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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 NTRS2000

NASA Goddard Space Flight Center

The NASA SLR Operational Center is responsible for: 1) NASA SLR network control, sustaining engineering, and logistics; 2) ILRS mission operations; and 3) ILRS and NASA SLR data operations. NASA SLR network control and sustaining engineering tasks include technical support, daily system performance monitoring, system scheduling, operator training, station status reporting, system relocation, logistics and support of the ILRS Networks and Engineering Working Group. These activities ensure the NASA SLR systems are meeting ILRS and NASA mission support requirements. ILRS mission operations tasks include mission planning, mission analysis, mission coordination, development of mission support plans, and support of the ILRS Missions Working Group. These activities ensure than new mission and campaign requirements are coordinated with the ILRS. Global Normal Points (NP) data, NASA SLR FullRate (FR) data, and satellite predictions are managed as part of data operations. Part of this operation includes supporting the ILRS Data Formats and Procedures Working Group. Global NP data operations consist of receipt, format and data integrity verification, archiving and merging. This activity culminates in the daily electronic transmission of NP files to the CDDIS. Currently of all these functions are automated. However, to ensure the timely and accurate flow of data, regular monitoring and maintenance of the operational software systems, computer systems and computer networking are performed. Tracking statistics between the stations and the data centers are compared periodically to eliminate lost data. Future activities in this area include sub-daily (i.e., hourly) NP data management, more stringent data integrity tests, and automatic station notification of format and data integrity issues.

Carter, David↗
NASA NTRS1994

NASA Johnson Space Center Life Sciences Data System

The Life Sciences Project Division (LSPD) at JSC, which manages human life sciences flight experiments for the NASA Life Sciences Division, augmented its Life Sciences Data System (LSDS) in support of the Spacelab Life Sciences-2 (SLS-2) mission, October 1993. The LSDS is a portable ground system supporting Shuttle, Spacelab, and Mir based life sciences experiments. The LSDS supports acquisition, processing, display, and storage of real-time experiment telemetry in a workstation environment. The system may acquire digital or analog data, storing the data in experiment packet format. Data packets from any acquisition source are archived and meta-parameters are derived through the application of mathematical and logical operators. Parameters may be displayed in text and/or graphical form, or output to analog devices. Experiment data packets may be retransmitted through the network interface and database applications may be developed to support virtually any data packet format. The user interface provides menu- and icon-driven program control and the LSDS system can be integrated with other workstations to perform a variety of functions. The generic capabilities, adaptability, and ease of use make the LSDS a cost-effective solution to many experiment data processing requirements. The same system is used for experiment systems functional and integration tests, flight crew training sessions and mission simulations. In addition, the system has provided the infrastructure for the development of the JSC Life Sciences Data Archive System scheduled for completion in December 1994.

Rahman, Hasan↗
NASA NTRS1984

The Design and Usage of the New Data Management Features in NASTRAN

Two new data management features are installed in the April 1984 release of NASTRAN. These two features are the Rigid Format Data Base and the READFILE capability. The Rigid Format Data Base is stored on external files in card image format and can be easily maintained and expanded by the use of standard text editors. This data base provides the user and the NASTRAN maintenance contractor with an easy means for making changes to a Rigid Format or for generating new Rigid Formats without unnecessary compilations and link editing of NASTRAN. Each Rigid Format entry in the data base contains the Direct Matrix Abstraction Program (DMAP), along with the associated restart, DMAP sequence subset and substructure control flags. The READFILE capability allows an user to reference an external secondary file from the NASTRAN primary input file and to read data from this secondary file. There is no limit to the number of external secondary files that may be referenced and read.

