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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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
NASA NTRS1989

GPS-based system for satellite tracking and geodesy

High-performance receivers and data processing systems developed for GPS are reviewed. The GPS Inferred Positioning System (GIPSY) and the Orbiter Analysis and Simulation Software (OASIS) are described. The OASIS software is used to assess GPS system performance using GIPSY for data processing. Consideration is given to parameter estimation for multiday arcs, orbit repeatability, orbit prediction, daily baseline repeatability, agreement with VLBI, and ambiguity resolution. Also, the dual-frequency Rogue receiver, which can track up to eight GPS satellites simultaneously, is discussed.

Bertiger, Willy I.↗
NASA NTRS1988

NASA follow-on on the Fiji South Pacific Severe Storm Warning System Project (SPSSD/WS)

The follow-on agreement will implement needed systems enhancements of the satellite ground station installed under the previous SPSSD/WS project. These enhancements include the purchase and installation of an Uninterruptible Power Supply (UPS) and lightning protection unit, hardware modifications to provide system redundancy and increased data storage capacity, software modifications for the new Japanese GMS digital data, upgrades of the image processing software, and both hardware maintenance and tropical cyclone analysis training, and a non-renewable grant to provide emergency field repairs and replacement/spare parts. In March 1988, the UPS and lightning protection unit was installed at the Fiji Meteorological Service by NASA personnel. A tape recorder and demodulator was shipped to Fiji to record the new digital GMS data. Data tapes are not yet available from the Japanese Meteorological Service of the new digital format. This data is required to test the GMS digital software being developed for the Fiji SPSSD/WS facility.

Vermillion, C.↗
NASA NTRS2021

T0TEM - T0 Test Evaluation Module Development and Verification

Transition temperature testing of ferritic steels evaluates the ductile to brittle transition temperature, where the behavior of the steel changes from controlled ductile tearing to uncontrollable brittle fracture. This testing is governed by ASTM (American Society of Testing and Materials) E1921 standard. The calculations and plots required by this standard are iterative in nature and require significant effort to produce by standard hand calculations. In addition to analysis of a complete data set, intermediate analysis during testing is beneficial to determine optimal test temperatures. Given the exhaustive nature of calculating the transition temperature, being able to quickly update target temperatures is a significant benefit to not only the quality of tests, but the number of required tests as well. T0 Test Evaluation Module (T0TEM) v1.5 is a software application created under the Layered Pressure Vessel (LPV) certification effort. To reduce the analysis time of transition temperature test data sets producedfor this effort, T0TEM was created to calculate the E1921 Master Curve along with all required data and validity checks. By creating this program, hundreds of hours of analysis time were saved. In addition, the creation of a standard program provided a significant improvement in the consistency with which results were reported. T0TEM also calculates the results and plots required for the E1921 inhomogeneity annex to determine whether a material behaves in a homogenous manner. This program was created by Levi Shelton and Cameron Bosley at NASA, with input and review from the E1921 committee. The results generated by T0TEM were compared to the validation data sets provided by ASTM with good concurrence. ASTM committee members have reviewed and applied T0TEM to other data sets with satisfactory results. T0TEM was originally released to the NASA Software Repository and publicly via SourceForge in May of 2020. Version 1.5 was released in April of 2021 with minor functionality updates and additional statistical analysis methods.

Levi Shelton↗
NASA NTRS2012

Automated Performance Characterization of DSN System Frequency Stability Using Spacecraft Tracking Data

This software provides an automated capability to measure and qualify the frequency stability performance of the Deep Space Network (DSN) ground system, using daily spacecraft tracking data. The results help to verify if the DSN performance is meeting its specification, therefore ensuring commitments to flight missions; in particular, the radio science investigations. The rich set of data also helps the DSN Operations and Maintenance team to identify the trends and patterns, allowing them to identify the antennas of lower performance and implement corrective action in a timely manner. Unlike the traditional approach where the performance can only be obtained from special calibration sessions that are both time-consuming and require manual setup, the new method taps into the daily spacecraft tracking data. This new approach significantly increases the amount of data available for analysis, roughly by two orders of magnitude, making it possible to conduct trend analysis with good confidence. The software is built with automation in mind for end-to-end processing. From the inputs gathering to computation analysis and later data visualization of the results, all steps are done automatically, making the data production at near zero cost. This allows the limited engineering resource to focus on high-level assessment and to follow up with the exceptions/deviations. To make it possible to process the continual stream of daily incoming data without much effort, and to understand the results quickly, the processing needs to be automated and the data summarized at a high level. Special attention needs to be given to data gathering, input validation, handling anomalous conditions, computation, and presenting the results in a visual form that makes it easy to spot items of exception/ deviation so that further analysis can be directed and corrective actions followed.

