Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “scientific data”

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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

NASA Tech Briefs, August 2004

Topics covered include: Data Relay Board with Protocol for High-Speed, Free-Space Optical Communications; Software and Algorithms for Biomedical Image Data Processing and Visualization; Rapid Chemometric Filtering of Spectral Data; Prioritizing Scientific Data for Transmission; Determining Sizes of Particles in a Flow from DPIV Data; Faster Processing for Inverting GPS Occultation Data; FPGA-Based, Self-Checking, Fault-Tolerant Computers; Ultralow-Power Digital Correlator for Microwave Polarimetry; Grounding Headphones for Protection Against ESD; Lightweight Stacks of Direct Methanol Fuel Cells; Highly Efficient Vector-Inversion Pulse Generators; Estimating Basic Preliminary Design Performances of Aerospace Vehicles; Framework for Development of Object-Oriented Software; Analyzing Spacecraft Telecommunication Systems; Collaborative Planning of Robotic Exploration; Tools for Administration of a UNIX-Based Network; Preparing and Analyzing Iced Airfoils; Evaluating Performance of Components; Fuels Containing Methane of Natural Gas in Solution; Direct Electrolytic Deposition of Mats of MnxOy Nanowires; Bubble Eliminator Based on Centrifugal Flow; Inflatable Emergency Atmospheric-Entry Vehicles; Lightweight Deployable Mirrors with Tensegrity Supports; Centrifugal Adsorption Cartridge System; Ultrasonic Apparatus for Pulverizing Brittle Material; Transplanting Retinal Cells using Bucky Paper for Support; Using an Ultrasonic Instrument to Size Extravascular Bubbles; Coronagraphic Notch Filter for Raman Spectroscopy; On-the-Fly Mapping for Calibrating Directional Antennas; Working Fluids for Increasing Capacities of Heat Pipes; Computationally-Efficient Minimum-Time Aircraft Routes in the Presence of Winds; Liquid-Metal-Fed Pulsed Plasma Thrusters; Personal Radiation Protection System; and Attitude Control for a Solar-Sail Spacecraft.

Source record↗
NASA NTRSDate not supplied

Enabling Dynamic Data Governance in Science: Design, Implementation, and Future Directions of the Modern Data Governance Framework

As scientific data volumes exponentially grow, dynamic, flexible and open approaches to data governance are needed. In this paper, we describe our efforts to build an open, scientific Modern Data Governance Framework (mDGF) that streamlines and makes actionable data governance requirements for projects and data providers. We present the goals and design of the mDGF. We also share our envisioned usage for the mDGF and planned future work.

Kaylin Bugbee↗
NASA NTRS1975

Main principles used for building up a data bank for the long-term storage and retrieval of scientific space data

Methodological, technical, and practical organizational problems are considered of constructing a long term data bank. Data processing flowcharts are presented which are based on an analysis of the tasks which the data bank must fulfill, an estimate of the existing and predicted data flows in the processing center, and the selection of the data storage media and the forms in which the data are presented. Questions related to the use of standard and special hardware and software in the data bank are discussed. Reasons are presented for the adopted structure of the document-fact type information retrieval system which permits the mechanization and automation of various stages in the retrieval and selection of the data.

Zlotin, G. N.↗
NASA NTRS1982

Lunar seismic data analysis

The scientific data transmitted continuously from all ALSEP (Apollo Lunar Surface Experiment Package) stations on the Moon and recorded on instrumentation tapes at receiving stations distributed around the Earth were processed. The processing produced sets of computer-compatible digital tapes, from which various other data sets convenient for analysis were generated. The seismograms were read, various types of seismic events were classified; the detected events were cataloged.

Nakamura, Y.↗
NASA NTRS2014

Anticipated Changes in Conducting Scientific Data-Analysis Research in the Big-Data Era

A Big-Data environment is one that is capable of orchestrating quick-turnaround analyses involving large volumes of data for numerous simultaneous users. Based on our experiences with a prototype Big-Data analysis environment, we anticipate some important changes in research behaviors and processes while conducting scientific data-analysis research in the near future as such Big-Data environments become the mainstream. The first anticipated change will be the reduced effort and difficulty in most parts of the data management process. A Big-Data analysis environment is likely to house most of the data required for a particular research discipline along with appropriate analysis capabilities. This will reduce the need for researchers to download local copies of data. In turn, this also reduces the need for compute and storage procurement by individual researchers or groups, as well as associated maintenance and management afterwards. It is almost certain that Big-Data environments will require a different "programming language" to fully exploit the latent potential. In addition, the process of extending the environment to provide new analysis capabilities will likely be more involved than, say, compiling a piece of new or revised code.We thus anticipate that researchers will require support from dedicated organizations associated with the environment that are composed of professional software engineers and data scientists. A major benefit will likely be that such extensions are of higherquality and broader applicability than ad hoc changes by physical scientists. Another anticipated significant change is improved collaboration among the researchers using the same environment. Since the environment is homogeneous within itself, many barriers to collaboration are minimized or eliminated. For example, data and analysis algorithms can be seamlessly shared, reused and re-purposed. In conclusion, we will be able to achieve a new level of scientific productivity in the Big-Data analysis environments.

