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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 1,315 records · Page 73
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

TRACER-Tethersonde VOC data

One objective of TRACER-Tethersonde campaign was to deploy a volatile organic compound (VOC) sampler on the Tethered Balloon System (TBS) to create vertical profiles and characterize VOC composition. Volatile organic compounds (VOCs) are highly reactive precursor species that undergo atmospheric processing to form secondary products, including aerosol. VOC emissions are influenced by many factors that include but are not limited to temperature, time of day, local anthropogenic activities, and local vegetation, which result in large spatiotemporal variability. The vertical distribution of volatile species is crucial for understanding gas-phase processing for particle production but challenging to accomplish using currently available sampling devices. The standalone sampler built during the campaign enabled the execution of robust experimental designs, including sample collection using resin tubes at multiple altitudes on subsequent flights. Following field sampling, resin tubes were transported back to Baylor University for chemical analysis using a Markes International thermal desorption unit coupled with a gas chromatograph-tandem mass spectrometer (Thermo Scientific). The target analyte list includes biogenic and anthropogenic VOCs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Back Trajectories during SAIL

This data set contains air mass back trajectories generated during the Surface Atmosphere Integrated Field Laboratory (SAIL) campaign using the Hybrid Single-Particle Lagrangian Integrated Trajectory model (HYSPLIT, Stein et al. 2015, Rolph et al. 2017). For each hour from January 1, 2021 to June 30, 2023, a 96-hour back trajectory was initiated at the SAIL sampling site, starting 100 m above ground level. The calculations used the GDAS meteorological data set with model vertical velocity. The files within this dataset show location and meteorological parameters of the back trajectory analysis. There are 21 columns within each data file. The first 2 columns pertain to back trajectory parameters: the trajectory number (which is always 1) and the meteorological grid number. The next 9 columns pertain to spatiotemporal information: the year, month, day, hour (0-23), and minute of the trajectory, the previous time of the trajectory (in negative hours), and the airmass location (latitude, longitude, and height in m AGL). The rest of the parameters within each file pertains to surface and meteorological characteristics of the airmass: pressure (in hPa), potential temperature (in K), temperature (in K), precipitation rate (in mm/hr), mixing depth (in m), relative humidity (in % relative to liquid water), specific humidity (in g/kg), H2O mixing ratio (in g/kg), underlying terrain height (in meters above sea level), and incoming radiation (in W/m^2).

back trajectory↗
DOE OSTI2026

BNF C-band Scanning ARM Precipitation Radar 2nd Generation (CSAPR-2) Extracted Radar Columns and In-Situ Sensors (RadCLss)

Corrected Moments in Antenna Coordinates (CMAC) calculates quantitative precipitation estimates (QPE) from empirical relationships based on equivalent radar reflectivity factor, specific differ- ential phase, and specific attenuation. To evaluate these empirical relationships, the Extracted Radar Columns and In-Situ Sensors (RADclss) product was developed. Utilizing Py-ART, RAD- clss extracts CMAC radar columns above various ARM and partner locations. These columns are then spatiotemporally synced with in-situ observations at the surface utilizing the Atmospheric data Community Toolkit (ACT; Theisen et al. 2025), allowing direct comparison of radar parameters with rain gauges and laser disdrometers for further investigation.

bankhead↗
DOE OSTI2025

GreenSight WxHive Unmanned Aerial System (UAS) Atmospheric Profiling at the SGP Central Facility

The GreenSight WxHive is capable of flying multiple nanodrones simultaneously to provide spatiotemporal atmospheric sampling. During the WH2yMSIE campaign, the WxHive would fly up to 5 nanodrones at once, performing profiling within the planetary boundary layer over the ARM SGP Central Facility site. The measurements provided by the WxHive include latitude, longitude, altitude, pressure, temperature, humidity, and wind speed and direction. See the attached WeatherHive User Guide for more details about the instrument and measurements.

