Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “science data system”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
NASA NTRS2009

Utilizing Remote Sensing Data to Ascertain Soil Moisture Applications and Air Quality Conditions

Recognizing the significance of NASA remote sensing Earth science data in monitoring and better understanding our planet's natural environment, NASA Earth Applied Sciences has implemented the 'Decision Support Through Earth Science Research Results' program. Several applications support systems through collaborations with benefiting organizations have been implemented. The Goddard Earth Sciences Data and Information Services Center (GES DISC) has participated in this program on two projects (one complete, one ongoing), and has had opportune ad hoc collaborations utilizing NASA Earth science data. GES DISC's understanding of Earth science missions and resulting data and information enables the GES DISC to identify challenges that come with bringing science data to research applications. In this presentation we describe applications research projects utilizing NASA Earth science data and a variety of resulting GES DISC applications support system project experiences. In addition, defining metrics that really evaluate success will be exemplified.

Leptoukh, Gregory↗
NASA NTRSDate not supplied

NASA’s Advance Information Systems Technology (AIST) Program

NASA’s Earth Science Technology Office (ESTO) develops early-stage technologies to enhance scientific understanding. ESTO’s technologies can be reliably and confidently applied to a broad range of science measurements and missions, as well as facilitate practical applications to benefit society at large. As the lead technology office within the Earth Science Division of the NASA Science Mission Directorate, ESTO is focused on the technological challenges inherent to space-based investigations of our planet's dynamic, interrelated systems. Through flexible, science-driven technology strategies and a competitive selection process, ESTO-funded technologies have supported numerous Earth science missions as well as commercial applications. From next generation sensors and instruments to communication and information systems, ESTO technologies enable many NASA missions and data services. The Advanced Information Systems Technology (AIST) Program is one focal area of ESTO. AIST innovates information system technologies that enable the development of new observing systems as well as agile science investigations through data analytics and artificial intelligence tools and algorithms. AIST utilizes an end-to-end development approach with the goal of infusing mature technologies into future missions, measurements, and analysis. One thrust of AIST is data exploitation and analysis using an analytic center framework to make observational data and model output more accessible and usable to scientists conducting specific investigations as well as to extract higher-level science content and information from the data. The framework accelerates scientific discovery by harmonizing the data, tools, and computational resources. NASA’s upcoming Surface, Biology and Geology (SBG) mission is one such mission whose data architecture will leverage many of the technologies developed through the AIST program. This talk will highlight current and future program development goals.

Laura Rogers↗
NASA NTRS1995

A Systems Engineering Approach to the Analysis of a Planetary Mission Ground System in Terms of Science Objectives

The most fundamental objective of all planetary missions is to return data. To accomplish this, a spacecraft is fabricated and built, software is planned and coded, and a ground system is designed and implemented. However, a systems engineering approach to determine how the collection of data drives ground system capabilities has received little attention.This paper defines a technique by which science objectives can be quantitatively evaluated. For illustrative purposes, it will be applied to NASA's Cassini Mission. This mission, to be launched in 1997, is an international endeavor designed to orbit Saturn for four years.The results of this systems engineering approach will show which science objectives drive specific ground system capabilities. In addition, this technique can assist system engineers in the selection of the science payload during pre-project mission planning; ground system designers during ground system development and implementation; and operations personnel during the mission.

systems engineering, ground systems↗
NASA NTRS1987

1986 Nuclear Science Symposium, 33rd, and 1986 Symposium on Nuclear Power Systems, 18th, Washington, DC, Oct. 29-31, 1986, Proceedings

Papers are presented on space, low-energy physics, and general nuclear science instrumentations. Topics discussed include data acquisition systems and circuits, nuclear medicine imaging and tomography, and nuclear radiation detectors. Consideration is given to high-energy physics instrumentation, reactor systems and safeguards, health physics instrumentation, and nuclear power systems.

