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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

Global Change Data Center: Mission, Organization, Major Activities, and 2001 Highlights

Rapid efficient access to Earth sciences data is fundamental to the Nation's efforts to understand the effects of global environmental changes and their implications for public policy. It becomes a bigger challenge in the future when data volumes increase further and missions with constellations of satellites start to appear. Demands on data storage, data access, network throughput, processing power, and database and information management are increased by orders of magnitude, while budgets remain constant and even shrink. The Global Change Data Center's (GCDC) mission is to provide systems, data products, and information management services to maximize the availability and utility of NASA's Earth science data. The specific objectives are (1) support Earth science missions be developing and operating systems to generate, archive, and distribute data products and information; (2) develop innovative information systems for processing, archiving, accessing, visualizing, and communicating Earth science data; and (3) develop value-added products and services to promote broader utilization of NASA Earth Sciences Enterprise (ESE) data and information. The ultimate product of GCDC activities is access to data and information to support research, education, and public policy.

Wharton, Stephen W.↗
NASA NTRS2004

Global Change Data Center: Mission, Organization, Major Activities, and 2003 Highlights

Rapid, efficient access to Earth sciences data from satellites and ground validation stations is fundamental to the nation's efforts to understand the effects of global environmental changes and their implications for public policy. It becomes a bigger challenge in the future when data volumes increase from current levels to terabytes per day. Demands on data storage, data access, network throughput, processing power, and database and information management are increased by orders of magnitude, while budgets remain constant and even shrink.The Global Change Data Center's (GCDC) mission is to develop and operate data systems, generate science products, and provide archival and distribution services for Earth science data in support of the U.S. Global Change Program and NASA's Earth Sciences Enterprise. The ultimate product of the GCDC activities is access to data to support research, education, and public policy.

FROM↗
NASA NTRS2012

NASA GSFC Space Weather Center - Innovative Space Weather Dissemination: Web-Interfaces, Mobile Applications, and More

The NASA GSFC Space Weather Center (http://swc.gsfc.nasa.gov) is committed to providing forecasts, alerts, research, and educational support to address NASA's space weather needs - in addition to the needs of the general space weather community. We provide a host of services including spacecraft anomaly resolution, historical impact analysis, real-time monitoring and forecasting, custom space weather alerts and products, weekly summaries and reports, and most recently - video casts. There are many challenges in providing accurate descriptions of past, present, and expected space weather events - and the Space Weather Center at NASA GSFC employs several innovative solutions to provide access to a comprehensive collection of both observational data, as well as space weather model/simulation data. We'll describe the challenges we've faced with managing hundreds of data streams, running models in real-time, data storage, and data dissemination. We'll also highlight several systems and tools that are utilized by the Space Weather Center in our daily operations, all of which are available to the general community as well. These systems and services include a web-based application called the Integrated Space Weather Analysis System (iSWA http://iswa.gsfc.nasa.gov), two mobile space weather applications for both IOS and Android devices, an external API for web-service style access to data, google earth compatible data products, and a downloadable client-based visualization tool.

Maddox, Marlo↗
NASA NTRS1998

Advanced Data Format (ADF) Software Library and Users Guide

The "CFD General Notation System" (CGNS) consists of a collection of conventions, and conforming software, for the storage and retrieval of Computational Fluid Dynamics (CFD) data. It facilitates the exchange of data between sites and applications, and helps stabilize the archiving of aerodynamic data. This effort was initiated in order to streamline the procedures in exchanging data and software between NASA and its customers, but the goal is to develop CGNS into a National Standard for the exchange of aerodynamic data. The CGNS development team is comprised of members from Boeing Commercial. Airplane Group, NASA-Ames, NASA-Langley, NASA-Lewis, McDonnell-Douglas Corporation (now Boeing-St. Louis), Air Force-Wright Lab., and ICEM-CFD Engineering. The elements of CGNS address all activities associated with the storage of data on external media and its movement to and from application programs. These elements include: 1) The Advanced Data Format (ADF) Database manager, consisting of both a file format specification and its 1/0 software, which handles the actual reading and writing of data from and to external storage media; 2) The Standard Interface Data Structures (SIDS), which specify the intellectual content of CFD data and the conventions governing naming and terminology; 3) The SIDS-to-ADF File Mapping conventions, which specify the exact location where the CFD data defined by the SIDS is to be stored within the ADF file(s); and 4) The CGNS Mid-level Library, which provides CFD-knowledgeable routines suitable for direct installation into application codes. The ADF is a generic database manager with minimal intrinsic capability. It was written for the purpose of storing large numerical datasets in an efficient, platform independent manner. To be effective, it must be used in conjunction with external agreements on how the data will be organized within the ADF database such defined by the SIDS. There are currently 34 user callable functions that comprise the ADF Core library and are described in the Users Guide. The library is written in C, but each function has a FORTRAN counterpart.