Pham, Timothy T.↗
NASA NTRS2012

Automated Performance Characterization of DSN System Frequency Stability Using Spacecraft Tracking Data

This software provides an automated capability to measure and qualify the frequency stability performance of the Deep Space Network (DSN) ground system, using daily spacecraft tracking data. The results help to verify if the DSN performance is meeting its specification, therefore ensuring commitments to flight missions; in particular, the radio science investigations. The rich set of data also helps the DSN Operations and Maintenance team to identify the trends and patterns, allowing them to identify the antennas of lower performance and implement corrective action in a timely manner. Unlike the traditional approach where the performance can only be obtained from special calibration sessions that are both time-consuming and require manual setup, the new method taps into the daily spacecraft tracking data. This new approach significantly increases the amount of data available for analysis, roughly by two orders of magnitude, making it possible to conduct trend analysis with good confidence. The software is built with automation in mind for end-to-end processing. From the inputs gathering to computation analysis and later data visualization of the results, all steps are done automatically, making the data production at near zero cost. This allows the limited engineering resource to focus on high-level assessment and to follow up with the exceptions/deviations. To make it possible to process the continual stream of daily incoming data without much effort, and to understand the results quickly, the processing needs to be automated and the data summarized at a high level. Special attention needs to be given to data gathering, input validation, handling anomalous conditions, computation, and presenting the results in a visual form that makes it easy to spot items of exception/deviation so that further analysis can be directed and corrective actions followed.

Pham, Timothy T.↗
NASA NTRS1997

Sulfur in Cometary Dust

The computer-intensive project consisted of the analysis and synthesis of existing data on composition of comet Halley dust particles. The main objective was to obtain a complete inventory of sulfur containing compounds in the comet Halley dust by building upon the existing classification of organic and inorganic compounds and applying a variety of statistical techniques for cluster and cross-correlational analyses. A student hired for this project wrote and tested the software to perform cluster analysis. The following tasks were carried out: (1) selecting the data from existing database for the proposed project; (2) finding access to a standard library of statistical routines for cluster analysis; (3) reformatting the data as necessary for input into the library routines; (4) performing cluster analysis and constructing hierarchical cluster trees using three methods to define the proximity of clusters; (5) presenting the output results in different formats to facilitate the interpretation of the obtained cluster trees; (6) selecting groups of data points common for all three trees as stable clusters. We have also considered the chemistry of sulfur in inorganic compounds.

Fomenkova, M. N.↗
NASA NTRS2011

Draper Station Analysis Tool

Draper Station Analysis Tool (DSAT) is a computer program, built on commercially available software, for simulating and analyzing complex dynamic systems. Heretofore used in designing and verifying guidance, navigation, and control systems of the International Space Station, DSAT has a modular architecture that lends itself to modification for application to spacecraft or terrestrial systems. DSAT consists of user-interface, data-structures, simulation-generation, analysis, plotting, documentation, and help components. DSAT automates the construction of simulations and the process of analysis. DSAT provides a graphical user interface (GUI), plus a Web-enabled interface, similar to the GUI, that enables a remotely located user to gain access to the full capabilities of DSAT via the Internet and Webbrowser software. Data structures are used to define the GUI, the Web-enabled interface, simulations, and analyses. Three data structures define the type of analysis to be performed: closed-loop simulation, frequency response, and/or stability margins. DSAT can be executed on almost any workstation, desktop, or laptop computer. DSAT provides better than an order of magnitude improvement in cost, schedule, and risk assessment for simulation based design and verification of complex dynamic systems.

Bedrossian, Nazareth↗
NASA NTRS1981

The GEMPAK Barnes objective analysis scheme

GEMPAK, an interactive computer software system developed for the purpose of assimilating, analyzing, and displaying various conventional and satellite meteorological data types is discussed. The objective map analysis scheme possesses certain characteristics that allowed it to be adapted to meet the analysis needs GEMPAK. Those characteristics and the specific adaptation of the scheme to GEMPAK are described. A step-by-step guide for using the GEMPAK Barnes scheme on an interactive computer (in real time) to analyze various types of meteorological datasets is also presented.