Stubblefield, F. W.↗
NASA NTRS1995

Link Winds: A visual data analysis system and its application to the atmospheric ozone depletion problem

The Linked Windows Interactive Data System (LinkWinds) is a prototype visual data exploration system resulting from a NASA Jet Propulsion Laboratory (JPL) program of research into the application of graphical methods for rapidly accessing, displaying, and analyzing large multi variate multidisciplinary data sets. Running under UNIX it is an integrated multi-application executing environment using a data-linking paradigm to dynamically interconnect and control multiple windows containing a variety of displays and manipulators. This paradigm, resulting in a system similar to a graphical spreadsheet, is not only a powerful method for organizing large amounts of data for analysis, but leads to a highly intuitive, easy-to-learn user interface. It provides great flexibility in rapidly interacting with large masses of complex data to detect trends, correlations, and anomalies. The system, containing an expanding suite of non-domain-specific applications, provides for the ingestion of a variety of data base formats and hard -copy output of all displays. Remote networked workstations running LinkWinds may be interconnected, providing a multiuser science environment (MUSE) for collaborative data exploration by a distributed science team. The system is being developed in close collaboration with investigators in a variety of science disciplines using both archived and real-time data. It is currently being used to support the Microwave Limb Sounder (MLS) in orbit aboard the Upper Atmosphere Research Satellite (UARS). This paper describes the application of LinkWinds to this data to rapidly detect features, such as the ozone hole configuration, and to analyze correlations between chemical constituents of the atmosphere.

Jacobson, Allan S.↗
DOE OSTI2016

Short Distance of Nuclei - Mining the Wealth of Existing Jefferson Lab Data - Final Report

Over the last fifteen years of operation, the Jefferson Lab CLAS Collaboration has performed many experiments using nuclear targets. Because the CLAS detector has a very large acceptance and because it used a very open (i.e., nonspecific) trigger, there is a vast amount of data on many different reaction channels yet to be analyzed. The goal of the Jefferson Lab Nuclear Data Mining grant was to (1) collect the data from nuclear target experiments using the CLAS detector, (2) collect the associated cuts and corrections used to analyze that data, (3) provide non-expert users with a software environment for easy analysis of the data, and (4) to search for interesting reaction signatures in the data. We formed the Jefferson Lab Nuclear Data Mining collaboration under the auspices of this grant. The collaboration successfully carried out all of our goals. Dr. Gavalian, the data mining scientist, created a remarkably user-friendly web-based interface to enable easy analysis of the nuclear-target data by non-experts. Data from many of the CLAS nuclear target experiments has been made available on servers at Old Dominion University. Many of the associated cuts and corrections have been incorporated into the data mining software. The data mining collaboration was extraordinarily successful in finding interesting reaction signatures in the data. Our paper Momentum sharing in imbalanced Fermi systems was published in Science. Several analyses of CLAS data are continuing and will result in papers after the end of the grant period. We have held several analysis workshops and have given many invited talks at international conferences and workshops related to the data mining initiative. Our initiative to maximize the impact of data collected with CLAS in the 6-GeV era was very successful. During the hiatus between the end of 6-GeV experiments and the beginning of 12-GeV experiments, our collaboration and the physics community at large benefited tremendously from the Jefferson Lab Nuclear Data Mining effort.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2019

Computing observation geometry for small satellites

Most solar system science missions need a variety of observation geometry–quantities such as position and velocity, range and altitude, viewing latitude and longitude, and lighting angles– to support mission engineering, science planning, and science data analysis activities. NASA's "SPICE" system offers one popular, multi-mission means for doing just that. SPICE comprises both data files, called kernels, and a SPICE software Toolkit that is available in many popular languages. A mission operations center produces the SPICE kernel files. Scientists and engineers write their own applications programs to address some need, and they include a few SPICE subroutines within that code to do the needed geometry computations. The SPICE system has been in use throughout NASA’s planetary science mission domain since 1991, and it has slowly spread to most major space agencies around the globe since then. The SPICE software is available in most popular languages, and for most popular platforms. The code is thoroughly tested before being released, and new versions of the Toolkit are always backwards compatible. The SPICE components are freely offered to everyone, and have no export, licensing or similar restrictions. Maybe using SPICE would work for your CubeSat or SmallSat mission?

