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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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This work was focused on developing novel methods to facilitate rapid data to knowledge transformation for subsurface applications, particularly those related to unconventional oil and gas.
Raw data for all figures and panels in the paper. Data is contained in Igor files. Trial version of Igor can be obtained free for 30 days from https://www.wavemetrics.com/order/order_igordownloads.htm
Two years of SBUV/TOMS (Solar Backscattered Ultraviolet/Total Ozone Mapping Spectrometer) data spanning the period November 1978 to October 1980 have been processed and compared with ground-based ozone measurements made at 62 Dobson spectrophotometer and 18 M83 filter photometer ozone stations. Results show that the satellite ozone values are consistently smaller than those measured by the stations; most of this difference is probably due to an error in the currently accepted ozone absorption cross sections at ultraviolet wavelengths. Dobson-derived ozone amounts agree extremely well with those derived from each of the satellite instruments. Long-term stability of the ozone derived by the two instruments is expected to be better than 0.5 percent per year.
Within 12 months a 5-year space-based research investigation with an estimated daily data volume of 10 to 15 gigabytes will be launched. Our instrument/analysis team will analyze 2 to 8 gigabytes per day from this mission. Most of these data will be spatial and multispectral collected from nine sensors covering the UV/Visible/NlR spectrum. The volume and diversity of these data and the nature of its analysis require a very robust reduction and management system. This paper is a summary of the systems requirements and a high-level description of a solution. The paper is intended as a case study of the problems and potential solutions faced by the new generation of Earth observation data support systems.
An analysis of a case study of the favorable impact of satellite data assimilation on model cyclone prediction is discussed. Also discussed is the isolation of systematic biases in the vertical structure of satellite derived temperatures which in all probability negatively impact the prediction of ocean cyclones during periods of rapid baroclinic amplification. Access to CYBER 205 and transfer of software for Eulerian and quasi-Lagrangian diagnostic studies of atmospheric circulation are discussed.
The algorithm-development activities at USF during the second half of 1997 have concentrated on data collection and theoretical modeling. Six abstracts were submitted for presentation at the AGU conference in San Diego, California during February 9-13, 1998. Four papers were submitted to JGR and Applied Optics for publication.
Objectives Review and inform on tactics to analyze & communicate data from animal research (e.g., rodents, mini-pigs, NHPs, et al) exposed to single and combinations of spaceflight hazards, using NASA’s Human System Risk Board (HSRB) process for the Behavioral Medicine Risk - To quantitatively inform Behavioral Medicine Risk posture - i.e., likelihood (L) and consequence (C) - To help inform estimation of crew health standards for operational task performance (i.e., Fitness For Duty, Space Permissible Exposure Levels, Permissible Operational Limits).
Combining different observational probes, such as galaxy clustering and weak lensing, is a promising technique for unveiling the physics of the Universe with upcoming dark energy experiments. The galaxy redshift sample from the Dark Energy Spectroscopic Instrument (DESI) will have a significant overlap with major ongoing imaging surveys specifically designed for weak lensing measurements: the Kilo-Degree Survey (KiDS), the Dark Energy Survey (DES), and the Hyper Suprime-Cam (HSC) survey. In this work, we analyse simulated redshift and lensing catalogues to establish a new strategy for combining high-quality cosmological imaging and spectroscopic data, in view of the first-year data assembly analysis of DESI. In a test case fitting for a reduced parameter set, we employ an optimal data compression scheme able to identify those aspects of the data that are most sensitive to cosmological information and amplify them with respect to other aspects of the data. We find this optimal compression approach is able to preserve all the information related to the growth of structures.
Three geological models in Petrel (Mark of Schlumberger) and data output from shallow groundwater modeling using TOUGH Codes from Lawrence Berkeley National Laboratory, included under folders: Static_Geologic_Model, Dynamic_Reservoir_Model, Geomechanical_Model, and Groundwater_Model.
Scale factors and assumptions which were applied in calculations of global radiation budget parameters based on ERB data are discussed. The study was performed to examine the relationship between the composite global ERB map that can be generated every six days using all available data and the actual average global ERB. The wide field of view ERB instrument functioned for the first 19 months of the Nimbus-7 life, and furnished sufficient data for calculating actual ERB averages. The composite was most accurate in regions with the least variation in radiation budget.
