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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

Science opportunity analyzer - a multi-mission tool for planning

For many years the diverse scientific community that supports JPL's wide variety ofinterplanetary space missions has needed a tool in order to plan and develop their experiments. The tool needs to be easily adapted to various mission types and portable to the user community. The Science Opportunity Analyzer, SOA, now in its third year of development, is intended to meet this need. SOA is a java-based application that is designed to enable scientists to identify and analyze opportunities for science observations from spacecraft. It differs from other planning tools in that it does not require an in-depth knowledge of the spacecraft command system or operation modes to begin high level planning. Users can, however, develop increasingly detailed levels of design. SOA consists of six major functions: Opportunity Search, Visualization, Observation Design, Constraint Checking, Data Output and Communications. Opportunity Search is a GUI driven interface to existing search engines that can be used to identify times when a spacecraft is in a specific geometrical relationship with other bodies in the solar system. This function can be used for advanced mission planning as well as for making last minute adjustments to mission sequences in response to trajectory modifications. Visualization is a key aspect of SOA. The user can view observation opportunities in either a 3D representation or as a 2D map projection. The user is given extensive flexibility to customize what is displayed in the view. Observation Design allows the user to orient the spacecraft and visualize the projection of the instrument field of view for that orientation using the same views as Opportunity Search. Constraint Checking is provided to validate various geometrical and physical aspects of an observation design. The user has the ability to easily create custom rules or to use official project-generated flight rules. This capability may also allow scientists to easily impact the cost to science if flight rule changes occur. Data Output generates information based on the spacecraft's trajectory, opportunity search results or based on a created observation. The data can be viewed either in tabular format or as a graph. Finally, SOA is unique in that it is designed to be able to communicate with a variety of existing planning and sequencing tools. From the very beginning SOA was designed with the user in mind. Extensive surveys of the potential user community were conducted in order to develop the software requirements. Throughout the development period, close ties have been maintained with the science community to insure that the tool maintains its user focus. Although development is still in its early stages, SOA is already developing a user community on the Cassini project, which is depending on this tool for their science planning. There are other tools at JPL that do various pieces of what SOA can do; however, there is no other tool which combines all these functions and presents them to the user in such a convenient, cohesive, and easy to use fashion.

SOA science planning mission operations sequence s↗
NASA NTRS1984

User's guide for SBUV/TOMS ozone derivative products

A series of products are available derived from the total-ozone and ozone vertical profile results for the Solar Backscattered Ultraviolet/Total-Ozone Mapping Spectrometer (SBUV/TOMS) Nimbus-7 operation. Products available are (1) orbital height-latitude cross sections of the SBUV profile data, (2) daily global total ozone contours in polar coordinates, (3) daily averages of total ozone in global 5x5 degree latitude-longitude grid, (4) daily, monthly and quarterly averages of total ozone and profile data in 10 degree latitude zones, (5) tabular presentation of zonal means, (6) daily global total ozone and profile contours in polar coordinates. The ""Derivative Products User's Guide'' describes each of these products in detail, including their derivation and presentation format. Information is provided on how to order the tapes and microfilm from the National Space Science Data Center.

Fleig, A. J.↗
DOE OSTI2024

Data associated with the manuscript “Radiative impact of record-breaking wildfires from integrated ground-based data” collected in Richland, Washington in September 2020

