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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 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
NASA NTRS2011

Land Surface Microwave Emissivities Derived from AMSR-E and MODIS Measurements with Advanced Quality Control

A microwave emissivity database has been developed with data from the Advanced Microwave Scanning Radiometer-EOS (AMSR-E) and with ancillary land surface temperature (LST) data from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the same Aqua spacecraft. The primary intended application of the database is to provide surface emissivity constraints in atmospheric and surface property retrieval or assimilation. An additional application is to serve as a dynamic indicator of land surface properties relevant to climate change monitoring. The precision of the emissivity data is estimated to be significantly better than in prior databases from other sensors due to the precise collocation with high-quality MODIS LST data and due to the quality control features of our data analysis system. The accuracy of the emissivities in deserts and semi-arid regions is enhanced by applying, in those regions, a version of the emissivity retrieval algorithm that accounts for the penetration of microwave radiation through dry soil with diurnally varying vertical temperature gradients. These results suggest that this penetration effect is more widespread and more significant to interpretation of passive microwave measurements than had been previously established. Emissivity coverage in areas where persistent cloudiness interferes with the availability of MODIS LST data is achieved using a classification-based method to spread emissivity data from less-cloudy areas that have similar microwave surface properties. Evaluations and analyses of the emissivity products over homogeneous snow-free areas are presented, including application to retrieval of soil temperature profiles. Spatial inhomogeneities are the largest in the vicinity of large water bodies due to the large water/land emissivity contrast and give rise to large apparent temporal variability in the retrieved emissivities when satellite footprint locations vary over time. This issue will be dealt with in the future by including a water fraction correction. Also note that current reliance on the MODIS day-night algorithm as a source of LST limits the coverage of the database in the Polar Regions. We will consider relaxing the current restriction as part of future development.

Moncet, Jean-Luc↗
NASA NTRS1983

Advanced Platform Systems Technology study. Volume 3: Supporting data

The overall study effort proceeded from the identification of 106 technology topics to the selection of 5 for detail trade studies. The technical issues and options were evaluated through the trade process. Finally, individual consideration was given to costs and benefits for the technologies identified for advancement. Eight priority technology items were identified for advancement. Supporting data generated during the trade selection and trade study process were presented. Space platform requirements, trade study and cost benefits analysis, and technology advancement planning are advanced. The structured approach used took advantage of a number of forms developed to ensure that a consistent approach was employed by each of the diverse specialists that participated. These forms were an intrinsic part of the study protocol.

Source record↗
DOE OSTI2020

Solar Wind Turbulence from 1 to 45 au. I. Evidence for Dissipation of Magnetic Fluctuations Using Voyager and ACE Observations

As part of a published effort to study low-frequency magnetic waves excited by newborn interstellar pickup ions seen by the Voyager spacecraft, we developed a set of control intervals that represent the background turbulence when the observations are not dominated by wave excitation. This paper begins an effort to better understand solar wind turbulence from 1 to 45 au while spanning greater than one solar cycle. Here, we first focus on the diagnostics marking the onset of dissipation. This includes an expected break in the power spectrum at frequencies greater than the proton cyclotron frequency and a resultant steepening of the spectrum at higher frequencies. Contrary to what is established at 1 au, we only see the spectral break in rare instances. The expected scaling of the spectral index with the turbulence rate is seen, but it is not as clearly established as it was at 1 au. We also find that both Voyager data from 1 to 45 au and Advanced Composition Explorer data from 1 au show significant bias of the magnetic helicity at dissipation scales when the dissipation-range power-law spectral index steepens. We conclude that dissipation dynamics are similar throughout the heliosphere in so far as we have examined to date.