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A description of AOIPS/2, an interactive hardware and software system to process, integrate, and display meteorological data is presented. The AOIPS/2 objectives and functional specifications are given. The hardware system architecture and work stations and the software architecture and special features are described. A summary is given of the software system and its main menu.
The raw data for all figures including panel figures and layout formatting in Igor format. trial version of Igor can be obtained to access the data at https://www.wavemetrics.com/order/order_igordownloads.htm
The use of collaborative scientific visualization systems for the analysis, visualization, and sharing of "big data" available from new high resolution remote sensing satellite sensors or four‐dimensional numerical model simulations is propelling the wider adoption of ultra‐resolution tiled display walls interconnected by high speed networks. These systems require a globally connected and well‐integrated operating environment that provides persistent visualization and collaboration services. This abstract and subsequent presentation describes a new collaborative visualization system installed for NASA's Shortterm Prediction Research and Transition (SPoRT) program at Marshall Space Flight Center and its use for Earth science applications. The system consists of a 3 x 4 array of 1920 x 1080 pixel thin bezel video monitors mounted on a wall in a scientific collaboration lab. The monitors are physically and virtually integrated into a 14' x 7' for video display. The display of scientific data on the video wall is controlled by a single Alienware Aurora PC with a 2nd Generation Intel Core 4.1 GHz processor, 32 GB memory, and an AMD Fire Pro W600 video card with 6 mini display port connections. Six mini display‐to‐dual DVI cables are used to connect the 12 individual video monitors. The open source Scalable Adaptive Graphics Environment (SAGE) windowing and media control framework, running on top of the Ubuntu 12 Linux operating system, allows several users to simultaneously control the display and storage of high resolution still and moving graphics in a variety of formats, on tiled display walls of any size. The Ubuntu operating system supports the open source Scalable Adaptive Graphics Environment (SAGE) software which provides a common environment, or framework, enabling its users to access, display and share a variety of data‐intensive information. This information can be digital‐cinema animations, high‐resolution images, high‐definition video‐teleconferences, presentation slides, documents, spreadsheets or laptop screens. SAGE is cross‐platform, community‐driven, open‐source visualization and collaboration middleware that utilizes shared national and international cyberinfrastructure for the advancement of scientific research and education.
This public dataset contains openly-documented, machine readable digital research data corresponding to figures published in J.D. Weberski et al., “Taylor Limit Studies for Local Helicity Injection Plasma Startup,” Physics of Plasmas 32 , 062510 (2025).
Several datasets regarding the ocean in the Southern Hemisphere are combined into a coregistered format to analyze the use of the data in multidisciplinary research. The datasets are described detailing bathymetric climatological data on surface pigment concentration, eddy-kinetic-energy measurements, surface wind-stress magnitudes, sea-surface temperatures, surface densities, and nitrate concentrations. The data are combined in a common projection which facilitates the comparison of the fields, and the combined data yield insights regarding such phenomena as bottom topography, surface heat and moisture fluxes, and divergences in flow. The number of available datasets is shown to be good, and the data can be used to develop working hypotheses on the relationships between physical and biogeochemical processes.
In this paper a framework is presented for extracting information content from modern sky surveys, which have archived multiple terabytes of data in various wavelengths and at various resolutions.
Key elements of a traditional regression model term selection process for the analysis of wind tunnel strain-gage balance calibration data are discussed. The traditional process is sometimes applied when regression models of the gage outputs are needed and an analyst does not have access to a term selection algorithm. In principle, the traditional process identifies supported regression model terms of a gage output by combining an analyst's subject- matter knowledge with a visual examination of selected plots of the calibration loads. Twelve empirical rules are listed that may be used to select regression model terms. Data from the manual calibration of a force balance is used to illustrate the application of the traditional term selection process. The data example shows that the traditional process can become very complex. Its successful application highly depends on an analyst's experience and skills. Therefore, it is suggested to replace the traditional term selection process with an automated term selection algorithm. Then, objective metrics are systematically applied during the term selection that make the identification of the regression model more repeatable and less dependent on an analyst's personal skills.