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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 1,081 records · Page 60

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NASA NTRS1981

Mesoscale aspects of jet streak coupling and implications for the short term forecasting of severe convective storms

An analysis of a tornado outbreak in Wichita Falls, Texas was analyzed. The coupling of upper and lower tropospheric jet streaks, leading to severe storm outbreaks is illustrated. The high resolution SESAME data sets indicate that mass and momentum adjustments which couple upper and lower tropospheric jets occur within a 3 to 6 hr time frame over a 100 to 500 km domain, and establish the role of isallobaric forcing in the storm development. It is suggested that the output rate of data from the existing 12 hr network be increased to provide better temporal resolution of wind, mass and moisture data.

Uccellini, L. W.↗

DOE OSTI2024

Imaging and Segmenting Grains and Subgrains Using Backscattered Electron Techniques

We present two new methods of processing data from backscattered electron signals in a scanning electron microscope to image grains and subgrains. The first combines data from multiple backscattered electron images acquired at different specimen geometries to (1) better reveal grain boundaries in recrystallized microstructures and (2) distinguish between recrystallized and unrecrystallized regions in partially recrystallized microstructures. The second utilizes spherical harmonic transform indexing of electron backscatter diffraction patterns to produce high angular resolution orientation data that enable the characterization of subgrains. Subgrains are produced during high-temperature plastic deformation and have boundary misorientation angles ranging from a few degrees down to a few hundredths of a degree. Here, we also present an algorithm to automatically segment grains from combined backscattered electron image data or grains and subgrains from high angular resolution electron backscatter diffraction data. Together, these new techniques enable rapid measurements of individual grains and subgrains from large populations.

36 MATERIALS SCIENCE↗

NASA NTRS1986

Influence of the Yukon River on the Bering Sea

The purpose is to use satellite data to study relationships between discharge of the Yukon River to currents and biologic productivity in the northern Bering Sea. Amended specific objectives are: to develop thermal, sediment and chlorophyll surface maps using thematic mapping (TM) data of the discharge of the Yukon River and the Alaska Coastal Current during the ice free season; to develop a historical model of the distribution of the Yukon River discharge and the Alaska Coastal Current using LANDSAT multispectral scanner (MMS) and NOAA satellite imagery; and to use high resolution TM data to define the surface dynamics of the front between the Alaska Coastal Current and the Bering Shelf/Anadyr Current. LANDSAT MSS and TM, and Advanced Very High Resolution Radiometer (AVHRR) data were recorded during the 1985 ice-free period. The satellite data coincided with shipboard measurements acquired by Inner Self Transfer and Recycling scientists. Circumstances were such, that on July 5 and July 22, all three sensors recorded data that has been registered to a common map projection and map base, then contrast stretched, color composited, and density sliced.

Dean, K.↗

NASA NTRS1986

Influence of the Yukon River on the Bering Sea

The relationships between the discharge of the Yukon River to the currents and biological productivity in the northern Bering Sea were studied. Specific objectives were: to develop thermal, sediment, and chlorophyll surface maps using Thematic Mapper (TM) data of the discharge of the Yukon River and the Alaskan Coastal Current during the ice free season; to develop a historical model of the distribution of the Yukon River discharge and the Alaskan Coastal Current using LANDSAT Multispectral band scanner (MSS) and NOAA satellite imagery; and to use high resolution TM data to define the surface dynamics of the front between the Alaskan Coastal Current and the Bering Shelf/Anadyr Current. LANDSAT MSS, TM, and Advanced Very High Resolution Radiometer (AVHRR) data were recorded during the 1985 ice free period. The data coincided with shipboard measurements acquired by Inner Shelf Transfer and Recycling (ISTAR) project scientists. An integrated model of the distribution of turbid water discharged from the Yukon River was compiled. A similar model is also being compiled for the Alaskan Coastal and Bering Shelf/Anadyr water masses based on their thermal expressions seen on AVHRR imagery.

