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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 NTRS2013

NASA Tech Briefs, April 2013

Topics covered include: Fully Integrated, Miniature, High-Frequency Flow Probe Utilizing MEMS Leadless SOI Technology; Nanoscale Surface Plasmonics Sensor With Nanofluidic Control; Advanced Dispersed Fringe Sensing Algorithm for Coarse Phasing Segmented Mirror Telescopes; Neural Network Back-Propagation Algorithm for Sensing Hypergols; Bulk Moisture and Salinity Sensor; Change-Based Satellite Monitoring Using Broad Coverage and Targetable Sensing; Circularly Polarized Microwave Antenna Element with Very Low Off-Axis Cross-Polarization; Ultra-Low Heat-Leak, High-Temperature Superconducting Current Leads for Space Applications; Flash Cracking Reactor for Waste Plastic Processing; An Automated Safe-to-Mate (ASTM) Tester; Wireless Chalcogenide Nanoionic-Based Radio-Frequency Switch; Compute Element and Interface Box for the Hazard Detection System; DOT Transmit Module; Composite Aerogel Multifoil Protective Shielding; Li-Ion Electrolytes with Improved Safety and Tolerance to High-Voltage Systems; Polymer-Reinforced, Non-Brittle, Lightweight Cryogenic Insulation; Controlled, Site-Specific Functionalization of Carbon Nanotubes with Diazonium Salts; Regenerable Sorbent for CO2 Removal; Sprayable Aerogel Bead Compositions With High Shear Flow Resistance and High Thermal Insulation Value; Lexan Linear Shaped Charge Holder with Magnets and Backing Plate; Robotic Ankle for Omnidirectional Rock Anchors; Wind, Wave, and Tidal Energy Without Power Conditioning; An Active Heater Control Concept to Meet IXO Type Mirror Module Thermal-Structural Distortion Requirement; Waterless Clothes-Cleaning Machine; Integrated Electrical Wire Insulation Repair System; LVGEMS Time-of-Flight Mass Spectrometry on Satellites; Surface Inspection Tool for Optical Detection of Surface Defects; Per-Pixel, Dual-Counter Scheme for Optical Communications; Certification-Based Process Analysis; Surface Navigation Using Optimized Waypoints and Particle Swarm Optimization; Smart-Divert Powered Descent Guidance to Avoid the Backshell Landing Dispersion Ellipse; Estimating Foreign-Object-Debris Density from Photogrammetry Data; Adaptive Sampling of Spatiotemporal Phenomena with Optimization Criteria; Building a 2.5D Digital Elevation Model From 2D Imagery; Eyes on the Earth 3D; Target Trailing With Safe Navigation for Maritime Autonomous Surface Vehicles; Adams-Based Rover Terramechanics and Mobility Simulator - ARTEMIS; ISTP CDF Skeleton Editor; Uplink Summary Generator (ULSGEN) Version 1.0; Robotics On-Board Trainer (ROBoT); Software Engineering Tools for Scientific Models; Automatic Data Filter Customization Using a Genetic Algorithm; Tracker Toolkit; Towards Efficient Scientific Data Management Using Cloud Storage; On a Formal Tool for Reasoning About Flight Software Cost Analysis; A Nanostructured Composites Thermal Switch Controls Internal and External Short Circuit in Lithium Ion Batteries; Spacecraft Crew Cabin Condensation Control; and Functional Near-Infrared Spectroscopy Signals Measure Neuronal Activity in the Cortex.