Koch, S. E.↗
NASA NTRS2006

DORIS Satellite Phase Center Determination and Consequences on the Derived Scale of the Terrestrial Reference Frame

This slide presentation reports on the analysis of several years of Delft Object-oriented Radar Interferometric Software (Doris) data undertaken to estimate daily determination of satellite antenna phase center corrections. This was done on a satellite by satellite basis. For each DORIS satellite, we considered long-term time series of such individual estimations, looking for possible biases, discontinuities, trends or annual signals. The analysis compared DORIS to GPS estimates for common satellites (Jason and TOPEX/Poseidon).

terrestrial reference frame scale↗
NASA NTRS2004

Engineering Complex Embedded Systems with State Analysis and the Mission Data System

It has become clear that spacecraft system complexity is reaching a threshold where customary methods of control are no longer affordable or sufficiently reliable. At the heart of this problem are the conventional approaches to systems and software engineering based on subsystem-level functional decomposition, which fail to scale in the tangled web of interactions typically encountered in complex spacecraft designs. Furthermore, there is a fundamental gap between the requirements on software specified by systems engineers and the implementation of these requirements by software engineers. Software engineers must perform the translation of requirements into software code, hoping to accurately capture the systems engineer's understanding of the system behavior, which is not always explicitly specified. This gap opens up the possibility for misinterpretation of the systems engineer s intent, potentially leading to software errors. This problem is addressed by a systems engineering methodology called State Analysis, which provides a process for capturing system and software requirements in the form of explicit models. This paper describes how requirements for complex aerospace systems can be developed using State Analysis and how these requirements inform the design of the system software, using representative spacecraft examples.

mission data systems↗
NASA NTRS1989

The software product assurance metrics study: JPL's software systems quality and productivity

The findings are reported of the Jet Propulsion Laboratory (JPL)/Software Product Assurance (SPA) Metrics Study, conducted as part of a larger JPL effort to improve software quality and productivity. Until recently, no comprehensive data had been assembled on how JPL manages and develops software-intensive systems. The first objective was to collect data on software development from as many projects and for as many years as possible. Results from five projects are discussed. These results reflect 15 years of JPL software development, representing over 100 data points (systems and subsystems), over a third of a billion dollars, over four million lines of code and 28,000 person months. Analysis of this data provides a benchmark for gauging the effectiveness of past, present and future software development work. In addition, the study is meant to encourage projects to record existing metrics data and to gather future data. The SPA long term goal is to integrate the collection of historical data and ongoing project data with future project estimations.

Bush, Marilyn W.↗
NASA NTRS1983

Supporting flight data analysis for Space Shuttle Orbiter Experiments at NASA Ames Research Center

The Space Shuttle Orbiter Experiments program in responsible for collecting flight data to extend the research and technology base for future aerospace vehicle design. The Infrared Imagery of Shuttle (IRIS), Catalytic Surface Effects, and Tile Gap Heating experiments sponsored by Ames Research Center are part of this program. The paper describes the software required to process the flight data which support these experiments. In addition, data analysis techniques, developed in support of the IRIS experiment, are discussed. Using the flight data base, the techniques have provided information useful in analyzing and correcting problems with the experiment, and in interpreting the IRIS image obtained during the entry of the third Shuttle mission.

Green, M. J.↗
NASA NTRS1997

GOME wavelength calibration using solar and atmospheric spectra

Spectral information in the global ozone monitoring experiment (GOME) solar irradiance spectra and GOME earth radiance spectra are used in conjunction with the GOME solar reference spectrum to provide absolute vacuum internal wavelength calibration for GOME. Two methods for wavelength calibration of GOME data are investigated. The first employs chi-square minimization of a merit function involving wavelength and the GOME slit function. It is quite robust and requires little GOME data in the processing (calibration window regions from 15 to 40 pixels). The second employs cross correlation of GOME data and the solar reference spectrum in the Fourier transform domain, using a procedure in the image reduction and analysis facility (IRAF) software system developed for the determination of galaxy redshifts. It also requires small amounts of GOME data (calibration window regions with from 10 to 15 pixels). Both methods provide absolute wavelength calibration accurate to a small fraction of a GOME pixel across the entire GOME spectrum, and to 0.001 nm over much of the range.