This data package is associated with the publication “Radiative impact of record-breaking wildfires from integrated ground-based data” submitted to Nature Scientific Reports (Kassianov et al., 2024). Data from ground-based measurements of shortwave and spectrally resolved irradiance and aerosol optical depth (AOD) in the visible and near-infrared spectral ranges were assessed to quantify the radiative impact of the September 2020 wildfires that occurred in the Western United States. Data were collected in September 2020 by several ground-based instruments at the Atmospheric Measurements Laboratory (AML) located in Richland, Washington (46.3451, -119.2792). These data include (1) Aerosol Optical Depth (AOD); (2) spectrally resolved and shortwave (SW) irradiances; (3) backscatter profiles; (4) total sky images; and (5) near-surface ambient air temperatures.The data package consists of five sub-directories: (1) “AML_Ceilometer_”; (2)” AML_CSPHOT_”; (3) “AML_MFRSR_irradiances_”; (4) “AML_SW_irradiances_and_Temp_”; (5) “AML_TSI_images_”; and 6 files stored at the directory level, including the readme, file-level metadata file, and data dictionary. The file-level metadata file (the file ending in “_flmd.csv”) lists all files contained in this data package and descriptions for each. The data dictionary (the file ending in “_dd.csv”) describes each tabular column header’s unit, definition, and structure. Below are descriptions of each sub-directory:“AML_Ceilometer_” includes ceilometer data collected at the AML. These files contain the corresponding narratives of data. Details related to the ceilometer data can be found in Morris (2016). “AML_CSPHOT_” includes ascii files with high-temporal resolution (about 10-15 min) AML CSPHOT data and their daily-averaged counterparts. These two files contain the corresponding narratives of data. Details related to the CSPHOT data can be found in Gregory (2011). “AML_MFRSR_irradiances_” includes ascii files with the AML MFRSR-measured diffuse, normal, and total spectrally resolved irradiance. Details related to the MFRSR data can be found in Hodges and Michalsky (2016) and Koontz et al. (2013). “AML_SW_irradiances_+_Temp_” includes near-surface ambient air temperature and SW irradiances, namely direct normal, diffuse hemispherical, and total hemispheric (global), measured at the AML. These files also incorporate the corresponding narratives of data. Details related to the SW irradiances can be found in Andreas et al. (2018). “AML_TSI_images_” includes Total Sky Images (TSIs) collected at the AML. Details related to the TSI data can be found in Morris (2005).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1945

Net Heat of Combustion of AN-F-28 Aviation Gasolines

Experimental data on the heats of combustion and hydrogen contents of a number of aviation gasolines have been used in deriving a formula for computing net heat of combustion from (measured) gross heat of combustion. This formula appears to be sufficiently reliable for the purpose and has the advantage of making hydrogen determinations unnecessary. The data on heats of combustion are presented in tabular form, and in graphs showing the relation between net heat of combustion and (1) hydrogen content, (2) aniline point, (3) APO gravity, and (4) the product of aniline point and APO gravity. Data are given on the change in aniline point with time, and also the change resulting from the addition of xylidine.

FUELS - COMBUSTION TEMPERATURES↗
NASA NTRS1979

Flight design system level C requirements. Solid rocket booster and external tank impact prediction processors

The prediction of the SRB and ET impact areas requires six separate processors. The SRB impact prediction processor computes the impact areas and related trajectory data for each SRB element. Output from this processor is stored on a secure file accessible by the SRB impact plot processor which generates the required plots. Similarly the ET RTLS impact prediction processor and the ET RTLS impact plot processor generates the ET impact footprints for return-to-launch-site (RTLS) profiles. The ET nominal/AOA/ATO impact prediction processor and the ET nominal/AOA/ATO impact plot processor generate the ET impact footprints for non-RTLS profiles. The SRB and ET impact processors compute the size and shape of the impact footprints by tabular lookup in a stored footprint dispersion data base. The location of each footprint is determined by simulating a reference trajectory and computing the reference impact point location. To insure consistency among all flight design system (FDS) users, much input required by these processors will be obtained from the FDS master data base.

Seale, R. H.↗
NASA NTRS1989

Materials properties numerical database system established and operational at CINDAS/Purdue University

A computerized comprehensive numerical database system on the mechanical, thermophysical, electronic, electrical, magnetic, optical, and other properties of various types of technologically important materials such as metals, alloys, composites, dielectrics, polymers, and ceramics has been established and operational at the Center for Information and Numerical Data Analysis and Synthesis (CINDAS) of Purdue University. This is an on-line, interactive, menu-driven, user-friendly database system. Users can easily search, retrieve, and manipulate the data from the database system without learning special query language, special commands, standardized names of materials, properties, variables, etc. It enables both the direct mode of search/retrieval of data for specified materials, properties, independent variables, etc., and the inverted mode of search/retrieval of candidate materials that meet a set of specified requirements (which is the computer-aided materials selection). It enables also tabular and graphical displays and on-line data manipulations such as units conversion, variables transformation, statistical analysis, etc., of the retrieved data. The development, content, accessibility, etc., of the database system are presented and discussed.