Smith, Matthew↗
NASA NTRS1990

Design and development of a space station hazardous material system for assessing chemical compatibility

As the Space Station nears reality in funding support from Congress, NASA plans to perform over a hundred different missions in the coming decade. Incrementally deployed, the Space Station will evolve into modules linked to an integral structure. Each module will have characteristic functions, such as logistics, habitation, and materials processing. Because the Space Station is to be user friendly for experimenters, NASA is anticipating that a variety of different chemicals will be taken on-board. Accidental release of these potentially toxic chemicals and their chemical compatibility is the focus of this discourse. The Microgravity Manufacturing Processing Facility (MMPF) will contain the various facilities within the U.S. Laboratory (USL). Each facility will have a characteristic purpose, such as alloy solidification or vapor crystal growth. By examining the proposed experiments for each facility, identifying the chemical constituents, their physical state and/or changes, byproducts and effluents, those payloads can be identified which may contain toxic, explosive, or reactive compounds that require processing or containment in mission peculiar waste management systems. Synergistic reactions from mixed effluent streams is of major concern. Each experiment will have it own data file, complete with schematic, chemical listing, physical data, etc. Chemical compatibility information from various databases will provide assistance in the analysis of alternate disposal techniques (pretreatment, separate storage, etc.). Along with data from the Risk Analysis of the Proposed USL Waste Management System, accidental release of potentially toxic and catastrophic chemicals would be eliminated or reduced.

Congo, Richard T.↗
NASA NTRS2004

Automated File Transfer and Storage Management Concepts for Space

This presentation will summarize work that has been done to prototype and analyze approaches for automated file transfer and storage management for space missions. The concepts were prototyped in an environment with data files being generated at the target mission rates and stored in onboard files. The space-to-ground link was implemented using a channel simulator to introduce representative mission delays and errors. The system was operated for days with data files building up on the spacecraft and periodically being transferred to ground storage during a limited contact time. Overall performance was measured to identify limits under which the entire data volume could be transferred automatically while still fitting into the mission s limited contact time. The overall concepts, measurements, and results will be presented.

Hogie, Keith↗
NASA NTRS2004

Data Management as a Cluster Middleware Centerpiece

Through earth and space modeling and the ongoing launches of satellites to gather data, NASA has become one of the largest producers of data in the world. These large data sets necessitated the creation of a Data Management System (DMS) to assist both the users and the administrators of the data. Halcyon Systems Inc. was contracted by the NASA Center for Computational Sciences (NCCS) to produce a Data Management System. The prototype of the DMS was produced by Halcyon Systems Inc. (Halcyon) for the Global Modeling and Assimilation Office (GMAO). The system, which was implemented and deployed within a relatively short period of time, has proven to be highly reliable and deployable. Following the prototype deployment, Halcyon was contacted by the NCCS to produce a production DMS version for their user community. The system is composed of several existing open source or government-sponsored components such as the San Diego Supercomputer Center s (SDSC) Storage Resource Broker (SRB), the Distributed Oceanographic Data System (DODS), and other components. Since Data Management is one of the foremost problems in cluster computing, the final package not only extends its capabilities as a Data Management System, but also to a cluster management system. This Cluster/Data Management System (CDMS) can be envisioned as the integration of existing packages.