Caspar, C.↗
NASA NTRS2023

System for Photogrammetry, Imaging, Detection, and Ranging, Software Design

Kennedy Space Center (KSC) uses high level pan/tilt camera systems in order to capture data for image analysis. As of right now, we know that current camera systems need to be man-operated, range greatly in costs, and are supplied by third parties. This project, System for Photogrammetric Imaging, Detection, and Ranging, otherwise known as SPIDR, aims to provide high quality image analysis from data drawn from the pan/tilt camera system to upgrade KSC’s ability to take images, and improve space flight and tracking. What this abstract will do, is explain the software needed to carry out such important tasks.

R.S. Kim↗
NASA NTRS2008

Algorithm Optimally Orders Forward-Chaining Inference Rules

People typically develop knowledge bases in a somewhat ad hoc manner by incrementally adding rules with no specific organization. This often results in a very inefficient execution of those rules since they are so often order sensitive. This is relevant to tasks like Deep Space Network in that it allows the knowledge base to be incrementally developed and have it automatically ordered for efficiency. Although data flow analysis was first developed for use in compilers for producing optimal code sequences, its usefulness is now recognized in many software systems including knowledge-based systems. However, this approach for exhaustively computing data-flow information cannot directly be applied to inference systems because of the ubiquitous execution of the rules. An algorithm is presented that efficiently performs a complete producer/consumer analysis for each antecedent and consequence clause in a knowledge base to optimally order the rules to minimize inference cycles. An algorithm was developed that optimally orders a knowledge base composed of forwarding chaining inference rules such that independent inference cycle executions are minimized, thus, resulting in significantly faster execution. This algorithm was integrated into the JPL tool Spacecraft Health Inference Engine (SHINE) for verification and it resulted in a significant reduction in inference cycles for what was previously considered an ordered knowledge base. For a knowledge base that is completely unordered, then the improvement is much greater.

James, Mark↗
NASA NTRS2003

Software Aids Visualization of Computed Unsteady Flow

Unsteady Flow Analysis Toolkit (UFAT) is a computer program that synthesizes motions of time-dependent flows represented by very large sets of data generated in computational fluid dynamics simulations. Prior to the development of UFAT, it was necessary to rely on static, single-snapshot depictions of time-dependent flows generated by flow-visualization software designed for steady flows. Whereas it typically takes weeks to analyze the results of a largescale unsteady-flow simulation by use of steady-flow visualization software, the analysis time is reduced to hours when UFAT is used. UFAT can be used to generate graphical objects of flow visualization results using multi-block curvilinear grids in the format of a previously developed NASA data-visualization program, PLOT3D. These graphical objects can be rendered using FAST, another popular flow visualization software developed at NASA. Flow-visualization techniques that can be exploited by use of UFAT include time-dependent tracking of particles, detection of vortex cores, extractions of stream ribbons and surfaces, and tetrahedral decomposition for optimal particle tracking. Unique computational features of UFAT include capabilities for automatic (batch) processing, restart, memory mapping, and parallel processing. These capabilities significantly reduce analysis time and storage requirements, relative to those of prior flow-visualization software. UFAT can be executed on a variety of supercomputers.

Kao, David↗
NASA NTRS1999

Is the spatial distribution of brain lesions associated with closed-head injury predictive of subsequent development of attention-deficit/hyperactivity disorder? Analysis with brain-image database

PURPOSE: To determine whether there is an association between the spatial distribution of lesions detected at magnetic resonance (MR) imaging of the brain in children after closed-head injury and the development of secondary attention-deficit/hyperactivity disorder (ADHD). MATERIALS AND METHODS: Data obtained from 76 children without prior history of ADHD were analyzed. MR images were obtained 3 months after closed-head injury. After manual delineation of lesions, images were registered to the Talairach coordinate system. For each subject, registered images and secondary ADHD status were integrated into a brain-image database, which contains depiction (visualization) and statistical analysis software. Using this database, we assessed visually the spatial distributions of lesions and performed statistical analysis of image and clinical variables. RESULTS: Of the 76 children, 15 developed secondary ADHD. Depiction of the data suggested that children who developed secondary ADHD had more lesions in the right putamen than children who did not develop secondary ADHD; this impression was confirmed statistically. After Bonferroni correction, we could not demonstrate significant differences between secondary ADHD status and lesion burdens for the right caudate nucleus or the right globus pallidus. CONCLUSION: Closed-head injury-induced lesions in the right putamen in children are associated with subsequent development of secondary ADHD. Depiction software is useful in guiding statistical analysis of image data.

NASA Discipline Neuroscience↗