Ho, C. Y.↗
DOE OSTI2024

UAS remote sensing (Osprey platform): Red-green-blue (RGB) imagery, thermal infrared (TIR) imagery, and canopy reflectance, Seward Peninsula, Alaska, 2018

Airborne remote sensing data collected using the Brookhaven National Laboratory's (BNL) heavy-lift unoccupied aerial system (UAS) octocopter platform - the Osprey - operated by the Terrestrial Ecosystem Science and Technology (TEST) group. This package includes data from 34 flights flown over the NGEE-Arctic Council Mile Maker 72 (MM72), Kougarok MM64, Kougarok MM80, and Teller MM27 sites in July, 2018. The Osprey is a multi-sensor UAS platform that simultaneously measures very high spatial resolution optical red/green/blue (RGB) and thermal infrared (TIR) surface "skin" temperature imagery, as well as surface reflectance at 1 nm intervals in the visible to near-infrared spectral range from ~350-1000 nm measured at regular intervals along each flight path. This package provide the Level 0 (raw, unprocessed) data collected by the Osprey platform. Ancillary aircraft data, flight mission parameters, and general flight conditions provided by the onboard flight and data collection computers are also included. Data and metadata are provided as text (*.txt, *.json), tabular (*.dat, *.csv, *.waypoint), and image (*.jpg) formats. This metadata document contains flight campaign, instrument and file metadata, along with a description of the L0 data, and file naming scheme. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

UAS remote sensing (Osprey platform): Red-green-blue (RGB) imagery, thermal infrared (TIR) imagery, and canopy reflectance, Seward Peninsula, Alaska, 2019

Airborne remote sensing data collected using the Brookhaven National Laboratory's (BNL) heavy-lift unoccupied aerial system (UAS) octocopter platform - the Osprey - operated by the Terrestrial Ecosystem Science and Technology (TEST) group (https://www.bnl.gov/testgroup). This package includes data from 17 flights flown over the NGEE-Arctic Council Mile Maker 64 (MM64) and Teller MM27 sites in July, 2019. The Osprey is a multi-sensor UAS platform that simultaneously measures very high spatial resolution optical red/green/blue (RGB) and thermal infrared (TIR) surface "skin" temperature imagery, as well as surface reflectance at 1 nm intervals in the visible to near-infrared spectral range from ~350-1000 nm measured at regular intervals along each flight path. This package provide the Level 0 (raw, unprocessed) data collected by the Osprey platform. Ancillary aircraft data, flight mission parameters, and general flight conditions provided by the onboard flight and data collection computers are also included. Data and metadata are provided as text (*.txt, *.json), tabular (*.dat, *.csv, *.waypoint), and image (*.jpg) formats. This metadata document contains flight campaign, instrument and file metadata, along with a description of the L0 data, and file naming scheme. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2012

Linking NASA Environmental Data with a National Public Health Cohort Study and a CDC On-Line System to Enhance Public Health Decision Making

