interferometer Spectrometer (IRIS; 5-50 micron 2000200/cm) and the 1996 Thermal Emission Spectrometer (TES; 6-50 micron 1667-200/cm).

Kirkland, Laurel E.↗
NASA NTRS2001

Possibilities of Using MARSES Instrument for Long-Term Monitoring and Subsurface Studies in Arctic and Arid Lands

The MARSES is the sounding instrument developed of searching for groundwater, water-ice or permafrost layers existing in some depth under the visible surface in the dry lands of Mars. One of the more important challenges facing natural resource managers today is how to identify, measure and monitoring the cumulative impacts of land use decisions across space and time. The secondary task is to measure the soil properties of Martian subsurface, which includes porosity, electrical resistance of the liquid phase, thermal conductivity, temperature dependence. A main task of the MARSES monitoring system is to examine changes in the subsurface properties of local areas regolith on the Martian surface on the base of the database of various soil slices in terrestrial conditions

Ozorovich, Y. R.↗
NASA NTRS1998

Guest Investigator Studies with the Compton Gamma Ray Observatory

The cumulative all-sky survey by the Compton Gamma Ray Observatory (CGRO), composed of data acquired during the first three years of the mission, included a number of regions of very limited exposure. The most glaring deficiency in coverage was toward the region of the South Galactic Pole (SGP), which received significantly less exposure than other directions- by a factor of at least 2 to 3. Furthermore, nearly all of the SGP exposure was accumulated during the first year of the mission. Since blazars are known to be time-variable, and of unknown duty cycle, a pointing of the CCRO in that direction was considered highly desirable, and long overdue. In addition, data gathered from a pointing toward the SGP and its comparison with comprehensive data available for the North Galactic Pole would be extremely valuable to investigators studying the extragalactic diffuse emission. The reasons outlined above prompted our initiation of a Cycle 4 campaign to systematically search with EGRET and COMPTEL for gamma-ray emission from sources near the South Galactic Pole. The Cycle 4 SGP campaign consisted of tnvo 14-day observations separated in in time by approximately 10 months. The temporal separation of the observations was requested to allow a test for possible variations in the detected sources. Our primary targets were 38 FSRQs which lie within 30 degrees of the SGP, and which satisfy the basic criteria for candidate gamma-ray AGNs,flat-spectrum radio sources, many of which exhibit blazar-type properties). These targets were selected from the standard references, and from the available on-line databases (e.g., the NASA Extragalactic Database, NED), as the most promising AGN targets in the vicinity of the SGP. A 30 radius from the SGP was chosen as the boundary of our survey, since the selected targets would then fall within the most sensitive portion of the fields of view of EGRET and COMPTEL (i.e., within a 30 zenith angle), for a CGRO pointing directed exactly at the SGP. Our South Galactic Pole Survey yielded a number of exciting results. The EGRET data were analyzed using the maximum likelihood techniques to estimate the intensity, spectrum, and position of gamma-ray sources in the field of view. Our analysis revealed four sources at energies greater than 100 MeV with likelihood ratios corresponding to greater than 30 detections (Vestrand et al. 1996). One of the sources is associated with the well known gamma-ray blazar PKS 0208-512, but the other three were previously unknown. Among the new detections was PKS 2155-304 which is often considered a prototype of the x-ray selected BL Lacs. PKS 2155-304, which was also detected at hard x-ray energies by CGRO/OSSE, is one of the brightest BL Lac objects in the sky at optical through x-ray energies and has a history of rapid, strong multiwavelength variability. As such, it has been the subject of intensive, contemporaneous, multiwavelength monitoring covering radio frequencies to x-ray energies.

Vestrand, W. T.↗
NASA NTRS2020

GeneLab

GeneLab collects and enables analysis of spaceflight and ground-based spaceflight simulation genomic data, RNA and protein expression, and metabolic profiles. It interfaces with other existing databases containing spaceflight omic data. The 2011 National Research Council (NRC) Decadal Survey on NASA Life and Physical Sciences called for increased opportunities for multi-investigator spaceflight opportunities and greater use of genomic approaches to meet the needs of NASA researchers. To address these recommendations of the NRC Decadal Survey, the Space Life and Physical Sciences Research and Applications Division of NASA's Human Exploration and Operations Mission Directorate has initiated a transition to an Open Science architecture to increase research opportunities, and has developed the GeneLab Platform based on highly leveraged and integrated bioinformatics analytics. GeneLab is an interactive, open-access resource where scientists can upload, download, store, search, share, transfer, and analyze omics data from spaceflight and corresponding analogue experiments. Users can explore GeneLab datasets in the Data Repository, analyze data using the Analysis Platform, visualize high-order data and create collaborative projects using the Collaborative Workspace. Our primary goal is to maximize the utilization of the valuable biological research conducted aboard the International Space Station (ISS) by collecting genomic, transcriptomic, proteomic, and metabolomics data known as “omics”. By providing a portal linking processed data to flight parameters, GeneLab enables exploration of the molecular network responses of terrestrial biology to the space environment. This allows researchers to understand the complex responses of biological systems to the space environment. This technology development activity was transferred from the Human Exploration and Operations Mission Directorate to the Science Mission Directorate Division of Biological and Physical Sciences (BPS) in October 2020.