Pamidi, P. R.↗
NASA NTRS2009

American Meteorological Society (AMS) - The Modern Era Retrospective-Analysis for Research and Applications (MERRA) Data and Accessibility

The AM Short Course on The Modern Era Retrospective-analysis for Research and Applications (MERRA) data and accessibility will be held on January 11, 2009 preceding the 89th Annual Meeting in Phoenix, Arizona. Preliminary programs, registration, hotel, and general information will be posted on the AMS Web site in mid-September 2008. Retrospective-analyses (or reanalyses) have been established as an important tool in weather and climate research over the last decade. As computer power increases, the data assimilation and modeling systems improve and become more advanced, the input data quality increases and so reanalyses become more reliable. In 2008, NASA Global Modeling and Assimilation Office began producing a new reanalysis called the Modem Era Retrospective-analysis for Research and Applications (MERRA). The initial data from the reanalysis has been made available to the community and should be complete through 30 years (1979-present) by Fall of 2009. MERRA has taken advantage of the advancement of computing resources to provide users more data than previously available. The native spatial resolution is nominally 1/2 degrees and the surface two dimensional data are one hourly frequency. In addition to the meteorological analysis data, complete mass, energy and momentum budget data and also stratospheric data are provided. The eventual data holdings will exceed 150Tb. In order to facilitate user accessibility to the data, it will be stored in online hard drives (not tape storage) and available through several portals. Subsetting tools will also be available to allow users to tailor their data requests. The goals of this short course are to provide hands on users of reanalyses instruction on MERRA systems and also interactive experience with the online data and access tools. The course is intended for students and research scientists who will be actively interested in accessing and applying MERRA data in their weather, climate or applications work. The course has three parts. There will be an overview of the MERRA system, the validation of the system and the native data format. Second, Instructors will provide examples of weather and climate data analysis using various software packages (primarily GrADS) as well as the online access tools for subsetting and download, as well as visualization (e.g. Giovanni and Google Earth). This will also include examples on changing the data format to fit user's preferences and also to regrid the data for comparisons to other reanalyses and observational data. Lastly, there will he time set aside for participants to have hands on access to the data and software while interacting with the instructors and other developers. The course convener is Dr. Michael Bosilovich, NASA GSFC Global Modeling and Assimilation Office (GMAO). He will be joined by several GMAO, Goddard Earth Science Data and information Services Center (GES DISC) and Software Integration and Visualization Office (SIVO) staff.

daSilva, Arlindo↗
NASA NTRS2005

Development and operations of the astrophysics data system

Abstract service - Continued regular updates of abstracts in the databases, both at SA0 and at all mirror sites. - Modified loading scripts to accommodate changes in data format (PhyS) - Discussed data deliveries with providers to clear up problems with format or other errors (EGU) - Continued inclusion of large numbers of historical literature volumes and physics conference volumes xeroxed from the library. - Performed systematic fixes on some data sets in the database to account for changes in article numbering (AGU journals) - Implemented linking of ADS bibliographic records with multimedia files - Debugged and fixed obscure connection problems with the ADS Korean mirror site which were preventing successful updates of the data holdings. - Wrote procedure to parse citation data and characterize an ADS record based on its citation ratios within each database.

Murray, Stephen S.↗
NASA NTRS1985

Data presentation techniques for rotating machinery malfunction diagnosis

Baseline steady state data is excellent for documentation of vibration signals at normal operating conditions. Assuming that a set of initial data was acquired with the machinery in a good state of repair, any future changes or deterioration in mechanical condition can be easily compared to the baseline information. Often this type of comparison will yield sufficient information for evaluation of the problem. However, many malfunctions require the analysis of transient data in order to identify the malfunction. Steady-state data formats consist of: Time Base Waveform, Orbit, Spectrum. Transient data formats consist of: Polar, Bode, Cascade. Our objective is to demonstrate the use of the above formats to diagnose a machine malfunction. A turbine-driven compressor train is chosen as an example. The machine train outline drawing is shown.

Spettel, T.↗
NASA NTRS1992

FITS data conversion efforts at the Compton Observatory Science Support Center

The Compton Gamma Ray Observatory (CGRO) is an active, earth orbiting satellite consisting of four gamma-ray telescopes. Each telescope is maintained by an independent principal investigator (PI) team, and each PI team has devised separate data formats to handle the needs of their particular instrument. As mandated by NASA, the Compton Observatory Science Support Center (COSSC) intends to archive and distribute PI data to the public in FITS (Flexible Image Transport System) format. To accomplish this task, we at COSSC have been developing a set of general purpose software tools that facilitate the transformation of non-FITS formatted data into FITS format. These tools, known as ToFU (To FITS Utilities), serve as the kernel of our CGRO data conversion software. This presentation describes the problems encountered in transcribing large amounts of data into a standard FITS form and the capabilities of the COSSC-built conversion software designed to perform the transformations.