Source record↗
NASA NTRS1996

Geodata Modeling and Query in Geographic Information Systems

Geographic information systems (GIS) deal with collecting, modeling, man- aging, analyzing, and integrating spatial (locational) and non-spatial (attribute) data required for geographic applications. Examples of spatial data are digital maps, administrative boundaries, road networks, and those of non-spatial data are census counts, land elevations and soil characteristics. GIS shares common areas with a number of other disciplines such as computer- aided design, computer cartography, database management, and remote sensing. None of these disciplines however, can by themselves fully meet the requirements of a GIS application. Examples of such requirements include: the ability to use locational data to produce high quality plots, perform complex operations such as network analysis, enable spatial searching and overlay operations, support spatial analysis and modeling, and provide data management functions such as efficient storage, retrieval, and modification of large datasets; independence, integrity, and security of data; and concurrent access to multiple users. It is on the data management issues that we devote our discussions in this monograph. Traditionally, database management technology have been developed for business applications. Such applications require, among other things, capturing the data requirements of high-level business functions and developing machine- level implementations; supporting multiple views of data and yet providing integration that would minimize redundancy and maintain data integrity and security; providing a high-level language for data definition and manipulation; allowing concurrent access to multiple users; and processing user transactions in an efficient manner. The demands on database management systems have been for speed, reliability, efficiency, cost effectiveness, and user-friendliness. Significant progress have been made in all of these areas over the last two decades to the point that many generalized database platforms are now available for developing data intensive applications that run in real-time. While continuous improvement is still being made at a very fast-paced and competitive rate, new application areas such as computer aided design, image processing, VLSI design, and GIS have been identified by many as the next generation of database applications. These new application areas pose serious challenges to the currently available database technology. At the core of these challenges is the nature of data that is manipulated. In traditional database applications, the database objects do not have any spatial dimension, and as such, can be thought of as point data in a multi-dimensional space. For example, each instance of an entity EMPLOYEE will have a unique value corresponding to every attribute such as employee id, employee name, employee address and so on. Thus, every Employee instance can be thought of as a point in a multi-dimensional space where each dimension is represented by an attribute. Furthermore, all operations on such data are one-dimensional. Thus, users may retrieve all entities satisfying one or more constraints. Examples of such constraints include employees with addresses in a certain area code, or salaries within a certain range. Even though constraints can be specified on multiple attributes (dimensions), the search for such data is essentially orthogonal across these dimensions.

Adam, Nabil↗
NASA NTRS1993

NASA Langley Research Center's distributed mass storage system

There is a trend in institutions with high performance computing and data management requirements to explore mass storage systems with peripherals directly attached to a high speed network. The Distributed Mass Storage System (DMSS) Project at NASA LaRC is building such a system and expects to put it into production use by the end of 1993. This paper presents the design of the DMSS, some experiences in its development and use, and a performance analysis of its capabilities. The special features of this system are: (1) workstation class file servers running UniTree software; (2) third party I/O; (3) HIPPI network; (4) HIPPI/IPI3 disk array systems; (5) Storage Technology Corporation (STK) ACS 4400 automatic cartridge system; (6) CRAY Research Incorporated (CRI) CRAY Y-MP and CRAY-2 clients; (7) file server redundancy provision; and (8) a transition mechanism from the existent mass storage system to the DMSS.

Pao, Juliet Z.↗
NASA NTRS1994

Managing People's Data

Just imagine a mass storage system that consists of a machine with 2 CPUs, 1 Gigabyte (GB) of memory, 400 GB of disk space, 16800 cartridge tapes in the automated tape silos, 88,000 tapes located in the vault, and the software to manage the system. This system is designed to be a data repository; it will always have disk space to store all the incoming data. Currently 9.14 GB of new data per day enters the system with this rate doubling each year. To assure there is always disk space available for new data, the system. has to move data reside from the expensive disk to a much less expensive medium such as the 3480 cartridge tapes. Once the data is archived to tape, it should be able to move back to disk when someone wants to access it and the data movement should be transparent to the user. Now imagine all the tasks that a system administrator must perform to keep this system running 24 hour a day, 7 days a week. Since the filesystem maintains the illusion of unlimited disk space, data that comes to the system must get moved to tapes in an efficient manner. This paper will describe the mass storage system running at the Numerical Aerodynamic Simulation (NAS) at NASA Ames Research Center in both software and hardware aspects, then it will describe all of the tasks the system administrator has to perform on this system.