Zero, Jose↗
NASA NTRS1993

Value added data archiving

Researchers in the Molecular Sciences Research Center (MSRC) of Pacific Northwest Laboratory (PNL) currently generate massive amounts of scientific data. The amount of data that will need to be managed by the turn of the century is expected to increase significantly. Automated tools that support the management, maintenance, and sharing of this data are minimal. Researchers typically manage their own data by physically moving datasets to and from long term storage devices and recording a dataset's historical information in a laboratory notebook. Even though it is not the most efficient use of resources, researchers have tolerated the process. The solution to this problem will evolve over the next three years in three phases. PNL plans to add sophistication to existing multilevel file system (MLFS) software by integrating it with an object database management system (ODBMS). The first phase in the evolution is currently underway. A prototype system of limited scale is being used to gather information that will feed into the next two phases. This paper describes the prototype system, identifies the successes and problems/complications experienced to date, and outlines PNL's long term goals and objectives in providing a permanent solution.

Berard, Peter R.↗
NASA NTRS1984

On-orbit cryogenic storage and resupply

Methods of integrating pressure control, liquid acquisition, and liquid transfer concepts for the Cryogenic Fluid Management Facility, a reusable test bed in the Shuttle cargo bay studying the efficient management of cryogens in space, are investigated. Significant design data and criteria for future subcritical cryogenic storage and transfer systems are presented. Technology requirements for liquid storage/supply systems, thermal control systems, and fluid transfer/resupply are addressed, and fluid and thermal analysis pertaining to receiver tank chilldown and no-vent fill of the receiver tank are discussed.

Eberhardt, R. N.↗
NASA NTRS2002

SIDS-toADF File Mapping Manual

The "CFD General Notation System" (CGNS) consists of a collection of conventions, and conforming software, for the storage and retrieval of Computational Fluid Dynamics (CFD) data. It facilitates the exchange of data between sites and applications, and helps stabilize the archiving of aerodynamic data. This effort was initiated in order to streamline the procedures in exchanging data and software between NASA and its customers, but the goal is to develop CGNS into a National Standard for the exchange of aerodynamic data. The CGNS development team is comprised of members from Boeing Commercial Airplane Group, NASA-Ames, NASA-Langley, NASA-Lewis, McDonnell-Douglas Corporation (now Boeing-St. Louis), Air Force-Wright Lab., and ICEM-CFD Engineering. The elements of CGNS address all activities associated with the storage of data on external media and its movement to and from application programs. These elements include: 1) The Advanced Data Format (ADF) Database manager, consisting of both a file format specification and its I/O software, which handles the actual reading and writing of data from and to external storage media; 2) The Standard Interface Data Structures (SIDS), which specify the intellectual content of CFD data and the conventions governing naming and terminology; 3) The SIDS-to-ADF File Mapping conventions, which specify the exact location where the CFD data defined by the SIDS is to be stored within the ADF file(s); and 4) The CGNS Mid-level Library, which provides CFD-knowledgeable routines suitable for direct installation into application codes. The SIDS-toADF File Mapping Manual specifies the exact manner in which, under CGNS conventions, CFD data structures (the SIDS) are to be stored in (i.e., mapped onto) the file structure provided by the database manager (ADF). The result is a conforming CGNS database. Adherence to the mapping conventions guarantees uniform meaning and location of CFD data within ADF files, and thereby allows the construction of universal software to read and write the data.

McCarthy, Douglas↗
NASA NTRSDate not supplied

Earth Independent Medical Operations (EIMO)

Inherent in interplanetary space travel are unprecedented challenges that could threaten mission success and negatively impact crew health and performance. Return to definitive care is essentially untenable and resources will be constrained with practically no re-supply capability. Access to ground-based medical expertise will be significantly delayed under nominal conditions with exacerbation during conjunction or prolonged dust storms. Taken together, these challenges necessitate the development of a progressively autonomous medical operational support system to assist the crew medical officer (CMO). While support from ground based medical experts will remain indispensable for pre-mission planning, the approach to management of acute/emergent medical contingencies will require a gradual transition of medical care and decision making from terrestrial to space-based assets, enabling support of astronaut health and performance and reducing overall mission risk. To progressively enable EIMO, a series of meetings were convened with subject matter experts from within NASA, academia and industry to facilitate mapping of the path to support autonomous medical operations. Topics explored in these meetings included the scope of data (storage capacity, usage, transmission rate and bandwidth, computing capacity), CMO training, supply and resource management and task load balance. Recommendations from these meetings will inform the EIMO Concept of Operations and definition of the associated requirements culminating in updates to the NASA 3001 standards. The EIMO project team will work with stakeholders to conceptualize a clinical decision support system (CDSS) to assist the CMO in response to medical contingencies when terrestrial support is delayed or otherwise unavailable. The CDSS will be a system of systems that will utilize data from numerous input vectors. Successful deployment of the CDSS will facilitate medical decision making while decreasing the cognitive load leading to an improvement in task load balancing. Additional benefits of the envisioned CDSS include assistance with inventory management, locating resources, storage/retrieval of medical records, highlighting trends in recorded data, in addition to providing a consult for diagnosis and treatment. More advanced features might include passive monitoring to identify early warning signs of behavioral or medical anomalies to possibly pre-empt onset of conditions that would compromise crew health and performance.