Jennings, D. G.↗
NASA NTRS2017

Climate Data Guide - Modern Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2)

The Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2) is a global atmospheric reanalysis produced by the NASA Global Modeling and Assimilation Office (GMAO). It spans the satellite observing era from 1980 to the present. The goals of MERRA-2 are to provide a regularly-gridded, homogeneous record of the global atmosphere, and to incorporate additional aspects of the climate system including trace gas constituents (stratospheric ozone), and improved land surface representation, and cryospheric processes. MERRA-2 is also the first satellite-era global reanalysis to assimilate space-based observations of aerosols and represent their interactions with other physical processes in the climate system. The inclusion of these additional components are consistent with the overall objectives of an Integrated Earth System Analysis (IESA). MERRA-2 is intended to replace the original MERRA product, and reflects recent advances in atmospheric modeling and data assimilation. Modern hyperspectral radiance and microwave observations, along with GPS-Radio Occultation and NASA ozone datasets are now assimilated in MERRA-2. Much of the structure of the data files remains the same in MERRA-2. While the original MERRA data format was HDF-EOS, the MERRA-2 supplied binary data format is now NetCDF4 (with lossy compression to save space).

MERRA-2↗
NASA NTRS2016

Advancing User Supports with a Structured How-To Knowledge Base for Earth Science Data

It is a challenge to access and process fast growing Earth science data from satellites and numerical models, which may be archived in very different data format and structures. NASA data centers, managed by the Earth Observing System Data and Information System (EOSDIS), have developed a rich and diverse set of data services and tools with features intended to simplify finding, downloading, and working with these data. Although most data services and tools have user guides, many users still experience difficulties with accessing or reading data due to varying levels of familiarity with data services, tools, and/or formats. A type of structured online document, data recipe, were created in beginning 2013 by Goddard Earth Science Data and Information Services Center (GES DISC). A data recipe is the How-To document created by using the fixed template, containing step-by-step instructions with screenshots and examples of accessing and working with real data. The recipes has been found to be very helpful, especially to first-time-users of particular data services, tools, or data products. Online traffic to the data recipe pages is significant to some recipes. In 2014, the NASA Earth Science Data System Working Group (ESDSWG) for data recipes was established, aimed to initiate an EOSDIS-wide campaign for leveraging the distributed knowledge within EOSDIS and its user communities regarding their respective services and tools. The ESDSWG data recipe group started with inventory and analysis of existing EOSDIS-wide online help documents, and provided recommendations and guidelines and for writing and grouping data recipes. This presentation will overview activities of creating How-To documents at GES DISC and ESDSWG. We encourage feedback and contribution from users for improving the data How-To knowledge base.

how-to↗
NASA NTRS2005

NASA GES DISC DAAC Satellite Data for GIS

NASA's Goddard Earth Science (GES) Data and Information Services Center (DISC) Distributed Active Archive Center (DAAC) makes available a large and continually growing collection of spatially continuous global satellite observations of environmental parameters. These products include those from the MODIS (Moderate Resolution Imaging Spectroradiometer) on both Terra and Aqua platforms, and the Tropical Rainfall Measuring Mission (TRMM). These data products are well suited for use within Geographic Information Systems (GIS), as both backdrops to cartographic products as well as spatial analysis. However, data format, file size, and other issues have limited their widespread use by traditional GIS users. To address these data usability issues, the GES DISC DAAC recently updated tools and improved documentation of conversion procedures. In addition, the GES DISC DAAC has also been working with a major GIS software vendor to incorporate the ability to read the native Hierarchial Data Format (HDF), the format in which most of the NASA data is stored. The result is the enabling of GIS users to realize the benefit of GES DISC DAAC data without a substantial expenditure in resources to incorporate these data into their GIS. Several documents regarding the potential uses of GES DISC DAAC satellite data in GIS have recently been created. These show the combinations of concurrent data from different satellite products with traditional GIS vector products for given geographic areas. These map products include satellite imagery of Hurricane Isabel and the California wildfires, and can be viewed at http://daac.gsfc.nasa.gov/MODIS/GIS/.