Le, Diana↗
NASA NTRS1984

Managing geometric information with a data base management system

The strategies for managing computer based geometry are described. The computer model of geometry is the basis for communication, manipulation, and analysis of shape information. The research on integrated programs for aerospace-vehicle design (IPAD) focuses on the use of data base management system (DBMS) technology to manage engineering/manufacturing data. The objectives of IPAD is to develop a computer based engineering complex which automates the storage, management, protection, and retrieval of engineering data. In particular, this facility must manage geometry information as well as associated data. The approach taken on the IPAD project to achieve this objective is discussed. Geometry management in current systems and the approach taken in the early IPAD prototypes are examined.

Dube, R. P.↗
NASA NTRS2001

External Data and Attribute Hyperlink Programs for Promis*e(Registered Trademark)

External Data and Attribute Hyperlink are computer programs that can be added to Promis*e(trademark) which is a commercial software system that automates routine tasks in the design (including drawing schematic diagrams) of electrical control systems. The programs were developed under the Stennis Space Center's (SSC) Dual Use Technology Development Program to provide capabilities for SSC's BMCS configuration management system which uses Promis*e(trademark). The External Data program enables the storage and management of information in an external database linked to a drawing. Changes can be made either in the database or on the drawing. Information that originates outside Promis*e(trademark) can be stored in custom fields that can be added to the database. Although this information is not available in Promis*e(trademark) printed drawings, it can be associated with symbols in the drawings, and can be retrieved through the drawings when the software is running. The Attribute Hyperlink program enables the addition of hyperlink information as attributes of symbols. This program enables the formation of a direct hyperlink between a schematic diagram and an Internet site or a file on a compact disk, on the user's hard drive, or on another computer on a network to which the user's computer is connected. The user can then obtain information directly related to the part (e.g., maintenance, or troubleshooting information) associated with the hyperlink.

Derengowski, Rich↗
NASA NTRS1986

A database management capability for Ada

The data requirements of mission critical defense systems have been increasing dramatically. Command and control, intelligence, logistics, and even weapons systems are being required to integrate, process, and share ever increasing volumes of information. To meet this need, systems are now being specified that incorporate data base management subsystems for handling storage and retrieval of information. It is expected that a large number of the next generation of mission critical systems will contain embedded data base management systems. Since the use of Ada has been mandated for most of these systems, it is important to address the issues of providing data base management capabilities that can be closely coupled with Ada. A comprehensive distributed data base management project has been investigated. The key deliverables of this project are three closely related prototype systems implemented in Ada. These three systems are discussed.

Chan, Arvola↗
NASA NTRS2012

Investigation into Cloud Computing for More Robust Automated Bulk Image Geoprocessing

Geospatial resource assessments frequently require timely geospatial data processing that involves large multivariate remote sensing data sets. In particular, for disasters, response requires rapid access to large data volumes, substantial storage space and high performance processing capability. The processing and distribution of this data into usable information products requires a processing pipeline that can efficiently manage the required storage, computing utilities, and data handling requirements. In recent years, with the availability of cloud computing technology, cloud processing platforms have made available a powerful new computing infrastructure resource that can meet this need. To assess the utility of this resource, this project investigates cloud computing platforms for bulk, automated geoprocessing capabilities with respect to data handling and application development requirements. This presentation is of work being conducted by Applied Sciences Program Office at NASA-Stennis Space Center. A prototypical set of image manipulation and transformation processes that incorporate sample Unmanned Airborne System data were developed to create value-added products and tested for implementation on the "cloud". This project outlines the steps involved in creating and testing of open source software developed process code on a local prototype platform, and then transitioning this code with associated environment requirements into an analogous, but memory and processor enhanced cloud platform. A data processing cloud was used to store both standard digital camera panchromatic and multi-band image data, which were subsequently subjected to standard image processing functions such as NDVI (Normalized Difference Vegetation Index), NDMI (Normalized Difference Moisture Index), band stacking, reprojection, and other similar type data processes. Cloud infrastructure service providers were evaluated by taking these locally tested processing functions, and then applying them to a given cloud-enabled infrastructure to assesses and compare environment setup options and enabled technologies. This project reviews findings that were observed when cloud platforms were evaluated for bulk geoprocessing capabilities based on data handling and application development requirements.