Pine, Zackary B.↗
NASA NTRS1990

NASA SERC 1990 Symposium on VLSI Design

This document contains papers presented at the first annual NASA Symposium on VLSI Design. NASA's involvement in this event demonstrates a need for research and development in high performance computing. High performance computing addresses problems faced by the scientific and industrial communities. High performance computing is needed in: (1) real-time manipulation of large data sets; (2) advanced systems control of spacecraft; (3) digital data transmission, error correction, and image compression; and (4) expert system control of spacecraft. Clearly, a valuable technology in meeting these needs is Very Large Scale Integration (VLSI). This conference addresses the following issues in VLSI design: (1) system architectures; (2) electronics; (3) algorithms; and (4) CAD tools.

Maki, Gary K.↗
NASA NTRS1996

Validation of the ASTER Thermal Infrared Surface Radiance Data Product

The Advanced Spaceborne Thermal Emission and reflection Radiometer (ASTER) is a 14 channel high spatial resolution instrument selected for flight on the EOS AM-1 platform...To provide an objective assessment of the validity of the atmospheric correction, in situ measurements of water surfaces under a variety of atmospheric conditions will be used to estimate the surface leaving radiance at the scale of an ASTER pixel... These measurements and the spectral emissivity of the water will be combined with the relative system spectral response to provide and estimater of thermal infrared surface leaving radiance for each ASTER thermal channel. An example of this approach using a multichannel thermal aircraft scanner as a stand in for ASTER will be described.

ASTER↗
NASA NTRS2022

Science Autonomy for Ocean Worlds Astrobiology: A Perspective

Astrobiology missions to ocean worlds in our solar system must overcome both scientific and technological challenges due to extreme temperature and radiation conditions, long communication times, and limited bandwidth. While such tools could not replace ground-based analysis by science and engineering teams, machine learning algorithms could enhance the science return of these missions through development of autonomous science capabilities. Examples of science autonomy include onboard data analysis and subsequent instrument optimization, data prioritization (for transmission), and real-time decision-making based on data analysis. Similar advances could be made to develop streamlined data processing software for rapid ground-based analyses. Here we discuss several ways machine learning and autonomy could be used for astrobiology missions, including landing site selection, prioritization and targeting of samples, classification of “features” (e.g., proposed biosignatures) and novelties (uncharacterized, “new” features, which may be of most interest to agnostic astrobiological investigations), and data transmission.

ocean worlds↗
NASA NTRS2013

Modeling Longitudinal Data Containing Non-Normal Within Subject Errors

The mission of the National Aeronautics and Space Administration’s (NASA) human research program is to advance safe human spaceflight. This involves conducting experiments, collecting data, and analyzing data. The data are longitudinal and result from a relatively few number of subjects; typically 10 – 20. A longitudinal study refers to an investigation where participant outcomes and possibly treatments are collected at multiple follow-up times. Standard statistical designs such as mean regression with random effects and mixed–effects regression are inadequate for such data because the population is typically not approximately normally distributed. Hence, more advanced data analysis methods are necessary. This research focuses on four such methods for longitudinal data analysis: the recently proposed linear quantile mixed models (lqmm) by Geraci and Bottai (2013), quantile regression, multilevel mixed–effects linear regression, and robust regression. This research also provides computational algorithms for longitudinal data that scientists can directly use for human spaceflight and other longitudinal data applications, then presents statistical evidence that verifies which method is best for specific situations. This advances the study of longitudinal data in a broad range of applications including applications in the sciences, technology, engineering and mathematics fields.

Feiveson, Alan↗
NASA NTRS2023

A GeoNEX-Based High-Spatiotemporal-Resolution Product of Land Surface Downward Shortwave Radiation and Photosynthetically Active Radiation