Acton, Charles H.↗
NASA NTRSDate not supplied

PACE OCI Short-Wave Infrared Detection Assembly Optical System Design, Alignment, and Environmental Test

The Ocean Color Instrument (OCI), which will be integrated with the Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) satellite, will collect science data that will be used to monitor the health of Earth’s oceans and atmosphere. The Short-Wave Infrared (SWIR) Detection Assembly (SDA), built and characterized by Utah State University Space Dynamics Laboratory (SDL), is a subsystem of OCI consisting of 32 channels covering seven discrete optical bands of interest. A total of 16 SWIR Detection Subassemblies (SDSs) compose the SDA and house the cold optical system. The science data optical input for each SDS is supplied by a 0.22 NA multimode fiber interfacing with a fiber adapter. The diverging light from the fiber is collimated, split by a dichroic beamsplitter to two separate channels, filtered by the science filter, and then reimaged onto the single-element detectors with a final 0.76 NA. Aspheric, diamond-turned powered elements are used throughout the optical design. Fabrication and alignment tolerance analysis/budgets are balanced to ensure the optical system meets throughput requirements. All systems are aligned at ambient temperature using an InSb camera and an in-line illumination microscope system to directly image the active detector area through the science filters. Compensators used during alignment are detector focus and decenter, which are adjusted via photoetched shims in increments of 25 µm. Average focus and centering errors were less than 8 µm among all 32 flight and 10 flight spare detectors. Each SDS spectral response and conversion gain was verified at operational temperature of -65°C in vacuum.

OCI↗
NASA NTRS2002

Timekeeping for the Space Technology 5 (ST-5) Mission

Space Technology 5, or better known as ST-5, is a space technology development mission in the New Millennium Program (NMP) and NASA s first experiment in the design of miniaturized satellite constellations. The mission will design, integrate and launch multiple spacecraft into an orbit high above the Earth s protective magnetic field known as the magnetosphere. Each spacecraft incorporates innovative technology and constellation concepts which will be instrumental in future space science missions. A total of three ST-5 spacecraft will be launched as secondary payloads into a highly elliptical geo-synchronous transfer orbit, and will operate as a 3-element constellation for a minimum duration of 90 days. In order to correlate the time of science measurements with orbit position relative to the Earth, orbit position in space (with respect to other objects in space) and/or with events measured on Earth or other spacecraft, accurate knowledge of spacecraft and ground time is needed. Ground time as used in the USA (known as Universal Time Coordinated or UTC) is maintained by the U.S. Naval Observatory. Spacecraft time is maintained onboard within the Command and Data Handling (C&DH) system. The science requirements for ST-5 are that spacecraft time and ground time be correlatable to each other, with some degree of accuracy. Accurate knowledge of UTC time on a spacecraft is required so that science measurements can be correlated with orbit position relative to the Earth, orbit position in space and with events measured on Earth or other spacecraft. The most crucial parameter is not the clock oscillator frequency, but more importantly, how the clock oscillator frequency varies with time or temperature (clock oscillator drift). Even with an incorrect clock oscillator frequency, if there were no drift, the frequency could be assessed by comparing the spacecraft clock to a ground clock during a few correlation events. Once the frequency is accurately known, it is easy enough to make a regular adjustment to the spacecraft clock or to calculate the correct ground time for a given spacecraft clock time. The oscillator frequency, however, is temperature dependent, drifts with age and is affected by radiation; hence, repeated correlation measurements are required.

Raphael, Dave↗
NASA NTRS1998

Compact drilling and sample system

The Compact Drilling and Sample System (CDSS) was developed to drill into terrestrial, cometary, and asteroid material in a cryogenic, vacuum environment in order to acquire subsurface samples. Although drills were used by the Apollo astronauts some 20 years ago, this drill is a fraction of the mass and power and operates completely autonomously, able to drill, acquire, transport, dock, and release sample containers in science instruments. The CDSS has incorporated into its control system the ability to gather science data about the material being drilled by measuring drilling rate per force applied and torque. This drill will be able to optimize rotation and thrust in order to achieve the highest drilling rate possible in any given sample. The drill can be commanded to drill at a specified force, so that force imparted on the rover or lander is limited. This paper will discuss the cryo dc brush motors, carbide gears, cryogenic lubrication, quick-release interchangeable sampling drill bits, percussion drilling and the control system developed to achieve autonomous, cryogenic, vacuum, lightweight drilling.