Benjamin Easter↗
NASA NTRS1985

Optical disks and superconductors

Supercomputers whose anticipated operational capability in the 1990s is of the order of 1 teraoperation/sec require a new generation of peripheral storage devices. The solution presented for this peripheral device problem encompasses hardware, data base software, and special expert systems to manage the operational environment of the supercomputer complex; attention, however, is given to the application of optical disk storage methods.

Wallgren, K. R.↗
NASA NTRS1991

Organizing and Typing Persistent Objects Within an Object-Oriented Framework

Conventional operating systems provide little or no direct support for the services required for an efficient persistent object system implementation. We have built a persistent object scheme using a customization and extension of an object-oriented operating system called Choices. Choices includes a framework for the storage of persistent data that is suited to the construction of both conventional file system and persistent object system. In this paper we describe three areas in which persistent object support differs from file system support: storage organization, storage management, and typing. Persistent object systems must support various sizes of objects efficiently. Customizable containers, which are themselves persistent objects and can be nested, support a wide range of object sizes in Choices. Collections of persistent objects that are accessed as an aggregate and collections of light-weight persistent objects can be clustered in containers that are nested within containers for larger objects. Automated garbage collection schemes are added to storage management and have a major impact on persistent object applications. The Choices persistent object store provides extensible sets of persistent object types. The store contains not only the data for persistent objects but also the names of the classes to which they belong and the code for the operation of the classes. Besides presenting persistent object storage organization, storage management, and typing, this paper discusses how persistent objects are named and used within the Choices persistent data/file system framework.

Madany, Peter W.↗
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↗
NASA NTRS2019

Designing the User Experience for Earth Observation Data Services in the Cloud

NASA's Earth Observation (EO) inventory is projected to grow by an order of magnitude over the next 5-6 years. The current mode for working with EO data of downloading the data to a local machine (laptop, desktop or server) will be difficult to sustain for these upcoming volumes. Therefore, NASA is in the process of developing a capability to host large volume data in commercial cloud, with an eye toward encouraging data analysis in the cloud. However, in order for the user community to take advantage of this new mode of data interaction, the user experience must be redesigned. Cloud-hosted data brings new challenges, such as managing the costs of data egress and working with data in Web Object Storage instead of a Posix filesystem. However, it also brings new opportunities. Scaling data transformation processes may permit more synchronous data services with near-immediate response vs. cumbersome ordering systems with latencies of hours or days. Data co-location in the cloud can facilitate data integration and fusion. Highly scalable filesystems and databases in the cloud support data reorganization to facilitate analysis at scale. In the course of NASA's reimagining of the User Experience for EO data usage relies on end user input gathered through surveys, workshops and meetings (such as this). At the same time, we have embarked on a course of pedagogy and capacity building to help the user community evolve to cloud-based analysis.