Dean, K.↗

NASA NTRSDate not supplied

Advances to a Global Agroclimatology Solar Insolation and Meteorological Parameter Data Base: Improved Solar Irradiance up to Hourly Temporal Resolution

A primary objective of NASA’s Prediction of Worldwide Energy Resource (POWER) project is to facilitate the use of NASA Earth Science data holdings within the energy, agricultural, and architectural industries. To this end daily averaged solar data from several NASA projects and metrological data from a NASA assimilation model have long been reformatted and via a user friendly web based data portal (https://power.larc.nasa.gov) at the native resolution of each data products. Potential users can access solar and metrological data in a column formatted DSSAT ASCII format by entering single site specific coordinates or from an area by entering the appropriate area coordinates. Upgrades to the POWER data portal have been implemented that result in a complete upgrade of the base solar insolation data products. From the years 1984 through 2000, a new version of the NASA/GEWEX Surface Radiation Budget (SRB) and Clouds is utilized that reduces the RMS relative to surface measurements. Additionally, Clouds and the Earth’s Radiant Energy System (CERES) SYNoptic 1x1 Degree (SYN1Deg) data products are utilized starting from January 1, 2001 through 3 months of real-time. The CERES Fast Longwave and SHortwave radiative Fluxes (FLASHFlux) is still used to provided daily data spanning from the end of SYN1Deg to within 7 days of real-time. Meteorological parameters now are taken from the NASA Modern Era Retrospective-analysis for Research and Applications (MERRA-2) data set which provides higher resolution data products (hourly and 0.5 x 625 degree) covering the entire globe. Besides updating the solar and meteorological data products, this new version features new data products such as photosynthetically active radiation (PAR), more cloud information, estimates of soil temperatures and improved options for long-term climatological data requests. More than 36+ years daily time slices are included in the combined solar and meteorological data sets. However, perhaps the most important innovation of the POWER GIS-enabled Web Services is the provision of hourly solar and meteorological data products beginning in Jan 1, 2001. The hourly values will enable more detailed modeling and crop analysis that incorporates the diurnal variability of these parameters. The new capability is made possible by utilizing both the CERES SYN1Deg and MERRA-2 data products that include parameters at these resolutions. An assessment of both the meteorological and the solar irradiance data are based upon comparisons with globally distributed surface observations. The meteorological observations from the National Center for Environmental Information’s “Integrated Surface Database” as well as the “Global Summary of the Day” (GSOD) data files. The estimates of solar insolation are compared to the Baseline Solar Radiation Network (BSRN) and other high quality surface measurement networks. Results from the uncertainty assessments demonstrates that the NASA’s meteorological and solar irradiance data can represent a viable alternative to surface observations, particularly in data sparse regions of the world.

solar irradiance↗

NASA NTRS1987

Rarefied aerodynamics and upper atmospheric flight results from the Orbiter High Resolution Accelerometer Package experiment

Data from the High Resolution Accelerometer Package (HiRAP) experiment on the Space Shuttle Orbiter have been analyzed for 10 flights to produce lift-drag (L/D) ratios in the free molecule, transition, and continuum flow flight regimes. Freestream density is also obtained in the altitude range from 60 km to 160 km using an aerodynamic model based upon earlier flight analysis of accelerometer data. The results of the L/D analysis of the latest four flights have been compared with the aerodynamic model developed from the first six HiRAP missions. The new data agree with the established flight-derived model, thereby validating earlier analysis. However, the arithmetic mean of the 10 flight-derived L/D values in the free molecular flow regime is 0.053 (+ or - 0.1) as compared to the initial value of 0.10 (+ or - 0.3), determined from STS-6. Updates to the Orbiter aerodynamic model values and calibration factors have been incorporated into the density calculations for all 10 flights to provide realistic absolute density. The derived density altitude profiles, which have been normalized to the U.S. Standard Atmosphere 1976, are characterized by a large amplitude wave pattern relative to the standard as seen in the initial flight analysis.

Blanchard, R. C.↗

NASA NTRS1972

S-band transponder experiment

The experiment which derives data from three lunar-orbiting objects, the command-service module (CSM), the lunar module (LM), and the subsatellite in the S-band is described. Each provides detailed information on the near-side lunar gravitational field. The primary emphasis is on the low-altitude (20 km) CSM data. The LM data cover a very short time span and are somewhat redundant with the CSM data. The resolution of the high-altitude (100 km) CSM data is not as great as that of the low altitude data. The low-altitude CSM and LM data coverage and the complementary coverage obtained during the Apollo 14 mission are presented. The experiment uses the same technique of gravity determination employed on the Lunar Orbiter, in the data of which the large anomalies called mascons were first observed. The data consist of variations in the spacecraft speed as measured by the Earth-based radio tracking system.