Surface downward shortwave radiation (DSR) and photosynthetically active radiation (PAR) play critical roles in the Earth’s surface processes. As the main inputs of various ecological, hydrological, carbon, and solar photovoltaic models, increasing requirements for high-spatiotemporal-resolution DSR and PAR es- timation with high accuracy have been observed in recent years. However, few existing products satisfy all of these requirements. This study employed a well-established physical-based lookup table (LUT) approach to the GeoNEX gridded top-of-atmosphere bidirectional reflectance factor data acquired by the Advanced Hi- mawari Imager (AHI) and Advanced Baseline Imager (ABI) sensors. It produced a data product of DSR and PAR over both AHI and ABI coverage at an hourly temporal step with a 1 km spatial resolution. GeoNEX DSR data were validated over 63 stations, and GeoNEX PAR data were validated over 27 stations. The vali- dation showed that the new GeoNEX DSR and PAR products have accuracy higher than other existing prod- ucts, with root mean square error (RMSE) of hourly GeoNEX DSR achieving 74.3Wm−2 (18.0%), daily DSR estimation achieving 18.0 W m−2 (9.2 %), hourly GeoNEX PAR achieving 34.9 W m−2 (19.6 %), and daily PAR achieving 9.5 W m−2 (10.5 %). The study also demonstrated the application of the high-spatiotemporal- resolution GeoNEX DSR product in investigating the spatial heterogeneity and temporal variability of surface solar radiation. The data product can be freely accessed through the NASA Advanced Supercomputing Division GeoNEX data portal: https://data.nas.nasa.gov/geonex/geonexdata/GOES16/GEONEX-L2/DSR-PAR/ (last ac- cess: 12 March 2023) and https://data.nas.nasa.gov/geonex/geonexdata/HIMAWARI8/GEONEX-L2/DSR-PAR/ (last access: 12 March 2023) (https://doi.org/10.5281/zenodo.7023863; Wang and Li, 2022).

Surface downward shortwave radiation (DSR)↗
DOE OSTI2019

Data and Models: A Framework for Advancing AI in Science

On June 5, 2019, the Office of Science (SC) organized a one-day roundtable to focus on enhancing access to high-quality and fully traceable research data, models, and computing resources to increase the value of such resources for artificial intelligence (AI) research and development and the SC mission.1 In this report, we consider AI to be inclusive of, for example, machine learning (ML), deep learning (DL), neural networks (NN), computer vision, and natural language processing (NLP). We consider “data for AI” to mean the digital artifacts used to generate AI models and/or employed in combination with AI models during inference. In part, this roundtable was motivated by the recognition that a large portion of science data currently are not well suited for AI.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1991

Advanced Solid-State Array Spectrometer (ASAS) data sets from the 1990 field season: A unique look at two forested ecosystems

The Advanced Solid-state Array Spectrometer (ASAS) is a pointable imaging spectrometer which uses a solid-state array to acquire imagery of terrestrial targets in 29 spectral bands from .4 to .8 microns. Performance and calibration of the instrument are described. The ASAS data sets obtained in 1990 provide a unique look at forest canopies from two different forest regions of the North America continent under varying temporal, spectral, and bidirectional conditions. These data sets will be used to study such parameters as the albedo of forest canopies, the dynamics of scene radiation due to factors such as canopy architecture, moisture stress, leaf chemistry, topography, and understory composition.

Walthall, Charles L.↗
NASA NTRS1989

Proceedings of the Scientific Data Compression Workshop

Continuing advances in space and Earth science requires increasing amounts of data to be gathered from spaceborne sensors. NASA expects to launch sensors during the next two decades which will be capable of producing an aggregate of 1500 Megabits per second if operated simultaneously. Such high data rates cause stresses in all aspects of end-to-end data systems. Technologies and techniques are needed to relieve such stresses. Potential solutions to the massive data rate problems are: data editing, greater transmission bandwidths, higher density and faster media, and data compression. Through four subpanels on Science Payload Operations, Multispectral Imaging, Microwave Remote Sensing and Science Data Management, recommendations were made for research in data compression and scientific data applications to space platforms.

Ramapriyan, H. K.↗
NASA NTRS1989

General-Purpose Electronic System Tests Aircraft

Versatile digital equipment supports research, development, and maintenance. Extended aircraft interrogation and display system is general-purpose assembly of digital electronic equipment on ground for testing of digital electronic systems on advanced aircraft. Many advanced features, including multiple 16-bit microprocessors, pipeline data-flow architecture, advanced operating system, and resident software-development tools. Basic collection of software includes program for handling many types of data and for displays in various formats. User easily extends basic software library. Hardware and software interfaces to subsystems provided by user designed for flexibility in configuration to meet user's requirements.