Air pressure↗
DOE OSTI2026

A Climatology of Dust Deposition in the Upper Colorado River Basin for February-May 1980-2023

This data set is a long-term climatology of the average monthly total dust deposition, wet and dry, for the months of February-May 1980-2023 pulled from the MERRA-2 reanalysis data set over the Upper Colorado River Basin. This data set can be used to study the long-term spatiotemporal patterns of dust deposition, especially on snow. This data set is associated with the preprint article “A multi-decadal climatology of dust-on-snow from wet deposition in the Upper Colorado River Basin”.

dry_dust_deposition↗
DOE OSTI2022

IM3/HyperFACETS Thermodynamic Global Warming (TGW) Simulation Datasets

Publication For a thorough description of the methods, see the peer-reviewed paper: Jones, A.D., Rastogi, D., Vahmani, P. et al. Continental United States climate projections based on thermodynamic modification of historical weather. Sci Data 10, 664 (2023). https://doi.org/10.1038/s41597-023-02485-5 Overview The IM3 / HyperFACETS climate simulations provide 40-year historical (1980-2019) as well as four 80-year future simulations (2020-2099) over the U.S. The future simulations are split into near (2020-2059) and far future (2060-2099) segments. The future scenarios span a range of plausible changes in future climate (both Global Circulation Model (GCM) and Representative Concentration Pathways/Shared Socioeconomic Pathway (RCP/SSP) dimensions). The simulations provide climate variables with high spatiotemporal resolution (25 hourly variables and 207 3-hourly variables at 12 km2). The datasets are generated using dynamical downscaling with the WRF (Weather Research and Forecasting) model (version 4.2.1) and therefore preserve physical consistency across variables. WRF is a state-of-the-art, fully compressible, non-hydrostatic, mesoscale numerical weather prediction model. WRF is coupled with an urban canopy model (UCM), which resolves urban surfaces. The future scenarios were developed using a thermodynamic global warming approach where past events are replayed under a range of future warming conditions. These scenarios therefore provide a perspective on potential increases in extreme event intensity, geographic scope, and duration, with previously non-extreme conditions potentially crossing new thresholds to be considered extreme by today's standards. This approach is not intended to estimate future changes in extreme event frequency that might result from changes in large-scale atmospheric dynamics. This dataset has NOT been bias corrected. A bias corrected version of selected variables is under development and will be released here when available. Scenarios Files Data for each scenario is provided in weekly NetCDF files. 25 variables are available at hourly resolution, and 207 variables are available at three-hourly resolution. Spatial resolution is 12km and spans the conterminous United States (CONUS), including some areas of Canada and Mexico, resulting in a grid of 424 by 299 cells. The spatial projection is a Lambert Conformal Conic with the following proj-string: "+proj=lcc +lat_0=40.0000076293945 +lon_0=-97 +lat_1=30 +lat_2=45 +x_0=0 +y_0=0 +R=6370000 +units=m +no_defs". The available scenarios and simulation periods are listed below: historical | 1980 - 2019 rcp45cooler | 2020 - 2059 rcp45cooler | 2060 - 2099 rcp45hotter | 2020 - 2059 rcp45hotter | 2060 - 2099 rcp85cooler | 2020 - 2059 rcp85cooler | 2060 - 2099 rcp85hotter | 2020 - 2059 rcp85hotter | 2060 - 2099 * The first year (1979, 2019, and 2059) of data within each scenario represents a model warmup period and should not be used. These are located in the `spinup_files` directory. Historical year 2020 is considered an extra year of data beyond the simulation period and can be found in the `additional_files` directory. For information on specific variables and a more in-depth discussion of methodology, please refer to the data landing page at https://tgw-data.msdlive.org. Delta Warming Files The global and CONUS warming deltas for each scenario are provided in degrees Celsius annually and monthly. Restart Files Yearly restart files are provided for each scenario which can be used to restart the WRF model at a particular point in time. Spinup Files The first year of data within each simulation period represents a model warmup period and should not be used. The files are provided here for the sake of reproducibility. Additional Files Additional years of data are provided as an extension of the historic simulation.