Sjogren, W. L.↗

NASA NTRS2020

Development of a Display Tool to Quality Control Weather Balloon Data for Space Launch Vehicles Using Python

Continuous atmospheric data analysis is an important factor for space launch vehicle design and operations. The balloon quality control tool was developed by NASA’s Marshall Space Flight Center (MSFC) Natural Environments Branch (NEB) for monitoring quality control processes and verifying the automated flags created on the balloon data sets analyzed. The data sets currently analyzed are comprised of high-resolution and low-resolution balloon data from NASA Kennedy Space Center (KSC), co-located on the United States Air Force’s Eastern range (ER) at the Cape Canaveral Air Force Station. The NEB was tasked to perform a quality assessment of these data sets and needed a tool to confirm the quality control (QC) flags produced from an automated process and add additional QC flags if necessary. This Graphical User Interface (GUI) was developed to visualize all of the data from these balloon sets, display any flags from the automated QC process, and add additional flags to variables if necessary. The GUI was developed in Python 3.6 utilizing different packages available such as pandas for data analysis and manipulation, NumPy for high-performance multidimensional array and tools to compute with and manipulate arrays, Matplotlib for plotting data and Tkinter to build the GUI.

Jessica K Headley↗

NASA NTRS2020

Development of a Display Tool to Quality Control Weather Balloon Data for Space Launch Vehicles

Jessica K Headley↗

DOE OSTI2026

TSDC: Transportation Secure Data Center: Real-World Data for Planning, Modeling, and Analysis

The Transportation Secure Data Center is a centralized repository for high-resolution transportation data from hundreds of travel and transit surveys and studies. It makes vital transportation data broadly available to users while preserving the privacy of survey participants. It houses surveys and studies conducted by state departments of transportation, metropolitan planning organizations, transit agencies, cities, and other public agencies. Meanwhile, the Livewire Data Platform empowers research, industry, and academic partners to easily and securely preserve, maintain, share, discover, and gain access to transportation and mobility data. Livewire accommodates a range of datasets, including behavioral, experimental, model, analytical, and raw data at the vehicle, traveler, and system levels. Datasets support mobility research and planning spanning urban science, connected and automated vehicles, fueling and charging infrastructure, mobility decision science, multimodal transportation, vehicle efficiency, and more.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2024

SPRUCE: Carbon Dioxide and Methane Soil Flux Measurements at High Temporal Resolution, Beginning in 2022

This data set contains high temporal resolution measurements of greenhouse gas flux (CO2 and CH4) from the SPRUCE (Spruce and Peatland Responses Under Changing Environments) experiment (Hanson et al. 2017) over the growing seasons in 2022 (30-minute resolution) and 2023 (15-minute resolution). Additional data will be appended to this dataset periodically until the close out of the SPRUCE experiment in 2025. This dataset contains two data files in comma-separate (*.csv) format. ABB GLA131-GGA CO2/CH4 gas analyzers, each paired with an Eosense eosMX multiplexer and 2 eosAC-LT automated flux chambers, were deployed from during the 2022 and 2023 growing seasons (2022-06-06 – 2023-10-26). Each SPRUCE experimental enclosure included two Eosense 50 cm diameter flux chambers with 40 cm tall stainless steel collars embedded approximately 15 cm into the peat soil, to measure soil gas flux of peatland ecosystem moss-shrub communities. . Measurements were taken for three minutes, alternating between the flux chambers, with each Eosense flux chamber sampling gas fluxes four times per hour in 2023 and twice per hour for 2022. In addition, time-series environmental data measured at the flux chamber are included: Photosynthetically active radiation (PAR), soil temperature, soil volumetric water content (at 10 cm depth), air temperature, soil temperature (0-200 cm depth), and volumetric water at 20 cm depth.