Kuo, Kwo-Sen↗
NASA NTRSDate not supplied

Extravehicular Activity Mission System Software (EMSS) - Enabling Human Planetary Exploration Data Within The Broader Planetary Data Ecosystem

The planetary science community is once again on the verge of generating, capturing and analyzing human planetary exploration data, this time via the Artemis program. Artemis missions will involve robotic missions in addition to human extravehicular activity (EVA) where crew will be generating scientific data [1]. Present-day robotic mission data expectations for data archiving involves ingesting data into the Planetary Data System (PDS), but how might PDS be leveraged/adapted/ready (or not) for human spaceflight mission data, particularly EVA data that includes non-scientific data that provides important context to the scientific data gathered on the lunar surface? This question has broader implications than what this abstract can answer, but we wanted to pose the question to 1) get conversations started and 2) highlight how operations software data handling could play a role in overall data curation.

M J Miller↗
NASA NTRS1989

A rapid prototyping/artificial intelligence approach to space station-era information management and access

Applications of rapid prototyping and Artificial Intelligence techniques to problems associated with Space Station-era information management systems are described. In particular, the work is centered on issues related to: (1) intelligent man-machine interfaces applied to scientific data user support, and (2) the requirement that intelligent information management systems (IIMS) be able to efficiently process metadata updates concerning types of data handled. The advanced IIMS represents functional capabilities driven almost entirely by the needs of potential users. Space Station-era scientific data projected to be generated is likely to be significantly greater than data currently processed and analyzed. Information about scientific data must be presented clearly, concisely, and with support features to allow users at all levels of expertise efficient and cost-effective data access. Additionally, mechanisms for allowing more efficient IIMS metadata update processes must be addressed. The work reported covers the following IIMS design aspects: IIMS data and metadata modeling, including the automatic updating of IIMS-contained metadata, IIMS user-system interface considerations, including significant problems associated with remote access, user profiles, and on-line tutorial capabilities, and development of an IIMS query and browse facility, including the capability to deal with spatial information. A working prototype has been developed and is being enhanced.

Carnahan, Richard S., Jr.↗
NASA NTRS1993

Improved determination of vector lithospheric magnetic anomalies from MAGSAT data

Scientific contributions made in developing new methods to isolate and map vector magnetic anomalies from measurements made by Magsat are described. In addition to the objective of the proposal, the isolation and mapping of equatorial vector lithospheric Magsat anomalies, isolation of polar ionospheric fields during the period were also studied. Significant progress was also made in isolation of polar delta(Z) component and scalar anomalies as well as integration and synthesis of various techniques of removing equatorial and polar ionospheric effects. The significant contributions of this research are: (1) development of empirical/analytical techniques in modeling ionospheric fields in Magsat data and their removal from uncorrected anomalies to obtain better estimates of lithospheric anomalies (this task was accomplished for equatorial delta(X), delta(Z), and delta(B) component and polar delta(Z) and delta(B) component measurements; (2) integration of important processing techniques developed during the last decade with the newly developed technologies of ionospheric field modeling into an optimum processing scheme; and (3) implementation of the above processing scheme to map the most robust magnetic anomalies of the lithosphere (components as well as scalar).

Ravat, Dhananjay↗
NASA NTRS1974

Automated system for measurement, collection and processing of hydrometeorological data aboard scientific research vessels of the GUGMS (SIGMA-s)

A report is made on the automated system known as SIGMA-s for the measurement, collection, and processing of hydrometeorological data aboard scientific research vessels of the Hydrometeorological Service. The various components of the system and the interfacing between them are described, as well as the projects that the system is equipped to handle.

Borisenkov, Y. P.↗
NASA NTRS1974

Apollo scientific experiments data handbook

A brief description of each of the Apollo scientific experiments was described, together with its operational history, the data content and formats, and the availability of the data. The lunar surface experiments described are the passive seismic, active seismic, lunar surface magnetometer, solar wind spectrometer, suprathermal ion detector, heat flow, charged particle, cold cathode gage, lunar geology, laser ranging retroreflector, cosmic ray detector, lunar portable magnetometer, traverse gravimeter, soil mechanics, far UV camera (lunar surface), lunar ejecta and meteorites, surface electrical properties, lunar atmospheric composition, lunar surface gravimeter, lunar seismic profiling, neutron flux, and dust detector. The orbital experiments described are the gamma-ray spectrometer, X-ray fluorescence, alpha-particle spectrometer, S-band transponder, mass spectrometer, far UV spectrometer, bistatic radar, IR scanning radiometer, particle shadows, magnetometer, lunar sounder, and laser altimeter. A brief listing of the mapping products available and information on the sample program were also included.