Gillis-Smith, Greg R.↗
DOE OSTI2023

Toward a Smart Metaverse City: Immersive Realism and 3D Visualization of Digital Twin Cities

Metaverse and its related extended reality technologies can enable immersive, realistic, and participatory visualization of 3D data, and their use and the potential within a smart city can be effective for supporting urban research and urban operations management. This book chapter describes a vision for prototyping a “Smart Metaverse City” to combine the unique advantage of the Metaverse technology with the two-way connectivity of a digital twin city application. This synergy aims to create a virtual environment for immersive geovisualization to help researchers and the public understand the complex urban system through science-based and data-driven approaches. This book chapter selectively reviews past technological and paradigm advancements for collecting, analyzing, and visualizing 3D urban big data. Then we present a prototyping Geographic Information System (GIS) framework, together with some relevant data sources and open-source web technologies, to help researchers create a smart Metaverse city. We demonstrate our vision and discuss its application opportunities through a real-world example, a digital twin city developed at the Oak Ridge National Laboratory, to facilitate participatory, smart, and sustainable campus management.

Xu, Haowen↗
DOE OSTI2022

Perceived Costs and Benefits of ICON Science and Foundational Documents associated with “Integrated, Coordinated, Open, and Networked (ICON) Science to Advance the Geosciences: Introduction and Synthesis of a Special Collection of Commentary Articles"

This data package is associated with the publication "Integrated, Coordinated, Open, and Networked (ICON) Science to Advance the Geosciences: Introduction and Synthesis of a Special Collection of Commentary Articles" in Earth and Space Science (Goldman et al. 2022; https://doi.org/10.1029/2021EA002099). The manuscript is an introductory article for a special collection of commentary articles across 19 geoscience disciplines that explore the challenges and opportunities associated with the use of ICON science principles. These principles focus on research intentionally designed to be Integrated, Coordinated, Open, and Networked (ICON) with the goal of maximizing mutual benefit (among stakeholders) and cross-system transferability of science outcomes. This data package contains data, figures, and R scripts associated with the cost/benefit analysis presented in the manuscript. The writing teams involved in the special collection placed each letter of ICON on a plot with perceived cost on one axis and perceived benefit on the other to summarize their perceptions of pursuing each principle of ICON science. These data were subsequently quantified and analyzed. Files are saved as .csv, .R, and .pdf. This data package also contains (1) the public foundational and instructional documents that enabled the crowdsourced creation of the special collection; (2) file-level metadata (flmd) that lists each file in the data package with a description; (3) data dictionary (dd) that defines column headers that appear in csv files. Files are saved as .pdf and .csv.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1994

Automatic cataloguing and characterization of Earth science data using SE-trees

In the future, NASA's Earth Observing System (EOS) platforms will produce enormous amounts of remote sensing image data that will be stored in the EOS Data Information System. For the past several years, the Intelligent Data Management group at Goddard's Information Science and Technology Office has been researching techniques for automatically cataloguing and characterizing image data (ADCC) from EOS into a distributed database. At the core of the approach, scientists will be able to retrieve data based upon the contents of the imagery. The ability to automatically classify imagery is key to the success of contents-based search. We report results from experiments applying a novel machine learning framework, based on Set-Enumeration (SE) trees, to the ADCC domain. We experiment with two images: one taken from the Blackhills region in South Dakota; and the other from the Washington DC area. In a classical machine learning experimentation approach, an image's pixels are randomly partitioned into training (i.e. including ground truth or survey data) and testing sets. The prediction model is built using the pixels in the training set, and its performance is estimated using the testing set. With the first Blackhills image, we perform various experiments achieving an accuracy level of 83.2 percent, compared to 72.7 percent using a Back Propagation Neural Network (BPNN) and 65.3 percent using a Gaussain Maximum Likelihood Classifier (GMLC). However, with the Washington DC image, we were only able to achieve 71.4 percent, compared with 67.7 percent reported for the BPNN model and 62.3 percent for the GMLC.