Brown, Richard B.↗
DOE OSTI2025

Data Management in the Continuum: Cross-facility Object-based Data Transfers

Scientific workflows are evolving from relying on a monolithic storage subsystem at a single High-Performance Computing (HPC) facility to using geographically distributed file systems, repositories, and cloud storage. As a result, storing, accessing, transferring, and managing scientific data have become highly complex and prone to performance inefficiencies. This paper delves into these challenges by exploring an optimized end-to-end interface designed to seamlessly connect various local and remote storage systems, enabling efficient data movement of objects across HPC–Cloud and HPC–HPC environments. We showcase this capability through an object-focused data management runtime system, discuss the effects of relaxed consistency semantics in distributed object scenarios, and illustrate its application in an earthquake simulation workflow. Besides reducing the amount of data by selectively transferring regions of interest, our facility-local results achieved a speedup of 45 × over an optimized HDF5 usage and 15 × over the HDF5 with caching by using the new interface in PDC-XF.

Bez, Jean Luca↗
NASA NTRS1996

NASDA's earth observation satellite data archive policy for the earth observation data and information system (EOIS)

NASDA's new Advanced Earth Observing Satellite (ADEOS) is scheduled for launch in August, 1996. ADEOS carries 8 sensors to observe earth environmental phenomena and sends their data to NASDA, NASA, and other foreign ground stations around the world. The downlink data bit rate for ADEOS is 126 MB/s and the total volume of data is about 100 GB per day. To archive and manage such a large quantity of data with high reliability and easy accessibility it was necessary to develop a new mass storage system with a catalogue information database using advanced database management technology. The data will be archived and maintained in the Master Data Storage Subsystem (MDSS) which is one subsystem in NASDA's new Earth Observation data and Information System (EOIS). The MDSS is based on a SONY ID1 digital tape robotics system. This paper provides an overview of the EOIS system, with a focus on the Master Data Storage Subsystem and the NASDA Earth Observation Center (EOC) archive policy for earth observation satellite data.

Sobue, Shin-ichi↗
NASA NTRS1973

Evolution of the satellite telemetry data processing facility at the Goddard Space Flight Center.

Data from scientific and application satellites managed by the NASA Goddard Space Flight Center are acquired through the world-wide Spacecraft Tracking and Data Network (STDN). These data are forwarded to a central telemetry data processing facility whose primary objective is the timely provision of the data to users in a form suitable for their analysis. In a successful evolution, a satellite data processing facility must adapt to changing support requirements while operationally supporting active spacecraft. Advances in the technology of data transmission, data storage systems, and file management make it feasible to implement a third-generation system which will be able to satisfy experimenter requirements for the next ten years.

Keipert, F. A.↗
NASA NTRS1996

Use of HSM with Relational Databases

Hierarchical storage management (HSM) systems have evolved to become a critical component of large information storage operations. They are built on the concept of using a hierarchy of storage technologies to provide a balance in performance and cost. In general, they migrate data from expensive high performance storage to inexpensive low performance storage based on frequency of use. The predominant usage characteristic is that frequency of use is reduced with age and in most cases quite rapidly. The result is that HSM provides an economical means for managing and storing massive volumes of data. Inherent in HSM systems is system managed storage, where the system performs most of the work with minimum operations personnel involvement. This automation is generally extended to include: backup and recovery, data duplexing to provide high availability, and catastrophic recovery through use of off-site storage.