The overall goal of this study is to address issues of environmental health and enhance public health decision making by utilizing NASA remotely-sensed data and products. This study is a collaboration between NASA Marshall Space Flight Center, Universities Space Research Association (USRA), the University of Alabama at Birmingham (UAB) School of Public Health and the Centers for Disease Control and Prevention (CDC) National Center for Public Health Informatics. The objectives of this study are to develop high-quality spatial data sets of environmental variables, link these with public health data from a national cohort study, and deliver the linked data sets and associated analyses to local, state and federal end-user groups. Three daily environmental data sets were developed for the conterminous U.S. on different spatial resolutions for the period 2003-2008: (1) spatial surfaces of estimated fine particulate matter (PM2.5) exposures on a 10-km grid utilizing the US Environmental Protection Agency (EPA) ground observations and NASA s MODerate-resolution Imaging Spectroradiometer (MODIS) data; (2) a 1-km grid of Land Surface Temperature (LST) using MODIS data; and (3) a 12-km grid of daily Solar Insolation (SI) and maximum and minimum air temperature using the North American Land Data Assimilation System (NLDAS) forcing data. These environmental datasets were linked with public health data from the UAB REasons for Geographic and Racial Differences in Stroke (REGARDS) national cohort study to determine whether exposures to these environmental risk factors are related to cognitive decline and other health outcomes. These environmental national datasets will also be made available to public health professionals, researchers and the general public via the CDC Wide-ranging Online Data for Epidemiologic Research (WONDER) system, where they can be aggregated to the county, state or regional level as per users need and downloaded in tabular, graphical, and map formats. The linkage of these data provides a useful addition to CDC WONDER, allowing public health researchers and policy makers to better include environmental exposure data in the context of other health data available in this online system. It also substantially expands public access to NASA data, making their use by a wide range of decision makers feasible.

Al-Hamdan, Mohammad↗
NASA NTRS1990

Primary reference cell calibrations at SERI - History and methods

The tabular calibration method used at the Solar Energy Research Institute (SERI) for primary reference cells is derived and described in detail. An uncertainty analysis shows that the tabular method should have a total uncertainty of + or - 1.0 percent; data from five years of calibrations are then shown to support this analysis. Results from SERI's tabular method are compared with terrestrial calibrations performed by the NASA Lewis Research Center in the late 1970s.

Osterwald, C. R.↗
NASA NTRS1973

Application of a hybrid computer to sweep frequency data processing

A hybrid computer program is presented which can process as many as 10 channels of sweep frequency data simultaneously. The program needs only the sine sweep signal used to drive the system, and its correponding quadrature component, to process the data. It can handle a maximum frequency range of 0.5 to 500 hertz. Magnitude and phase are calculated at logarithmically spaced points covering the frequency range of interest. When the sweep is completed, these results are stored in digital form. Thus, a tabular listing and/or a plot of any processed data channel or the transfer function relating any two of them is immediately available.

Milner, E. J.↗
DOE OSTI2024

UAS remote sensing (Osprey platform): Red-green-blue (RGB) imagery, thermal infrared (TIR) imagery, and canopy reflectance, Seward Peninsula, Alaska, 2017

Airborne remote sensing data collected using the Brookhaven National Laboratory's (BNL) heavy-lift unoccupied aerial system (UAS) octocopter platform - the Osprey - operated by the Terrestrial Ecosystem Science and Technology (TEST) group (https://www.bnl.gov/testgroup). This package includes raw (L0) data from 14 flights flown over the NGEE-Arctic Council Mile Marker 71 (MM71), Kougarok MM64, and Teller MM 27 sites in August, 2017. The Osprey is a multi-sensor UAS platform that simultaneously measures very high spatial resolution optical red/green/blue (RGB) and thermal infrared (TIR) surface "skin" temperature imagery, as well as near-surface surface reflectance at 1 nm intervals in the visible to near-infrared spectral range from ~350-1000 nm measured at regular intervals along each flight path. This package provides the Level 0 (raw, unprocessed) data collected by the Osprey platform. Ancillary aircraft data, flight mission parameters, and general flight conditions provided by the onboard flight and data collection computers are also included. Data and metadata are provided as text (*.txt, *.json), tabular (*.dat, *.csv, *.waypoint), and image (*.jpg) formats. This metadata documents contain flight campaign, platform, sensor, flight and file metadata, along with a description of the L0 data and the file naming scheme. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 15-year research effort (2012-2027) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1994