GeneLab↗
NASA NTRS2005

The Challenges of Interoperable Data Discovery

The Global Change Master Directory (GCMD) assists the oceanographic community in data discovery and access through its online metadata directory. The directory also offers data holders a means to post and search their oceanographic data through the GCMD portals, i.e. online customized subset metadata directories. The Gulf of Maine Ocean Data Partnership (GoMODP) has expressed interest in using the GCMD portals to increase the visibility of their data holding throughout the Gulf of Maine region and beyond. The purpose of the Gulf of Maine Ocean Data Partnership (GoMODP) is to "promote and coordinate the sharing, linking, electronic dissemination, and use of data on the Gulf of Maine region". The participants have decided that a "coordinated effort is needed to enable users throughout the Gulf of Maine region and beyond to discover and put to use the vast and growing quantities of data in their respective databases". GoMODP members have invited the GCMD to discuss further collaborations in view of this effort. This presentation. will focus on the GCMD GoMODP Portal - demonstrating its content and use for data discovery, and will discuss the challenges of interoperable data discovery. interoperability among metadata standards and vocabularies will be discussed. A short overview of the lessons learned at the Marine Metadata Interoperability (MMI) metadata workshop held in Boulder, Colorado on August 9-11, 2005 will be given.

Meaux, Melanie F.↗
NASA NTRS2021

Machine Learning the COSMO Model for Predicting Thermodynamics of Electrolyte Mixtures

Bottom-up design of electrolyte mixtures for battery systems requires predicting macro thermodynamic properties from molecular constituents. For instance, molten salt electrolyte batteries require conditions far above room temperature to operate. Therefore, discovering mixtures with increasingly lower eutectic melting points is desirable. A model that can approximate chemical activity is a valuable tool to search through the vast compositional design space. Machine learning can predict properties of materials such as vibrational free energies, electronic energy gaps, and thermal conductivities. Moreover, they can learn physical models such as interatomic potentials. The COSMO-SAC model uses theory and empirical parameterization to predict liquid-vapor and liquid-solid properties using first-principles calculations. However, obtaining activity coefficients required for parameterizing the COSMO-SAC model is costly and limited to a select chemical space. In this work, we explored if machine learning methods could improve the COSMO-SAC model and bridge density functional theory calculations to liquid phase thermodynamic properties. Our data-driven approach uses existing databases for sigma-profiles of organic solvents and reconciles their methodological differences via ensemble averaging. First, an optimal machine learning model is constructed for each dataset. Our machine learning algorithms use the sigma-profile as an input feature to predict binary mixtures' activity coefficients using multi-output regression. Each dataset uses different choices of functionals, methods, and basis sets. Therefore, our ensemble model attempts to predict corrected activity coefficients given the combination of all the model outputs. The activity coefficients used for training are generated using the COSMO-SAC model. This approach enables the extraction of meaningful information from the existing datasets to improve the COSMO-SAC model for obtaining thermodynamic properties of electrolyte mixtures. With the liquid phase activities, we can identify electrolyte mixtures that meet desired phase equilibria conditions.

Thermodynamics↗
NASA NTRSDate not supplied

Hierarchical screening for Li-based solid electrolytes using fast, interpretable machine-learned potentials

Li-based solid-state electrolyte materials enable safer, all-solid-state batteries but the computational search for candidates with favorable stability and Li-ion conductivity is challenging due to the size of the search space and the cost of evaluating transport properties with ab initio methods. The prohibitive cost of high-throughput screening with DFT has lead to the development of surrogate models using geometric analysis, empirical potentials, and descriptors for ionic transport. Here, I will discuss a hierarchical screening approach for identifying promising materials using a combination of density functional theory, bond-valence methods, and machine learning potentials generated with the Ultra-Fast Force Fields (UF3) framework. We show how the inexpensive bond-valence method can be used to guide the generation of training samples for machine learning, in addition to filtering candidates. Finally, we apply the hierarchical workflow to screen for ionic conductivity across a database of Li-containing compounds.

