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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 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
NASA NTRS1987

Reduction and scientific analysis of data from the charge-energy-mass (CHEM) spectrometer on the AMPTE/CCE spacecraft

The Charge-Energy-Mass (CHEM) spectrometer instrument on the AMPTE/Charge Composition Explorer (CCE) spacecraft is designed to measure the mass and charge-state abundance of magnetospheric and magnetosheath ions between 0.3 and 315 keV/e, an energy range that includes the bulk of the ring current and the dynamically important portion of the plasma sheet population. Continuing research is being conducted using the AMPTE mission data set, and in particular, that of the CHEM spectrometer which has operated flawlessly since launch and still provides excellent quality data. The requirted routine data processing and reduction, and software develpment continues to be performed. Scientific analysis of composition data in a number of magnetospheric regions including the ring current region, near-earth plasma sheet and subsolar magnetosheath continues to be undertaken. Correlative studies using data from the sister instrument SULEICA, which determines the mass and charge states of ions in the energy range of approximately 10 to 250 keV/e on the IRM, as well as other data from the CCE and IRM spacecraft, particularly in the upstream region and plasma sheet have also been undertaken.

Gloeckler, G.↗
NASA NTRS2003

Lessons Learned From Developing A Streaming Data Framework for Scientific Analysis

We describe the development and usage of a streaming data analysis software framework. The framework is used for three different applications: Earth science hyper-spectral imaging analysis, Electromyograph pattern detection, and Electroencephalogram state determination. In each application the framework was used to answer a series of science questions which evolved with each subsequent answer. This evolution is summarized in the form of lessons learned.

Wheeler. Kevin R.↗
NASA NTRS1980

The payload connection - Approaches to onboard data processing for scientific systems on the Space Shuttle

The integration of payload instruments into the Command and Data Management Subsystem (CDMS) of the Space Shuttle Spacelab is discussed. Specific emphasis is on the distributed (self-contained processor) vs centralized (Spacelab Computer) approach to science payload utilization of these control and data handling capabilities. An overview of the Spacelab CDMS is first given. A synopsis of the integration process for Spacelab Missions 1, 2, and 3 is discussed. Three different hardware approaches to payload command and data handling are then categorized from which Spacelab implementations to date are derived. The different types of Spacelab Mission 3 payload CDMS hardware and software being used are discussed, including examples of microprocessors and data acquisition systems. Preliminary costs for Spacelab application software vs other flight software approaches are compared. A standard RAU interface that would permit a range of ECOS services to be provided, yet be implemented as a mass-produceable unit for incorporation into payloads, is proposed, in keeping with the trend toward simplifying the integration effort, standardizing CDMS interfaces, and ultimately lowering cost.

Konkel, C. R.↗
NASA NTRS1973

The data processor from the small scientific satellite

A reprogrammable data system aboard a small scientific satellite is described that samples and processes magnetospheric measurements for transmission to the ground. The lightweight configuration of the data system is made up of the program memory, data storage, input/output module, and a central processing unit. The system is designed for multiple missions.

Mccain, H. G.↗
NASA NTRS1991

High altitude aircraft direction using real-time scientific analysis of telemetered data

Microscale and some mesoscale scientific targets are often too small and fast moving in a dynamic atmosphere. In this environment the ER-2 may spend only a small time sampling the phenomena of interest. The ER-2 scientists currently rely on post-flight analysis to determine the success of the mission and to provide input for planning the next flight. Real time analysis, combined with realistic modeling, can provide important clues to significantly enhance the probability of success in the investigation of specific scientific targets.

Wegener, Steven↗
NASA NTRS1995

Data management and scientific integration within the Atmospheric Radiation Measurement Program