Lynnes, Christopher↗
NASA NTRS1998

CGNS Mid-Level Software Library and Users Guide

The "CFD General Notation System" (CGNS) consists of a collection of conventions, and conforming software, for the storage and retrieval of Computational Fluid Dynamics (CFD) data. It facilitates the exchange of data between sites and applications, and helps stabilize the archiving of aerodynamic data. This effort was initiated in order to streamline the procedures in exchanging data and software between NASA and its customers, but the goal is to develop CGNS into a National Standard for the exchange of aerodynamic data. The CGNS development team is comprised of members from Boeing Commercial Airplane Group, NASA-Ames, NASA-Langley, NASA-Lewis, McDonnell-Douglas Corporation (now Boeing-St. Louis), Air Force-Wright Lab., and ICEM-CFD Engineering. The elements of CGNS address all activities associated with the storage of data on external media and its movement to and from application programs. These elements include: - The Advanced Data Format (ADF) Database manager, consisting of both a file format specification and its I/O software, which handles the actual reading and writing of data from and to external storage media; - The Standard Interface Data Structures (SIDS), which specify the intellectual content of CFD data and the conventions governing naming and terminology; - The SIDS-to-ADF File Mapping conventions, which specify the exact location where the CFD data defined by the SIDS is to be stored within the ADF file(s); and - The CGNS Mid-level Library, which provides CFD-knowledgeable routines suitable for direct installation into application codes. The CGNS Mid-level Library was designed to ease the implementation of CGNS by providing developers with a collection of handy I/O functions. Since knowledge of the ADF core is not required to use this library, it will greatly facilitate the task of interfacing with CGNS. There are currently 48 user callable functions that comprise the Mid-level library and are described in the Users Guide. The library is written in C, but each function has a FORTRAN counterpart.

Poirier, Diane↗
NASA NTRS1994

New architectural paradigms for multi-petabyte distributed storage systems

In the not too distant future, programs such as NASA's Earth Observing System, NSF/ARPA/NASA's Digital Libraries Initiative and Intelligence Community's (NSA, CIA, NRO, etc.) mass storage system upgrades will all require multi-petabyte (petabyte: 1015 bytes of bitfile data) (or larger) distributed storage solutions. None of these requirements, as currently defined, will meet their objectives utilizing either today's architectural paradigms or storage solutions. Radically new approaches will be required to not only store and manage veritable 'mountain ranges of data', but to make the cost of ownership affordable, much less practical in today's (and certainly the future's) austere budget environment! Within this paper we will explore new architectural paradigms and project systems performance benefits and dollars per petabyte of information stored. We will discuss essential 'top down' approaches to achieving an overall systems level performance capability sufficient to meet the challenges of these major programs.

Lee, Richard R.↗
NASA NTRSDate not supplied

Py MILab: Capturing, Analyzing and Storing Test Data

Integrated Computational Materials Engineering (ICME) has recently received widespread attention due to its promises in reducing dependence on physical testing for engineering design by relying on simulation, reducing both time and cost to market for various applications. ICME however requires validated multiscale material models, which is heavily dependent on available test data with full material and test pedigree, including material processing, test and measurement equipment, raw data collection, and analysis methodology and results. Populating searchable information management systems with such rich data sets is often burdensome for data producers, resulting in a lack of findable data for modelers to validate and verify their models. To overcome these cultural barriers to ICME, NASA has developed of various database-integration toolsets that perform both data management activities within the organization’s best practices with additional functionality that relieves the effort of the data producer and promotes adoption of information management system. One such tool currently under development is Py MILab, an automatic framework for automatic capturing, analysis, maintenance, and storage of material test data. Py MILab uses a modular approach for capturing raw data, analyzing the data, and storing the data in a database, interfaced by neutral file structures, to promote plug-and-play capabilities for various analysis types. TMAnalysis is a Python-based tool that performs automatic data reduction and analysis of uniaxial thermomechanical test data. The TMAnalysis toolset can be implemented within the Analysis module of Py MILab, and thus requires a populated neutral file form the Raw Data Module of Py MILab and outputs a Analysis neutral file compatible with the Database Module of Py MILab. TMAnalysis is able to perform automatic segmentation of multistage tests and perform data analysis and reduction, including determination of point-wise properties in tension, compression, and shear, analysis of stress relaxation tests, creep analysis and zone identification, and combination of these stage types for tests with complex loading histories. The TMAnalysis code is accompanied with a graphical user interface (GUI) that allows users to easily analyze test data in bulk, verify the automatic, consistent analysis performed by the backend code, and edit stage segmentation if necessary before producing the output neutral files, ensuring data is properly analyzed and maintained with full traceability.

Data management↗