Materials discovery↗
NASA NTRS1985

Developement of an Optimum Interpolation Analysis Method for the CYBER 205

A state-of-the-art technique to assimilate the diverse observational database obtained during FGGE, and thus create initial conditions for numerical forecasts is described. The GLA optimum interpolation (OI) analysis method analyzes pressure, winds, and temperature at sea level, mixing ratio at six mandatory pressure levels up to 300 mb, and heights and winds at twelve levels up to 50 mb. Conversion to the CYBER 205 required a major re-write of the Amdahl OI code to take advantage of the CYBER vector processing capabilities. Structured programming methods were used to write the programs and this has resulted in a modular, understandable code. Among the contributors to the increased speed of the CYBER code are a vectorized covariance-calculation routine, an extremely fast matrix equation solver, and an innovative data search and sort technique.

Nestler, M. S.↗
NASA NTRS2002

Electron Density Profiles of the Topside Ionosphere

The existing uncertainties about the electron density profiles in the topside ionosphere, i.e., in the height region from h,F2 to - 2000 km, require the search for new data sources. The ISIS and Alouette topside sounder satellites from the sixties to the eighties recorded millions of ionograms but most were not analyzed in terms of electron density profiles. In recent years an effort started to digitize the analog recordings to prepare the ionograms for computerized analysis. As of November 2001 about 350000 ionograms have been digitized from the original 7-track analog tapes. These data are available in binary and CDF format from the anonymous ftp site of the National Space Science Data Center. A search site and browse capabilities on CDAWeb assist the scientific usage of these data. All information and access links can be found at http://nssdc.gsfc.nasa.gov/space/isis/isis- status.htm1. This paper describes the ISIS data restoration effort and shows how the digital ionograms are automatically processed into electron density profiles from satellite orbit altitude (1400 km for ISIS-2) down to the F peak. Because of the large volume of data an automated processing algorithm is imperative. The TOPside Ionogram Scaler with True height algorithm TOPIST software developed for this task is successfully scaling - 70% of the ionograms. An < > is available to manually scale the more difficult ionograms. The automated processing of the digitized ISIS ionograms is now underway, producing a much-needed database of topside electron density profiles for ionospheric modeling covering more than one solar cycle.

Huang, Xue-Qin↗
NASA NTRS2001

New Data on the Topside Electron Density Distribution

The existing uncertainties about the electron density profiles in the topside ionosphere, i.e., in the height region from hmF2 to approx. 2000 km, require the search for new data sources. The ISIS and Alouette topside sounder satellites from the sixties to the eighties recorded millions of ionograms and most were not analyzed in terms of electron density profiles. In recent years an effort started to digitize the analog recordings to prepare the ionograms for computerized analysis. As of November 2001 about 350,000 ionograms have been digitized from the original 7-track analog tapes. These data are available in binary and CDF format from the anonymous ftp site of the National Space Science Data Center. A search site and browse capabilities on CDAWeb assist the scientific usage of these data. All information and access links can be found at http://nssdc.gsfc.nasa.gov/space/isis/isis-status.html. This paper describes the ISIS data restoration effort and shows how the digital ionograms are automatically processed into electron density profiles from satellite orbit altitude (1400 km for ISIS-2) down to the F peak. Because of the large volume of data an automated processing algorithm is imperative. The automatic topside ionogram scaler with true height algorithm TOPIST software developed for this task is successfully scaling approx.70 % of the ionograms. An 'editing process' is available to manually scale the more difficult ionograms. The automated processing of the digitized ISIS ionograms is now underway, producing a much-needed database of topside electron density profiles for ionospheric modeling covering more than one solar cycle. The ISIS data restoration efforts are supported through NASA's Applied Systems and Information Research Program.

Huang, Xue-Qin↗
NASA NTRS2007

Machine Aided Indexing and the NASA Thesaurus

Machine Aided Indexing (MAI) is a Web-based application program for aiding the indexing of literature in the NASA Scientific and Technical Information (STI) Database. MAI was designed to be a convenient, fully interactive tool for determining the subject matter of documents and identifying keywords. The heart of MAI is a natural-language processor that accepts, as input, any user-supplied text, including abstracts, full documents, and Web pages. Within seconds, the text is analyzed and a ranked list of terms is generated. The 17,800 terms of the NASA Thesaurus serve as the foundation of the knowledge base used by MAI. The NASA Thesaurus defines a standard vocabulary, the use of which enables MAI to assist in ensuring that STI documents are uniformly and consistently accessible. Of particular interest to traditional users of the NASA Thesaurus, MAI incorporates a fully searchable thesaurus display module that affords word-search and hierarchy- navigation capabilities that make it much easier and less time-consuming to look up terms and browse, relative to lookup and browsing in older print and Portable Document Format (PDF) digital versions of the Thesaurus. In addition, because MAI is centrally hosted, the Thesaurus data are always current.