The Atmospheric Radiation Measurement (ARM) Program has been developed by the U.S. Department of Energy with the goal to improve the predictive capabilities of General Circulation Models (GCM's) in their treatment of clouds and radiative transfer effects. To achieve this goal, three experimental testbeds were designed for the deployment of instruments that will collect atmospheric data used to drive the GCM's. Each site, known as a Cloud and Radiation Testbed (CART), consists of a highly available, redundant data system for the collection of data from a variety of instrumentation. The first CART site was deployed in April 1992 in the Southern Great Plains (SGP), Lamont, Oklahoma, with the other two sites to follow in September 1995 in the Tropical Western Pacific and in 1997 on the North Slope of Alaska. Approximately 400 MB of data are transferred per day via the Internet from the SGP site to the ARM Experiment Center at Pacific Northwest Laboratory in Richland, Washington. The Experiment Center is central to the ARM data path and provides for the collection, processing, analysis, and delivery of ARM data. Data are received from the CART sites from a variety of instrumentation, observational systems, amd external data sources. The Experiment Center processes these data streams on a continuous basis to provide derived data products to the ARM Science Team in near real-time while providing a three-month running archive of data. A primary requirement of the ARM Program is to preserve and protect all data produced or acquired. This function is performed at Oak Ridge National Laboratory where leading edge technology is employed for the long-term storage of ARM data. The ARM Archive provides access to data for participation outside of the ARM Program. The ARM Program involves a collaborative effort by teams from various DOE National Laboratories, providing multi-disciplinary areas of expertise. This paper will discuss the collaborative methods in which the ARM teams translate the scientific goals of the Program into data products. By combining atmospheric scientists, systems engineers, and software engineers, the ARM Program has successfully designed and developed an environment where advances in understanding the parameterizations of GCM's can be made.

Gracio, Deborah K.↗
NASA NTRSDate not supplied

Enhancing NASA Earth Science Data Discovery from Scientific Publications

Earth observations from space borne instruments have evolved explosively in the past decades. Following closely are reanalysis systems assimilating model and observational data, yielding even longer records and larger number of variables. Thanks to advances in internet technology, it is now easier than ever to visualize and analyze these data using web interfaces. On the other hand, it also becomes an increasingly daunting task to build upon the existing knowledge published in various peer reviewed sources, and navigate toward the most relevant data, analysis, and visualization. We present an analysis of a subset of publications that utilized a popular visualization web interface at the NASA Goddard Earth Science Data and Information Services Center. Known as "Giovanni", it allows researchers from wide backgrounds to work with hundreds of variables from space observations and assimilation systems. Since coming online more than a decade ago, Giovanni has been credited in more than 100 papers per year, and the total count now is estimated to be nearly 1,500. Many of these papers contain valuable information about when, where and how Giovanni has been used, and hence forge an opportunity to learn and share the knowledge of which variables were used for what research projects. The purpose of our work is to retrieve the information from the papers and organize it as a knowledge repository which links together datasets, variables, places, dates and phenomena all of which reflect the essence of the published research. Since the publications are unstructured texts, we use natural language processing along with machine learning methods in the retrieval process. One of the challenges is deciphering the dataset names, because in many cases researchers refer to variables, rather than the datasets containing them. To constrain the number of terms, we deploy Earth Science ontologies as dictionaries for the term extraction. We demonstrate that storing these terms and underlying ontologies, along with datasets, variables and papers in the knowledge graph database, enables various linkages between all these entities facilitating the data discovery. Thus, we are setting a qualitatively new stage in improvements of web data interfaces, where machine learning techniques are used to establish and optimize usage-based discovery of data.

Irina V Gerasimov↗
NASA NTRS1987

Transportable educational programs for scientific and technical professionals: More effective utilization of automated scientific and technical data base systems

This grant final report executive summary documents a major, long-term program addressing innovative educational issues associated with the development, administration, evaluation, and widespread distribution of transportable educational programs for scientists and engineers to increase their knowledge of, and facilitate their utilization of automated scientific and technical information storage and retrieval systems. This educational program is of very broad scope, being targeted at Colleges of Engineering and Colleges of Physical sciences at a large number of colleges and universities throughout the United States. The educational program is designed to incorporate extensive hands-on, interactive usage of the NASA RECON system and is supported by a number of microcomputer-based software systems to facilitate the delivery and usage of the educational course materials developed as part of the program.

Dominick, Wayne D.↗
NASA NTRS1993

Cassini radio and plasma wave investigation - Data compression and scientific applications

The Radio and Plasma Wave Science (RPWS) experiment being built for the Cassini spacecraft will study a wide range of plasma and radio wave phenomena in the magnetosphere of Saturn and will also make valuable measurements during the cruise phase and at other encounters. A feature of data from wave receivers is the capability of producing vastly more data than the spacecraft telemetry link is capable of transmitting back to the Earth. Thus, techniques of on-board data compression and data reduction are important. The RPWS instrument has one processor dedicated to data compression tasks.