Jones, Andrew D.↗
DOE OSTI2026

Integration of GOES Data for Solar Resource Assessment of the Contiguous United States

The National Solar Radiation Database (NSRDB), produced by the National Laboratory of the Rockies (NLR), provides high-resolution solar resource data for the contiguous United States (CONUS) using Geostationary Operational Environmental Satellite (GOES) East and West observations. This study evaluates the integration of multi-satellite data within the GOES-East/West overlap regions, where conventional longitude-based selection methods often produce an artificial boundary seam. Our results demonstrate that an advanced blending algorithm, which incorporates sun-satellite scattering angles and satellite viewing zenith angles, improves NSRDB accuracy and creates a spatially continuous dataset. Validation against ground-based irradiance measurements reveals reductions in both percentage error (PE) and normalized Root Mean Square Error (nRMSE), particularly in the central United States. The dynamical integration of multi-satellite data provides a robust foundation for more precise modeling of solar resource and improved spatiotemporal analysis of solar ramp across the CONUS.

14 SOLAR ENERGY↗
NASA NTRS1973

Optimum detection of an optical image on a photoelectric surface.

The image-detecting performance of an optimum counting detector is compared with that of a threshold detector and that of a detector basing its decisions on the total number of photoelectrons from a finite area of the image. The illuminance of the image is assumed to have a Gaussian spatial distribution. The optimum detector works with the pristine datum (and not with the photoelectric response) which is the spatiotemporal electromagnetic field at the aperture of the observing optical instrument. It is shown that little is to be gained by using details of the illuminance distribution beyond the crude knowledge of its breadth as embodied in a simple counter of emitted photoelectrons. All three detectors exhibit accordingly about the same reliability.

Helstrom, C. W.↗
NASA NTRS1983

The window of visibility: A psychological theory of fidelity in time-sampled visual motion displays

Many visual displays, such as movies and television, rely upon sampling in the time domain. The spatiotemporal frequency spectra for some simple moving images are derived and illustrations of how these spectra are altered by sampling in the time domain are provided. A simple model of the human perceiver which predicts the critical sample rate required to render sampled and continuous moving images indistinguishable is constructed. The rate is shown to depend upon the spatial and temporal acuity of the observer, and upon the velocity and spatial frequency content of the image. Several predictions of this model are tested and confirmed. The model is offered as an explanation of many of the phenomena known as apparent motion. Finally, the implications of the model for computer-generated imagery are discussed.

Watson, A. B.↗
NASA NTRS1983

What does the eye see best?

The quantum efficiency of the human eye is measured for detecting a wide variety of spatiotemporal patterns using foveal vision in bright light. The performance of an ideal visual detector whose weighting function is matched to the signal is analyzed in the abstract, and the conditions of a two-interval forced-choice experiment are described. The best stimulus found is a small, briefly exposed circular patch of sinusoidal grating having a spatial frequency of about 7 c/deg, drifting at about 4 Hz. It is proposed that this is the weighting function of the most efficient human contrast detector. This function resembles the receptive field sensitivity profiles of many cortical neurons. The detectors resemble those derived from other recent experiments on both detection and discrimination and may account for a broad range of previous psychophysical results.

Watson, A. B.↗
NASA NTRS1983

Reduction of display artifacts by random sampling

The application of random-sampling techniques to remove visible artifacts (such as flicker, moire patterns, and paradoxical motion) introduced in TV-type displays by discrete sequential scanning is discussed and demonstrated. Sequential-scanning artifacts are described; the window of visibility defined in spatiotemporal frequency space by Watson and Ahumada (1982 and 1983) and Watson et al. (1983) is explained; the basic principles of random sampling are reviewed and illustrated by the case of the human retina; and it is proposed that the sampling artifacts can be replaced by random noise, which can then be shifted to frequency-space regions outside the window of visibility. Vertical sequential, single-random-sequence, and continuously renewed random-sequence plotting displays generating 128 points at update rates up to 130 Hz are applied to images of stationary and moving lines, and best results are obtained with the single random sequence for the stationary lines and with the renewed random sequence for the moving lines.