Breeden, Randall↗
NASA NTRS1996

Advanced optical disk storage technology

There is a growing need within the Air Force for more and better data storage solutions. Rome Laboratory, the Air Force's Center of Excellence for C3I technology, has sponsored the development of a number of operational prototypes to deal with this growing problem. This paper will briefly summarize the various prototype developments with examples of full mil-spec and best commercial practice. These prototypes have successfully operated under severe space, airborne and tactical field environments. From a technical perspective these prototypes have included rewritable optical media ranging from a 5.25-inch diameter format up to the 14-inch diameter disk format. Implementations include an airborne sensor recorder, a deployable optical jukebox and a parallel array of optical disk drives. They include stand-alone peripheral devices to centralized, hierarchical storage management systems for distributed data processing applications.

Haritatos, Fred N.↗
NASA NTRS2002

Enabling Earth Science: The Facilities and People of the NCCS

The NCCS's mass data storage system allows scientists to store and manage the vast amounts of data generated by these computations, and its high-speed network connections allow the data to be accessed quickly from the NCCS archives. Some NCCS users perform studies that are directly related to their ability to run computationally expensive and data-intensive simulations. Because the number and type of questions scientists research often are limited by computing power, the NCCS continually pursues the latest technologies in computing, mass storage, and networking technologies. Just as important as the processors, tapes, and routers of the NCCS are the personnel who administer this hardware, create and manage accounts, maintain security, and assist the scientists, often working one on one with them.

Source record↗
NASA NTRS1996

Fifth NASA Goddard Conference on Mass Storage Systems and Technologies.

This document contains copies of those technical papers received in time for publication prior to the Fifth Goddard Conference on Mass Storage Systems and Technologies. As one of an ongoing series, this conference continues to serve as a unique medium for the exchange of information on topics relating to the ingestion and management of substantial amounts of data and the attendant problems involved. This year's discussion topics include storage architecture, database management, data distribution, file system performance and modeling, and optical recording technology. There will also be a paper on Application Programming Interfaces (API) for a Physical Volume Repository (PVR) defined in Version 5 of the Institute of Electrical and Electronics Engineers (IEEE) Reference Model (RM). In addition, there are papers on specific archives and storage products.

Kobler, Benjamin↗
DOE OSTI2026

Scientific Data Compression for Large Scale Computational Fluid Dynamics (CFD) Simulations

This Cooperative Research and Development Agreement (CRADA) between Oak Ridge National Laboratory (ORNL) and General Electric (GE) investigated methods for reducing the size of large computational fluid dynamics (CFD) simulation datasets using scientific data compression techniques. The work focused on adapting the MultiGrid Adaptive Reduction of Data (MGARD) compression framework and integrating it with high-performance I/O and visualization tools used in CFD workflows. MGARD uses hierarchical multilevel decomposition to enable error-controlled compression of floating-point scientific data while preserving quantities of interest. During the project, MGARD compression was integrated with the ADIOS I/O framework and visualization tools such as ParaView to enable efficient storage, transfer, and analysis of simulation data. The collaboration also explored approaches for improving compression performance for CFD data defined on unstructured meshes. Results demonstrate that scientific data compression can significantly reduce storage requirements and improve data management for large-scale CFD simulations.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1987

A review of hypertext in a NASA project management context

The principles of data storage, the comparative strengths of data bases, and the evolution of hypertext within this context are discussed. A classification schema of indexing and of hypertext document structures is provided. Issues associated with hypertext implementation are also discussed and potential areas for further research are indicated.

Bell, Christopher J.↗
NASA NTRS1995

Visualization Techniques in Space and Atmospheric Sciences

Unprecedented volumes of data will be generated by research programs that investigate the Earth as a system and the origin of the universe, which will in turn require analysis and interpretation that will lead to meaningful scientific insight. Providing a widely distributed research community with the ability to access, manipulate, analyze, and visualize these complex, multidimensional data sets depends on a wide range of computer science and technology topics. Data storage and compression, data base management, computational methods and algorithms, artificial intelligence, telecommunications, and high-resolution display are just a few of the topics addressed. A unifying theme throughout the papers with regards to advanced data handling and visualization is the need for interactivity, speed, user-friendliness, and extensibility.

Szuszczewicz, E. P.↗