Spruce and Peatland Responses Under Changing Envir↗

NASA NTRS1989

Laser holographic interferometric measurements of the flow in a scramjet inlet at Mach 4

The need for quantitative data is addressed by laser holographic interferometry (LHI) by efficiently recording and reducing high resolution density data. This paper investigates the potential to get quantitative data from an interferogram created from two separate holographic plates. THe LHI measurements were made on a scramjet inlet at Mach 4. LHI successfully generated results for both internal and external flows, and demonstrated its ability to map entire flow fields. Of the three data reduction techniques used, the four-bucket method gave better results than the three-bucket or three-by-three methods. This technique requires high quality holograms as well as a good resolution in the digital images to produce good data.

Mcarthur, J. Craig↗

NASA NTRS1988

Spectral feature design in high dimensional multispectral data

The High resolution Imaging Spectrometer (HIRIS) is designed to acquire images simultaneously in 192 spectral bands in the 0.4 to 2.5 micrometers wavelength region. It will make possible the collection of essentially continuous reflectance spectra at a spectral resolution sufficient to extract significantly enhanced amounts of information from return signals as compared to existing systems. The advantages of such high dimensional data come at a cost of increased system and data complexity. For example, since the finer the spectral resolution, the higher the data rate, it becomes impractical to design the sensor to be operated continuously. It is essential to find new ways to preprocess the data which reduce the data rate while at the same time maintaining the information content of the high dimensional signal produced. Four spectral feature design techniques are developed from the Weighted Karhunen-Loeve Transforms: (1) non-overlapping band feature selection algorithm; (2) overlapping band feature selection algorithm; (3) Walsh function approach; and (4) infinite clipped optimal function approach. The infinite clipped optimal function approach is chosen since the features are easiest to find and their classification performance is the best. After the preprocessed data has been received at the ground station, canonical analysis is further used to find the best set of features under the criterion that maximal class separability is achieved. Both 100 dimensional vegetation data and 200 dimensional soil data were used to test the spectral feature design system. It was shown that the infinite clipped versions of the first 16 optimal features had excellent classification performance. The overall probability of correct classification is over 90 percent while providing for a reduced downlink data rate by a factor of 10.

Chen, Chih-Chien Thomas↗

NASA NTRS1993

Thermally distinct ejecta blankets from Martian craters

A study of Martian ejecta blankets is carried out using the high-resolution thermal IR/visible data from the Termoskan instrument aboard Phobos '88 mission. It is found that approximately 100 craters within the Termoskan data have an ejecta blanket distinct in the thermal infrared (EDITH). These features are examined by (1) a systematic examination of all Termoskan data using high-resolution image processing; (2) a study of the systematics of the data by compiling and analyzing a data base consisting of geographic, geologic, and mormphologic parameters for a significant fraction of the EDITH and nearby non-EDITH; and (3) qualitative and quantitative analyses of localized regions of interest. It is noted that thermally distinct ejecta blankets are excellent locations for future landers and remote sensing because of relatively dust-free surface exposures of material excavated from depth.

Betts, Bruce H.↗

DOE OSTI2023

Spatiotemporal Super-Resolution with Generative Machine Learning for Creating Renewable Energy Resource Data Under Climate Change Scenarios

As we plan for a future with higher penetrations of renewables and increasing electrification, it becomes more important to understand how the electricity grid will operate under a variety of weather events. We must also consider that the weather our future grid will experience will be different and possibly more extreme than the historical weather that we have extensive data for. We can use data from global climate models (GCMs) to help understand how our climate may change over the next several decades, but there is often a significant gap between the low-resolution GCM data and the high-resolution weather data required to study power systems under specific weather events. Therefore, our objective in this work is to develop tools that can bridge this gap by using low-resolution GCM data to create realistic high-resolution weather datasets that can be used to study renewable energy generation and electricity demand. To accomplish this objective, we have developed a set of generative machine learning models that can rapidly downscale GCM daily average output data at an approximate grid resolution of 100km to hourly data at an approximate 4 km grid resolution. The models can be used to create high resolution data from nearly any GCM included in the Coupled Model Intercomparison Project (CMIP) Phase 5 or 6. Our methods include all datasets regularly used to study the integration of wind and solar power plants as well as changes in electricity demand due to heating and cooling loads. These models and datasets enable power systems modelers to study climate change-influenced weather events and their impact on the grid. We have downscaled and validated wind, solar, temperature, and humidity data with very promising results. The generative machine learning methods are computationally efficient and produce data that has similar statistical characteristics to current state-of-the-art historical datasets. We have trained initial generative models and produced an initial dataset collectively referred to as Sup3rCC: Super-Resolved Renewable Energy Resource Data with Climate Change Impacts. The data covers a (mostly) historical period from 2015-2025 and a future period from 2050-2059. We have also taken hypothetical high-electrification load data and scaled the heating and cooling loads with respect to the 2050-2059 high-resolution Sup3rCC meteorology. The results show how future levels of renewable energy generation and electrified load may be impacted by climate change, setting the stage for capacity expansion models to consider a dynamic climate through model years.