Ahumada, A. J., Jr.↗
NASA NTRS1988

Neurophysiological predictors of quality of performance

New signal processing technologies have been developed to measure spatiotemporal neurocognitive processes of the human brain. In one experiment, application of these technologies produced measurements of distributed preparatory sets which predicted the accuracy of subsequent performance. In another experiment, neuroelectric changes were found in Air Force test pilots during the incipient stages of fatigue before behavior had severely degraded.

Gevins, Alan S.↗
NASA NTRS1988

The observed characteristics of flare energy release. I - Magnetic structure at the energy release site

It is shown that flaring activity as seen in X-rays usually encompasses two or more interacting magnetic bipoles within an active region. Soft and hard X-ray spatiotemporal evolution is considered as well as the time dependence of the thermal energy content in different magnetic bipoles participating in the flare, the hardness and impulsivity of the hard X-ray emission, and the relationship between the X-ray behavior and the strength and 'observable shear' of the magnetic field. It is found that the basic structure of a flare usually consists of an initiating closed bipole plus one or more adjacent closed bipoles impacted against it.

Machado, Marcos E.↗
NASA NTRS1988

Capacity for patterns and sequences in Kanerva's SDM as compared to other associative memory models

The information capacity of Kanerva's Sparse Distributed Memory (SDM) and Hopfield-type neural networks is investigated. Under the approximations used here, it is shown that the total information stored in these systems is proportional to the number connections in the network. The proportionality constant is the same for the SDM and Hopfield-type models independent of the particular model, or the order of the model. The approximations are checked numerically. This same analysis can be used to show that the SDM can store sequences of spatiotemporal patterns, and the addition of time-delayed connections allows the retrieval of context dependent temporal patterns. A minor modification of the SDM can be used to store correlated patterns.

Keeler, James D.↗
NASA NTRS1990

Determining Sense Of Motion In Robotic Vision

Image-processing algorithms based partly on natural visual/mental processes. Proposed digital image-processing scheme determines sense of motion of object in image along one coordinate axis (left to right or right to left) with respect to background in image. Image encoded by passing it through spatiotemporal filters, including nonlinear contrast function with threshold. Nonlinear response to sums and differences of imagery processed through even and odd spatial filters indicates sense of motion.

Lawton, Teri B.↗
NASA NTRS1987

Capacity for patterns and sequences in Kanerva's SDM as compared to other associative memory models

The information capacity of Kanerva's Sparse Distributed Memory (SDM) and Hopfield-type neural networks is investigated. Under the approximations used, it is shown that the total information stored in these systems is proportional to the number connections in the network. The proportionality constant is the same for the SDM and Hopfield-type models independent of the particular model, or the order of the model. The approximations are checked numerically. This same analysis can be used to show that the SDM can store sequences of spatiotemporal patterns, and the addition of time-delayed connections allows the retrieval of context dependent temporal patterns. A minor modification of the SDM can be used to store correlated patterns.

Keeler, James D.↗
NASA NTRS1990

Cockpit Ocular Recording System (CORS)

The overall goal was the development of a Cockpit Ocular Recording System (CORS). Four tasks were used: (1) the development of the system; (2) the experimentation and improvement of the system; (3) demonstrations of the working system; and (4) system documentation. Overall, the prototype represents a workable and flexibly designed CORS system. For the most part, the hardware use for the prototype system is off-the-shelf. All of the following software was developed specifically: (1) setup software that the user specifies the cockpit configuration and identifies possible areas in which the pilot will look; (2) sensing software which integrates the 60 Hz data from the oculometer and heat orientation sensing unit; (3) processing software which applies a spatiotemporal filter to the lookpoint data to determine fixation/dwell positions; (4) data recording output routines; and (5) playback software which allows the user to retrieve and analyze the data. Several experiments were performed to verify the system accuracy and quantify system deficiencies. These tests resulted in recommendations for any future system that might be constructed.

Rothenheber, Edward↗