Eichelman, W. F.↗
NASA NTRS2002

NASA IKONOS Radiometric Characterization

NASA acquired imagery from the IKONOS satellite as part of its Scientific Data Purchase (SDP) program, which purchases scientific data sets from commercial sources. This viewgraph presentation describes the IKONOS satellite and its sensors, and then gives an overview of characterization efforts undertaken by NASA in cooperation with other government agencies. The characterization included relative radiometric correction, absolute radiometric characterization of data from Lunar Lake Playa, Nevada, and calibration of data from Stennis Space Center, Mississippi.

Pagnutti, Mary↗
NASA NTRS2016

Analysis of CrIS ATMS and AIRS AMSU Data Using Scientifically Equivalent Retrieval Algorithms

Monthly mean August 2014 Version-6.28 AIRS and CrIS products agree well with OMPS and CERES, and reasonably well with each other. Version-6.28 CrIS total precipitable water is biased dry compared to AIRS. AIRS and CrIS Version-6.36 water vapor products are both improved compared to Version-6.28. Version-6.36 AIRS and CrIS total precipitable water also shows improved agreement with each other. AIRS Version-6.36 total ozone agrees even better with OMPS than does AIRS Version-6.28, and gives reasonable results during polar winter where OMPS does not generate products. CrIS and ATMS are high spectral resolution IR and Microwave atmospheric sounders currently flying on the SNPP satellite, and are also scheduled for flight on future NPOESS satellites. CrIS/ATMS have similar sounding capabilities to those of the AIRS/AMSU sounder suite flying on EOS Aqua. The objective of this research is to develop and implement scientifically equivalent AIRS/AMSU and CrIS/ATMS retrieval algorithms with the goal of generating a continuous data record of AIRS/AMSU and CrIS/ATMS level-3 data products with a seamless transition between them in time. To achieve this, monthly mean AIRS/AMSU and CrIS/ATMS retrieved products, and more importantly their interannual differences, should show excellent agreement with each other. The currently operational AIRS Science Team Version-6 retrieval algorithm has generated 14 years of level-3 data products. A scientifically improved AIRS Version-7 retrieval algorithm is expected to become operational in 2017. We see significant improvements in water vapor and ozone in Version-7 retrieval methodology compared to Version-6.We are working toward finalization and implementation of scientifically equivalent AIRS/AMSU and CrIS/ATMS Version-7 retrieval algorithms to be used for the eventual processing of all AIRS/AMSU and CrIS/ATMS data. The latest version of our retrieval algorithm is Verison-6.36, which includes almost all the improvements we want in Version-7. Version-6.28 has been used to process both AIRS and CrIS data for August 2014. This poster compares August 2014 monthly mean Version-6.28 AIRS/AMSU and CrIS/ATMS products with each other, and also with monthly mean products obtained using AIRS Version-6. AIRS and CrIS results using Version-6.36 are presented for April 15, 2016. These demonstrate further improvements since Version-6.28. The new results also show improved agreement of Version-6.36 AIRS and CrIS products with each other. Version-6.36 is not yet optimized for CrIS ozone products.

AIRS↗
NASA NTRS1993

Publication of science data on CD-ROM: A guide and example

CD-ROM (Compact Disk-Read Only Memory) is becoming the standard media not only in audio recording, but also in the publication of data and information accessible on many computer platforms. Little has been written about the complicated process involved in creating easy-to-use, high quality, and useful CD-ROM's containing scientific data. This document is a manual designed to aid those who are responsible for the publication of scientific data on CD-ROM. All aspects and steps of the procedure are covered, from feasibility assessment through disk design, data preparation, disc mastering, and CD-ROM distribution. General advice and actual examples are based on lessons learned from the publication of scientific data for an interdisciplinary field experiment. Appendices include actual files from a CD-ROM, a purchase request for CD-ROM mastering services, and the disk art for the first disk published for the project.