Woolliscroft, L. J. C.↗
NASA NTRS1993

Cassini radio and plasma wave investigation: Data compression and scientific applications

The Radio and Plasma Wave Science (RPWS) experiment being built for the Cassini spacecraft will study a wide range of plasma and radio wave phenomena in the magnetosphere of Saturn and will also make valuable measurements during the cruise phase and at other encounters. A feature of data from wave receivers is the capability of producing vastly more data than the spacecraft telemetry link is capable of transmitting back to the Earth. Thus, techniques of on-board data compression and data reduction are important. The RPWS instrument has one processor dedicated to data compression tasks.

Woolliscroft, L. J. C.↗
NASA NTRSDate not supplied

Biospecimen and Data Sharing: NASA Institutional Scientific Collection at Ames Research Center (ISC-ARC), and the Ames Life Sciences Data Archive (ALSDA)

For decades, NASA and international partners have conducted biological experiments in space to understand effects of spaceflight and address potential hazards. To enable spaceflight back to the Moon, and then to Mars and beyond, it is imperative to further understand basic science and health risks associated with spaceflight, along with developing countermeasures. The sending of experiments and organisms into space is a costly endeavor. To maximize scientific return, sharing with the scientific community both space-flown biospecimens and data from completed experiments is essential. New fundamental, applied, and bioinformatic science insights can be gained from specimen and data sharing efforts. Data reuse enables spaceflight health risk modeling, analyzing adverse outcomes across spaceflight hazards, and deep space autonomous support for the flight medical officer.

Data↗
NASA NTRS1990

Scientific study of data analysis

We present a comparison between two numerical methods for the extrapolation of nonlinear force-free magnetic fields, the Iterative Method (IM) and the Progressive Extension Method (PEM). The advantages and disadvantages of these two methods are summarized and the accuracy and numerical instability are discussed. On the basis of this investigation, we claim that the two methods do resemble each other qualitatively.

Wu, S. T.↗
NASA NTRS2000

BOREAS AES Campbell Scientific Surface Meteorological Data

Canadian AES personnel collected data related to surface and atmospheric meteorological conditions over the BOREAS region. This data set contains 15-minute meteorological data from 14 automated meteorology stations located across the BOREAS region. Included in this data are parameters of date, time, mean sea level pressure, station pressure, temperature, dew point, wind speed, resultant wind speed, resultant wind direction, peak wind, precipitation, maximum temperature in the last hour, minimum temperature in the last hour, pressure tendency, liquid precipitation in the last hour, relative humidity, precipitation from a weighing gauge, and snow depth. Temporally, the data cover the period of August 1993 to December 1996. The data are provided in tabular ASCII files, and are classified as AFM-Staff data.

Atkinson, G. Barrie↗
NASA NTRS2001

Scientific Analysis of Data for the ISTP/SOLARMAX Programs

This Grant supplemented our work on data analysis from the Wind spacecraft which was one of the ISTRIA fleet of spacecraft. It was targeted at observations related to the time of solar maximum in 2000. The work we proposed to do under this grant included comparison of solar wind parameters obtained from different spacecraft in order to establish correlation lengths appropriate to the solar wind and also to compare parameters to explore solar cycle effects.

Lazarus, Alan J.↗
NASA NTRS1991

Data evaluation, analysis, and scientific study

Extensive work was performed in data analysis and modeling of solar active phenomena. The work consisted in the study of UV data from the Ultraviolet Spectrometer and Polarimeter (UVSP) instrument on board the Solar Maximum Mission satellite. These data were studied in conjunction with X-rays from the Hard X-ray Imaging Spectrometer (HXIS) instrument, and with H-alpha and magnetographic data from ground-based observatories. The processes we studied are the active phenomena which result from the interaction of the solar magnetic fields with the plasma in the outer regions of the solar atmosphere. These processes include some very dynamic processes such as the prominence eruptions and the 'microflares'. Our research aimed at characterizing the following: the observed phenomena, the possible physical models, and the relevance to the chromospheric and coronal heating.

Wu, S. T.↗