Rymon, Ron↗
NASA NTRS1989

Earth observing system: 1989 reference handbook

NASA is studying a coordinated effort called the Mission to Planet Earth to understand global change. The goals are to understand the Earth as a system, and to determine those processes that contribute to the environmental balance, as well as those that may result in changes. The Earth Observing System (Eos) is the centerpiece of the program. Eos will create an integrated scientific observing system that will enable multidisciplinary study of the Earth including the atmosphere, oceans, land surface, polar regions, and solid Earth. Science goals, the Eos data and information system, experiments, measuring instruments, and interdisciplinary investigations are described.

Source record↗
NASA NTRS2001

First Flight of the Advanced Thin Ionization Calorimeter (ATIC) Balloon Experiment

The ATILT instrument is designed to measure the composition and energy spectra of Z = 1 to 28 cosmic rays over the energy range -10 GeV - 100 TeV. ATIC was launched as a long duration test balloon flight on 12/28/00 local time from McMurdo, Antarctica. The operations preceding and during launch went very smoothly. During the first -20 hr while the instrument remained within line of sight (LOS), a full system check out was conducted, the experiment was operated in several test configurations, and all major tuning was completed. Preliminary analysis of the science data indicates that the overall detector system is functioning as expected. With our fully functioning analysis software we were able to monitor the data in nearly real time. Each event was reconstructed event-by-event to confirm the detector performance. The shower profiles indicate that the shower maximum location is deeper in the calorimeter for higher energy events, as expected. The energy spectra of protons, Helium nuclei, and "all particles" appear to follow power laws. Both the Si matrix and top scintillator layer of the charge module show clear charge separation for p and He. As the statistics increase, heavy nuclei charge separation will be evaluated. We will present preliminary results of the LOS data, as well as other data that will be available from the flight-data hard disk,

Case, G.↗
NASA NTRS1992

Goldstone solar system radar signal processing

A performance analysis of the planetary radar data acquisition system is presented. These results extend previous computer simulation analysis and are facilitated by the development of a simple analytical model that predicts radar system performance over a wide range of operational parameters. The results of this study are useful to both the radar system designer and the science investigator in establishing operational radar data acquisition parameters which result in the best systems performance for a given set of input conditions.

Jurgens, R.↗
NASA NTRS1994

CESDIS

CESDIS, the Center of Excellence in Space Data and Information Sciences was developed jointly by NASA, Universities Space Research Association (USRA), and the University of Maryland in 1988 to focus on the design of advanced computing techniques and data systems to support NASA Earth and space science research programs. CESDIS is operated by USRA under contract to NASA. The Director, Associate Director, Staff Scientists, and administrative staff are located on-site at NASA's Goddard Space Flight Center in Greenbelt, Maryland. The primary CESDIS mission is to increase the connection between computer science and engineering research programs at colleges and universities and NASA groups working with computer applications in Earth and space science. Research areas of primary interest at CESDIS include: 1) High performance computing, especially software design and performance evaluation for massively parallel machines; 2) Parallel input/output and data storage systems for high performance parallel computers; 3) Data base and intelligent data management systems for parallel computers; 4) Image processing; 5) Digital libraries; and 6) Data compression. CESDIS funds multiyear projects at U. S. universities and colleges. Proposals are accepted in response to calls for proposals and are selected on the basis of peer reviews. Funds are provided to support faculty and graduate students working at their home institutions. Project personnel visit Goddard during academic recess periods to attend workshops, present seminars, and collaborate with NASA scientists on research projects. Additionally, CESDIS takes on specific research tasks of shorter duration for computer science research requested by NASA Goddard scientists.

Source record↗