vonOfenheim, Bill↗
NASA NTRS2003

Organizing Diverse, Distributed Project Information

SemanticOrganizer is a software application designed to organize and integrate information generated within a distributed organization or as part of a project that involves multiple, geographically dispersed collaborators. SemanticOrganizer incorporates the capabilities of database storage, document sharing, hypermedia navigation, and semantic-interlinking into a system that can be customized to satisfy the specific information-management needs of different user communities. The program provides a centralized repository of information that is both secure and accessible to project collaborators via the World Wide Web. SemanticOrganizer's repository can be used to collect diverse information (including forms, documents, notes, data, spreadsheets, images, and sounds) from computers at collaborators work sites. The program organizes the information using a unique network-structured conceptual framework, wherein each node represents a data record that contains not only the original information but also metadata (in effect, standardized data that characterize the information). Links among nodes express semantic relationships among the data records. The program features a Web interface through which users enter, interlink, and/or search for information in the repository. By use of this repository, the collaborators have immediate access to the most recent project information, as well as to archived information. A key advantage to SemanticOrganizer is its ability to interlink information together in a natural fashion using customized terminology and concepts that are familiar to a user community.

Keller, Richard M.↗
NASA NTRSDate not supplied

Modeling Atmospheric Science Knowledge from Research Publications

NASA Earth Science Data Centers contain enormous amounts of remote sensing digital data. It is often a significant challenge for users to find data suitable for their research topic in these vast archives. One of the approaches is the usage-driven dataset discovery, where users seek publications on projects similar to their intended study. For this approach to be effective, users need a clear connection between the underlying data in the publications and the study objectives; this is not often apparent to non-expert users. Tools and methodologies that can help facilitate and organize these connections are therefore valuable for creating improved knowledge mappings, which can be further used by search engines to suggest data or publications best tailored to a user’s specific research goal. As an illustration of these challenges, in this work we focus on the atmospheric chemistry processes related to Earth environmental impacts such as ozone depletion, aerosols, smog formation, acid rain, and radiative forcing. We further limit our study to publications that use data from the Microwave Limb Sounder (MLS) instrument flown on the Aura Earth Observing System. To create knowledge representations of science carried out in these publications, we use existing ontologies such as the Global Change Master Directory (GCMD) and Semantic Web for Earth and Environmental Terminology (SWEET). These ontologies together encompass term dictionaries that include measured variables, names of molecules or radicals, mission and instrument names, locations, action words, among many others. Based on these terms acknowledge graph database was populated with the terms retrieved from scientific publications that study atmospheric chemistry. These databases can be used to further enhance the automation of knowledge discovery and facilitate machine learning and artificial intelligence algorithms or applications. These tools and methods can also be extended to apply to content from other related Earth science domains.

Irina Gerasimov↗
NASA NTRS1988

Geological remote sensing signatures of terrestrial impact craters

Geological remote sensing techniques can be used to investigate structural, depositional, and shock metamorphic effects associated with hypervelocity impact structures, some of which may be linked to global Earth system catastrophies. Although detailed laboratory and field investigations are necessary to establish conclusive evidence of an impact origin for suspected crater landforms, the synoptic perspective provided by various remote sensing systems can often serve as a pathfinder to key deposits which can then be targetted for intensive field study. In addition, remote sensing imagery can be used as a tool in the search for impact and other catastrophic explosion landforms on the basis of localized disruption and anomaly patterns. In order to reconstruct original dimensions of large, complex impact features in isolated, inaccessible regions, remote sensing imagery can be used to make preliminary estimates in the absence of field geophysical surveys. The experienced gained from two decades of planetary remote sensing of impact craters on the terrestrial planets, as well as the techniques developed for recognizing stages of degradation and initial crater morphology, can now be applied to the problem of discovering and studying eroded impact landforms on Earth. Preliminary results of remote sensing analyses of a set of terrestrial impact features in various states of degradation, geologic settings, and for a broad range of diameters and hence energies of formation are summarized. The intention is to develop a database of remote sensing signatures for catastrophic impact landforms which can then be used in EOS-era global surveys as the basis for locating the possibly hundreds of missing impact structures. In addition, refinement of initial dimensions of extremely recent structures such as Zhamanshin and Bosumtwi is an important objective in order to permit re-evaluation of global Earth system responses associated with these types of events.

Garvin, J. B.↗
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↗