Glover, Richard D.↗
DOE OSTI2022

Data from: "Lab and Field Warming Similarly Advance Germination Date and Limit Germination Rate for High and Low Elevation Provenances of Two Widespread Subalpine Conifers"

This archive contains data used to draw conclusions in “Lab and Field Warming Similarly Advance Germination Date and Limit Germination Rate for High and Low Elevation Provenances of Two Widespread Subalpine Conifers”, by Kueppers et al. 2017. Cone collection and field experiments were conducted on Niwot Ridge, Colorado, with the latter completed within the Alpine Treeline Warming Experiment (ATWE). Laboratory germination experiments were conducted at the University of California Merced. Geospatial files are also provided for additional geographical context.There are four data file formats in this package: comma-separated values (.csv), Microsoft Excel (.xlsx), keyhole markup language (.kml), and ESRI shapefile (.shp). The latter two are geospatial file formats. .csv files can be opened using any simple text editor program such as TextEdit (Mac) and Notepad (Windows), and .xlsx files can be opened using Microsoft Excel or Google Sheets. The .kml file contains coordinate data, and is compatible with Google Earth and Google Maps. ESRI shapefiles (.shp) are compatible with any geospatial software able to read the file type, such as QGIS and ESRI’s ArcGIS Suite. This data user’s guide is available in as a .pdf, and can be opened using software such as Adobe Acrobat Reader.-----------------------------------------------------------------------------------------------------------------------------------Accurately predicting upslope shifts in subalpine tree ranges with warming requires understanding how future forest populations will be affected by climate change, as these are the seed sources for new tree line and alpine populations. Early life history stages are particularly sensitive to climate and are also influenced by genetic variation among populations. We tested the climate sensitivity of germination and initial development for two widely distributed subalpine conifers, using controlled-environment growth chambers with one temperature regime from subalpine forest in the Colorado Rocky Mountains and one 5 °C warmer, and two soil moisture levels. We tracked germination rate and timing, rate of seedling development, and seedling morphology for two seed provenances separated by ~300 m elevation. Warming advanced germination timing and initial seedling development by a total of ~2 weeks, advances comparable to mean differences between provenances. Advances were similar for both provenances and species; however, warming reduced the overall germination rate, as did low soil moisture, only for Picea engelmannii. A three-year field warming and watering experiment planted with the same species and provenances yielded responses qualitatively consistent with the lab trials. Together these experiments indicate that in a warmer, drier climate, P. engelmannii germination, and thus regeneration, could decline, which could lead to declining subalpine forest populations, while Pinus flexilis forest populations could remain robust as a seed source for upslope range shifts.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1972

Evaluation of zirconia, thoria and zirconium diboride for advanced resistojet use

A literature survey was conducted to collect material properties data on all advanced high temperature materials. Three of these, Y2O3-stabilized ZrO2, ThO2, and ZrB2 with additives of C and SiC were selected for further study. Stabilized ZrO2 and ThO2 were found to have higher temperature oxidation resistance than any metal and great potential for use in advanced biowaste resistojets. ZrO2 has a lower electrical resistivity and sublimation and a higher creep endurance strength. ZrO2 and ThO2 tubular heat exchangers, electrically heated indirectly, were evaluated in short tests to about 1900 K in flowing CO2. ZrO2 was subjected to N2, H2, H2O and vacuum as well. X-ray diffraction and fluorescence analyses were made. The metal-to-ceramic seal technology for ZrO2 and ThO2 was developed using chemical vapor deposition of tantalum for metallizing and 82 Au - 18 Ni filler braze.