Nickless, Darryl↗
NASA NTRS1983

Compiling the space shuttle wind tunnel data base: An exercise in technical and managerial innovators

Engineers evaluating Space Shuttle flight data and performance results are using a massive data base of wind tunnel test data. A wind tunnel test data base of the magnitude attained is a major accomplishment. The Apollo program spawned an automated wind tunnel data analysis system called SADSAC developed by the Chrysler Space Division. An improved version of this system renamed DATAMAN was used by Chrysler to document analyzed wind tunnel data and data bank the test data in standardized formats. These analysis documents, associated computer graphics and standard formatted data were disseminated nationwide to the Shuttle technical community. These outputs became the basis for substantiating and certifying the flight worthiness of the Space Shuttle and for improving future designs. As an aid to future programs this paper documents the lessons learned in compiling the massive wind tunnel test data base for developing the Space Shuttle. In particular, innovative managerial and technical concepts evolved in the course of conceiving and developing this successful DATAMAN system and the methods and organization for applying the system are presented.

Kemp, N. D.↗
NASA NTRS1999

User's Guide for Monthly Vector Wind Profile Model

The background, theoretical concepts, and methodology for construction of vector wind profiles based on a statistical model are presented. The derived monthly vector wind profiles are to be applied by the launch vehicle design community for establishing realistic estimates of critical vehicle design parameter dispersions related to wind profile dispersions. During initial studies a number of months are used to establish the model profiles that produce the largest monthly dispersions of ascent vehicle aerodynamic load indicators. The largest monthly dispersions for wind, which occur during the winter high-wind months, are used for establishing the design reference dispersions for the aerodynamic load indicators. This document includes a description of the computational process for the vector wind model including specification of input data, parameter settings, and output data formats. Sample output data listings are provided to aid the user in the verification of test output.

Adelfang, S. I.↗
NASA NTRS2002

Implementation of CCSDS Lossless Data Compression in HDF

The Earth Science Data and Information System (ESDIS) handles over one terabyte (10(exp 12) bytes) of data daily and is using the Hierarchical Data Format (EDF) for data archiving and distribution. This report provides the progress and status of our effort to alleviate bandwidth and storage burdens by first performing compression studies on various science data products and later integrating the selected compression scheme into HDF.

Pen-Shu Yeh↗
NASA NTRS2004

Space Communications Emulation Facility

Establishing space communication between ground facilities and other satellites is a painstaking task that requires many precise calculations dealing with relay time, atmospheric conditions, and satellite positions, to name a few. The Space Communications Emulation Facility (SCEF) team here at NASA is developing a facility that will approximately emulate the conditions in space that impact space communication. The emulation facility is comprised of a 32 node distributed cluster of computers; each node representing a satellite or ground station. The objective of the satellites is to observe the topography of the Earth (water, vegetation, land, and ice) and relay this information back to the ground stations. Software originally designed by the University of Kansas, labeled the Emulation Manager, controls the interaction of the satellites and ground stations, as well as handling the recording of data. The Emulation Manager is installed on a Linux Operating System, employing both Java and C++ programming codes. The emulation scenarios are written in extensible Markup Language, XML. XML documents are designed to store, carry, and exchange data. With XML documents data can be exchanged between incompatible systems, which makes it ideal for this project because Linux, MAC and Windows Operating Systems are all used. Unfortunately, XML documents cannot display data like HTML documents. Therefore, the SCEF team uses XML Schema Definition (XSD) or just schema to describe the structure of an XML document. Schemas are very important because they have the capability to validate the correctness of data, define restrictions on data, define data formats, and convert data between different data types, among other things. At this time, in order for the Emulation Manager to open and run an XML emulation scenario file, the user must first establish a link between the schema file and the directory under which the XML scenario files are saved. This procedure takes place on the command line on the Linux Operating System. Once this link has been established the Emulation manager validates all the XML files in that directory against the schema file, before the actual scenario is run. Using some very sophisticated commercial software called the Satellite Tool Kit (STK) installed on the Linux box, the Emulation Manager is able to display the data and graphics generated by the execution of a XML emulation scenario file. The Emulation Manager software is written in JAVA programming code. Since the SCEF project is in the developmental stage, the source code for this type of software is being modified to better fit the requirements of the SCEF project. Some parameters for the emulation are hard coded, set at fixed values. Members of the SCEF team are altering the code to allow the user to choose the values of these hard coded parameters by inserting a toolbar onto the preexisting GUI.