Atlas of quasar energy distributions

We present an atlas of the spectral energy distributions (SEDs) of normal, nonblazar, quasars over the whole available range (radio to 10 keV X-rays) of the electromagnetic spectrum. The primary (UVSX) sample includes 47 quasars for which the spectral energy distributions include X-ray spectral indices and UV data. Of these, 29 are radio quiet, and 18 are radio loud. The SEDs are presented both in figures and in tabular form, with additional tabular material published on CD-ROM. Previously unpublished observational data for a second set of quasars excluded from the primary sample are also tabulated. The effects of host galaxy starlight contamination and foreground extinction on the UVSX sample are considered and the sample is used to investigate the range of SED properties. Of course, the properties we derive are influenced strongly by the selection effects induced by quasar discovery techniques. We derive the mean energy distribution (MED) for radio-loud and radio-quiet objects and present the bolometric corrections derived from it. We note, however, that the dispersion about this mean is large (approximately one decade for both the infrared and ultraviolet components when the MED is normalized at the near-infrared inflection). At least part of the dispersion in the ultraviolet may be due to time variability, but this is unlikely to be important in the infrared. The existence of such a large dispersion indicates that the MED reflects only some of the properties of quasars and so should be used only with caution.

Elvis, Martin↗
NASA NTRS1996

BIOME: A browser-aware search and order system

The Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC), which is associated with NASA's Earth Observing System Data and Information System (EOSDIS), provides access to a large number of tabular and imagery datasets used in ecological and environmental research. Because of its large and diverse data holdings, the challenge for the ORNL DAAC is to help users find data of interest from the hundreds of thousands of files available at the DAAC without overwhelming them. Therefore, the ORNL DAAC developed the Biogeochemical Information Ordering Management Environment (BIOME), a search and order system for the World Wide Web (WWW). The WWW provides a new vehicle that allows a wide range of users access to the data. This paper describes the specialized attributes incorporated into BIOME that allow researchers easy access to an otherwise bewildering array of data products.

Grubb, Jon W.↗
NASA NTRS1986

Photometry from Voyager 2 - Initial results from the Uranian atmosphere, satellites, and rings

The results of Voyager 2 photopolarimetry (PPS) surveys of Uranus, the ring system, occultation experiments and observations of the Uranian moons are reported. Dual-channel photometry and polarimetry data obtained of the atmosphere at various emission and phase angles are delineated and compared with characteristics of the Saturn and Jupiter atmospheres. The results of temperature, UV absorption and density profile calculations are also discussed. Extensive ring dimensional data, based on two occultation experiments, are provided in tabular form noting that the rings contain no dust. Finally, the geometric albedos of the five major moons and the phase curve of the moon Titania are presented. The latter data indicate that Titanian surface features are not the result of recent events such as volcanism or ice slurry outflows.

Lane, A. L.↗
NASA NTRS1994

CTAS data analysis program

The analysis program (AN) is specifically designed to produce graphic and tabular information to aid in the design and checkout of the Center TRACON Automation System (CTAS). To best reveal CTAS operation and possible problems, data are plotted in many different ways both in detail and summary form. AN has been designed to analyze both radar surveillance data and output data from CTAS. AN has been extensively used to debug and refine CTAS. It is also being used in the field to monitor and assess CTAS performance. AN is continuously refined to keep up with changing needs. The present version of AN grew out of analysis of Denver Center data. However, the AN software has been written to be adaptable to any other facility Center or TRACON. Presently, one can select Denver Stapleton, Denver International, Dallas/Fort Worth International Airport, and Dallas Love Field.

Neuman, Frank↗
DOE OSTI2020

turbine-models

The (wind) turbine-models GitHub repo hosts an archive/database of turbine models already in the public domain. This includes mainly tabular power and thrust (when available) curve data in .csv files, other technical data, as well as documentation and references built with Sphinx/GitHub Pages. There is a script called "curve_parser.py" to assist with the parsing of power and thrust curves, but this repo is mostly a central location for turbine model data.

Duffy, Patrick↗