Angelici, Gary↗
NASA NTRS2010

A History of NASA Remote Sensing Contributions to Archaeology

During its long history of developing and deploying remote sensing instruments, NASA has provided a scientific data that have benefitted a variety of scientific applications among them archaeology. Multispectral and hyperspectral instrument mounted on orbiting and suborbital platforms have provided new and important information for the discovery, delineation and analysis of archaeological sites worldwide. Since the early 1970s, several of the ten NASA centers have collaborated with archaeologists to refine and validate the use of active and passive remote sensing for archeological use. The Stennis Space Center (SSC), located in Mississippi USA has been the NASA leader in archeological research. Together with colleagues from Goddard Space Flight Center (GSFC), Marshall Space Flight Center (MSFC), and the Jet Propulsion Laboratory (JPL), SSC scientists have provided the archaeological community with useful images and sophisticated processing that have pushed the technological frontiers of archaeological research and applications. Successful projects include identifying prehistoric roads in Chaco canyon, identifying sites from the Lewis and Clark Corps of Discovery exploration and assessing prehistoric settlement patterns in southeast Louisiana. The Scientific Data Purchase (SDP) stimulated commercial companies to collect archaeological data. At present, NASA formally solicits "space archaeology" proposals through its Earth Science Directorate and continues to assist archaeologists and cultural resource managers in doing their work more efficiently and effectively. This paper focuses on passive remote sensing and does not consider the significant contributions made by NASA active sensors. Hyperspectral data offers new opportunities for future archeological discoveries.

Giardino, Marco J.↗
NASA NTRS2013

Tool for Automated Retrieval of Generic Event Tracks (TARGET)

Methods have been developed to identify and track tornado-producing mesoscale convective systems (MCSs) automatically over the continental United States, in order to facilitate systematic studies of these powerful and often destructive events. Several data sources were combined to ensure event identification accuracy. Records of watches and warnings issued by National Weather Service (NWS), and tornado locations and tracks from the Tornado History Project (THP) were used to locate MCSs in high-resolution precipitation observations and GOES infrared (11-micron) Rapid Scan Operation (RSO) imagery. Thresholds are then applied to the latter two data sets to define MCS events and track their developments. MCSs produce a broad range of severe convective weather events that are significantly affecting the living conditions of the populations exposed to them. Understanding how MCSs grow and develop could help scientists improve their weather prediction models, and also provide tools to decision-makers whose goals are to protect populations and their property. Associating storm cells across frames of remotely sensed images poses a difficult problem because storms evolve, split, and merge. Any storm-tracking method should include the following processes: storm identification, storm tracking, and quantification of storm intensity and activity. The spatiotemporal coordinates of the tracks will enable researchers to obtain other coincident observations to conduct more thorough studies of these events. In addition to their tracked locations, their areal extents, precipitation intensities, and accumulations all as functions of their evolutions in time were also obtained and recorded for these events. All parameters so derived can be catalogued into a moving object database (MODB) for custom queries. The purpose of this software is to provide a generalized, cross-platform, pluggable tool for identifying events within a set of scientific data based upon specified criteria with the possibility of storing identified events into a searchable database. The core of the application uses an implementation of the connected component labeling (CCL) algorithm to identify areas of interest, then uses a set of criteria to establish spatial and temporal relationships between identified components. The CCL algorithm is used for identifying objects within images for computer vision. This application applies it to scientific data sets using arbitrary criteria. The most novel concept was applying a generalized CCL implementation to scientific data sets for establishing events both spatially and temporally. The combination of several existing concepts (pluggable components, generalized CCL algorithm, etc.) into one application is also novel. In addition, how the system is designed, i.e., its extensibility with pluggable components, and its configurability with a simple configuration file, is innovative. This allows the system to be applied to new scenarios with ease.

Clune, Thomas↗
NASA NTRS2001

The Role of Advanced Information System Technology in Remote Sensing for NASA's Earth Science Enterprise in the 21st Century

Future NASA Earth observing satellites will carry high-precision instruments capable of producing large amounts of scientific data. The strategy will be to network these instrument-laden satellites into a web-like array of sensors to facilitate the collection, processing, transmission, storage, and distribution of data and data products - the essential elements of what we refer to as "Information Technology." Many of these Information Technologies will enable the satellite and ground information systems to function effectively in real-time, providing scientists with the capability of customizing data collection activities on a satellite or group of satellites directly from the ground. In future systems, extremely large quantities of data collected by scientific instruments will require the fastest processors, the highest communication channel transfer rates, and the largest data storage capacity to insure that data flows smoothly from the satellite-based instrument to the ground-based archive. Autonomous systems will control all essential processes and play a key role in coordinating the data flow through space-based communication networks. In this paper, we will discuss those critical information technologies for Earth observing satellites that will support the next generation of space-based scientific measurements of planet Earth, and insure that data and data products provided by these systems will be accessible to scientists and the user community in general.

Prescott, Glenn↗