climate change↗

DOE OSTI2020

Radar Super Resolution using a Deep Convolutional Neural Network

Super-resolution involves synthetically increasing the resolution of gridded data beyond its native resolution. Typically, this is done using interpolation schemes, which estimate sub-grid scale values from neighboring data, and perform the same operation everywhere regardless of the large-scale context, or by requiring a network of radars with overlapping fields of view. Recently, significant progress has been made in single image super resolution using convolutional neural networks. Conceptually, a neural network may be able to learn relations between large scale precipitation features and the associated sub-pixel scale variability and outperform interpolation schemes. Here, we use a deep convolutional neural network to artificially enhance the resolution of NEXRAD PPI scans. The model is trained on 6-months of reflectivity observations from the Langley Hill WA (KLGX) radar, and we find that it substantially outperforms common interpolation schemes for x4 and x8 resolution increases based on several objective error and perceptual quality metrics.

radar, machine learning, super resolution, Remote ↗

NASA NTRS1980

A solar activity monitoring platform for SCADM

The adaptation of proven space probe technology is proposed as a means of providing a solar activity monitoring platform which could be injected behind the Earth's orbital position to give 3 to 6 days advanced coverage of the solar phenomenon on the backside hemisphere before it rotates into view and affects terrestrial activities. The probe would provide some three dimensional discrimination within the ecliptic latitude. This relatively simple off-Earth probe could provide very high quality data to support the SCADM program, by transmitting both high resolution video data of the solar surface and such measurements of solar activity as particle, X-ray, ultraviolet, and radio emission fluxes. Topics covered include the orbit; constraints on the spacecraft; subsystems and their embodiments; optical imaging sensors and their operation; and the radiation-pressure attitude control system are described. The platform would be capable of mapping active regions on an hourly basis with one arc-second resolution.

Kissell, K. E.↗

NASA NTRSDate not supplied

Topographic Quintet: Comparing Five Methods for Measuring Ultra-High Resolution Topography

We compare different methods for collecting ultra-high resolution topography data within an analog planetary, human landing site scale area. Our aim is to investigate the cost and benefits of different 3D terrain mapping techniques, their associated data collection methods, and how their different specifications (e.g., range, spatial resolution, scanning-time, mobility, operating constraints, GPS-Denied operation, etc.) might be applied to landing-site characterization and mission operations. We compare 3D terrain data collected during a field campaign in November 2021 from an outcrop at Kilbourne Hole in southern New Mexico using different Light Detection and Ranging (LiDAR) sensors on the ground and stereo-derived 3D data from framing cameras mounted on small uncrewed aerial systems (sUAS).Our foci for this experiment are ground-based, surveying, and autonomous vehicle-type 3D scanning sensors that might be used for planetary surface exploration from landed assets (e.g., lander, rover, astronaut-mounted sensors, decent imaging, hoppers, or drones).[e.g. 1]This test is not meant to benchmark these scanners against one another, nor provide a recommendation for a specific make or model. Rather, our goal is to quantify time, effort, resolution, and operational trade-offs that are important for selecting a topographic instrument/methodology for a given scope of terrain characterization. Our results indicate that each technique is capable of exceptional quality terrain characterization for planetary exploration and scientific inquiry, but we hypothesize the appropriate technique is highly dependent on the scope of operational specifications and science requirements.

P Whelley↗