Hill, Chante A.↗
NASA NTRS2008

Visual Data Analysis for Satellites

The Visual Data Analysis Package is a collection of programs and scripts that facilitate visual analysis of data available from NASA and NOAA satellites, as well as dropsonde, buoy, and conventional in-situ observations. The package features utilities for data extraction, data quality control, statistical analysis, and data visualization. The Hierarchical Data Format (HDF) satellite data extraction routines from NASA's Jet Propulsion Laboratory were customized for specific spatial coverage and file input/output. Statistical analysis includes the calculation of the relative error, the absolute error, and the root mean square error. Other capabilities include curve fitting through the data points to fill in missing data points between satellite passes or where clouds obscure satellite data. For data visualization, the software provides customizable Generic Mapping Tool (GMT) scripts to generate difference maps, scatter plots, line plots, vector plots, histograms, timeseries, and color fill images.

Lau, Yee↗
NASA NTRS2010

Terrestrial Hydrological Data from NASA's Hydrology Data and Information Services Center (HDISC): Products, Services, and Applications

Terrestrial hydrological variables are important in global hydrology, climate, and carbon cycle studies. The North American and Global Land Data Assimilation Systems (NLDAS and GLDAS, respectively) have been generating a series of land surface states (soil moisture, snow, and temperature) and fluxes (evapotranspiration, radiation, and heat flux) variables. These data, hosted at and available from NASA s Hydrology Data and Information Services Center (HDISC), include the NLDAS hourly 1/8 degree products and the GLDAS 3-hourly 0.25 and 1.0 degree products. HDISC provides easy access and visualization and analysis capabilities for these products, thus reducing the time and resources spent by scientists on data management and facilitating hydrological research. Users can perform spatial and parameter subsetting, data format transformation, and data analysis operations without needing to first download the data. HDISC is continually being developed as a data and services portal that supports weather and climate forecasts, and water and energy cycle research.

Fang, Hongliang↗
NASA NTRS2004

Fast-Acquisition/Weak-Signal-Tracking GPS Receiver for HEO

A report discusses the technical background and design of the Navigator Global Positioning System (GPS) receiver -- . a radiation-hardened receiver intended for use aboard spacecraft. Navigator is capable of weak signal acquisition and tracking as well as much faster acquisition of strong or weak signals with no a priori knowledge or external aiding. Weak-signal acquisition and tracking enables GPS use in high Earth orbits (HEO), and fast acquisition allows for the receiver to remain without power until needed in any orbit. Signal acquisition and signal tracking are, respectively, the processes of finding and demodulating a signal. Acquisition is the more computationally difficult process. Previous GPS receivers employ the method of sequentially searching the two-dimensional signal parameter space (code phase and Doppler). Navigator exploits properties of the Fourier transform in a massively parallel search for the GPS signal. This method results in far faster acquisition times [in the lab, 12 GPS satellites have been acquired with no a priori knowledge in a Low-Earth-Orbit (LEO) scenario in less than one second]. Modeling has shown that Navigator will be capable of acquiring signals down to 25 dB-Hz, appropriate for HEO missions. Navigator is built using the radiation-hardened ColdFire microprocessor and housing the most computationally intense functions in dedicated field-programmable gate arrays. The high performance of the algorithm and of the receiver as a whole are made possible by optimizing computational efficiency and carefully weighing tradeoffs among the sampling rate, data format, and data-path bit width.

Wintemitz, Luke↗