Page, R. J.↗
DOE OSTI2022

Big Data Seismology

The discipline of seismology is based on observations of ground motion that are inherently undersampled in space and time. Our basic understanding of earthquake processes and our ability to resolve 4D Earth structure are fundamentally limited by data volume. Currently, Big Data Seismology is an emergent revolution involving the use of large, data-dense inquiries that is providing new opportunities to make fundamental advances in these areas. This article reviews recent scientific advances enabled by Big Data Seismology through the context of three major drivers: the development of new data-dense sensor systems, improvements in computing, and the development of new types of techniques and algorithms. Each driver is explored in the context of both global and exploration seismology, alongside collaborative opportunities that combine the features of long-duration data collections (common to global seismology) with dense networks of sensors (common to exploration seismology). The review explores some of the unique challenges and opportunities that Big Data Seismology presents, drawing on parallels from other fields facing similar issues. Finally, recent scientific findings enabled by dense seismic data sets are discussed, and we assess the opportunities for significant advances made possible with Big Data Seismology. This review is designed to be a primer for seismologists who are interested in getting up-to-speed with how the Big Data revolution is advancing the field of seismology.

58 GEOSCIENCES↗
DOE OSTI2026

Reliability Assessment of Solid-State Circuit Breakers (CRADA CRD-21-21469, Project 4 Final Report)

Growth in power requirements and the complexity of emerging distribution systems are creating the need for new solid-state products for many applications. The qualification requirements, testing standards and life-cycle management practices of solid-state devices used in protection applications is not established. The project will leverage newly developed accelerated testing capabilities design specifically for protection applications to generate large data sets that will enable advanced digital techniques for data analysis and embedded health monitoring.

14 SOLAR ENERGY↗
NASA NTRS1993

Data management for support of the Oregon Transect Ecosystem Research (OTTER) project

Management of data collected during projects that involve large numbers of scientists is an often overlooked aspect of the experimental plan. Ecosystem science projects like the Oregon Transect Ecosystem Research (OTTER) Project that involve many investigators from many institutions and that run for multiple years, collect and archive large amounts of data. These data range in size from a few kilobytes of information for such measurements as canopy chemistry and meteorological variables, to hundreds of megabytes of information for such items as views from multi-band spectrometers flown on aircraft and scenes from imaging radiometers aboard satellites. Organizing and storing data from the OTTER Project, certifying those data, correcting errors in data sets, validating the data, and distributing those data to other OTTER investigators is a major undertaking. Using the National Aeronautics and Space Administration's (NASA) Pilot Land Data System (PLDS), a Support mechanism was established for the OTTER Project which accomplished all of the above. At the onset of the interaction between PLDS and OTTER, it was not certain that PLDS could accomplish these tasks in a manner that would aid researchers in the OTTER Project. This paper documents the data types that were collected under the auspices of the OTTER Project and the procedures implemented to store, catalog, validate, and certify those data. The issues of the compliance of investigators with data-management requirements, data use and certification, and the ease of retrieving data are discussed. We advance the hypothesis that formal data management is necessary in ecological investigations involving multiple investigators using many data gathering instruments and experimental procedures. The issues and experience gained in this exercise give an indication of the needs for data management systems that must be addressed in the coming decades when other large data-gathering endeavors are undertaken by the ecological science community.

Skiles, J. W.↗
DOE OSTI2020

Open-Source High-Fidelity Aggregate Composite Load Models of Emerging Load Behaviors for Large-Sale Analysis

The goal of this project is to accurately model the dynamic loads for power system planning and operation and to address the challenges inherent in such modeling. Existing load models are inadequate to handle the increasing proliferation of residential air conditioner loads and distributed energy resources, the emerging trends of price-responsive demand, and the growing importance of protective devices in equipment and buildings. A need has emerged to develop a fundamentally new class of load models and next-generation data tools. This work proposes to develop a set of regional–level, scalable open source load models and tools, including large-scale aggregate load protection, concept of price responsive demand, advanced load composition data, next-generation load model data tools, and advanced composite load model calibration and validation frameworks to address new challenges in the representation of next-generation load models.

24 POWER TRANSMISSION AND DISTRIBUTION↗