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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS1986

MCC flight operations automation of STS orbiter systems monitoring

The integration of new capabilities into the Mission Control Center at the Johnson Space Center in Houston, Texas in order to improve the data monitoring and analysis of the STS is discussed. User interface application software and systems, such as the flight data file Shuttle mission simulator and failure analysis program, to be utilized for flight operations automation are examined. Consideration is given to task automation, the trend monitoring system, the data retrieval system, and the launch processing system. The development and functions of the Shuttle data analysis system, which is to operate in real time, are described.

Bates, William V., Jr.↗
NASA NTRS1993

Applications of CCSDS recommendations to Integrated Ground Data Systems (IGDS)

This paper describes an application of the CCSDS Principle Network (CPH) service model to communications network elements of a postulated Integrated Ground Data System (IGDS). Functions are drawn principally from COSMICS (Cosmic Information and Control System), an integrated space control infrastructure, and the Earth Observing System Data and Information System (EOSDIS) Core System (ECS). From functional requirements, this paper derives a set of five communications network partitions which, taken together, support proposed space control infrastructures and data distribution systems. Our functional analysis indicates that the five network partitions derived in this paper should effectively interconnect the users, centers, processors, and other architectural elements of an IGDS. This paper illustrates a useful application of the CCSDS (Consultive Committee for Space Data Systems) Recommendations to ground data system development.

Mizuta, Hiroshi↗
NASA NTRS1980

Description of a user-oriented geographic information system - The resource analysis program

This paper describes the Resource Analysis Program, an applied geographic information system. Several applications are presented which utilized soil, and other natural resource data, to develop integrated maps and data analyses. These applications demonstrate the methods of analysis and the philosophy of approach used in the mapping system. The applications are evaluated in reference to four major needs of a functional mapping system: data capture, data libraries, data analysis, and mapping and data display. These four criteria are then used to describe an effort to develop the next generation of applied mapping systems. This approach uses inexpensive microcomputers for field applications and should prove to be a viable entry point for users heretofore unable or unwilling to venture into applied computer mapping.

Tilmann, S. E.↗
NASA NTRS2008

Safe Upper-Bounds Inference of Energy Consumption for Java Bytecode Applications

Many space applications such as sensor networks, on-board satellite-based platforms, on-board vehicle monitoring systems, etc. handle large amounts of data and analysis of such data is often critical for the scientific mission. Transmitting such large amounts of data to the remote control station for analysis is usually too expensive for time-critical applications. Instead, modern space applications are increasingly relying on autonomous on-board data analysis. All these applications face many resource constraints. A key requirement is to minimize energy consumption. Several approaches have been developed for estimating the energy consumption of such applications (e.g. [3, 1]) based on measuring actual consumption at run-time for large sets of random inputs. However, this approach has the limitation that it is in general not possible to cover all possible inputs. Using formal techniques offers the potential for inferring safe energy consumption bounds, thus being specially interesting for space exploration and safety-critical systems. We have proposed and implemented a general frame- work for resource usage analysis of Java bytecode [2]. The user defines a set of resource(s) of interest to be tracked and some annotations that describe the cost of some elementary elements of the program for those resources. These values can be constants or, more generally, functions of the input data sizes. The analysis then statically derives an upper bound on the amount of those resources that the program as a whole will consume or provide, also as functions of the input data sizes. This article develops a novel application of the analysis of [2] to inferring safe upper bounds on the energy consumption of Java bytecode applications. We first use a resource model that describes the cost of each bytecode instruction in terms of the joules it consumes. With this resource model, we then generate energy consumption cost relations, which are then used to infer safe upper bounds. How energy consumption for each bytecode instruction is measured is beyond the scope of this paper. Instead, this paper is about how to infer safe energy consumption estimations assuming that those energy consumption costs are provided. For concreteness, we use a simplified version of an existing resource model [1] in which an energy consumption cost for individual Java opcodes is defined.

Navas, Jorge↗
NASA NTRS1977

Earth resources interactive processing system

System allows for processing and analysis of remotely-sensed Earth resources data. System may be modified for other sensors and allows numerous analysis functions on various types of image data.

Source record↗
NASA NTRS2018

GMI-IPS: Python Processing Software for Aircraft Campaigns

NASA's Atmospheric Tomography Mission (ATom) seeks to understand the impact of anthropogenic air pollution on gases in the Earth's atmosphere. Four flight campaigns are being deployed on a seasonal basis to establish a continuous global-scale data set intended to improve the representation of chemically reactive gases in global atmospheric chemistry models. The Global Modeling Initiative (GMI), is creating chemical transport simulations on a global scale for each of the ATom flight campaigns. To meet the computational demands required to translate the GMI simulation data to grids associated with the flights from the ATom campaigns, the GMI ICARTT Processing Software (GMI-IPS) has been developed and is providing key functionality for data processing and analysis in this ongoing effort. The GMI-IPS is written in Python and provides computational kernels for data interpolation and visualization tasks on GMI simulation data. A key feature of the GMI-IPS, is its ability to read ICARTT files, a text-based file format for airborne instrument data, and extract the required flight information that defines regional and temporal grid parameters associated with an ATom flight. Perhaps most importantly, the GMI-IPS creates ICARTT files containing GMI simulated data, which are used in collaboration with ATom instrument teams and other modeling groups. The initial main task of the GMI-IPS is to interpolate GMI model data to the finer temporal resolution (1-10 seconds) of a given flight. The model data includes basic fields such as temperature and pressure, but the main focus of this effort is to provide species concentrations of chemical gases for ATom flights. The software, which uses parallel computation techniques for data intensive tasks, linearly interpolates each of the model fields to the time resolution of the flight. The temporally interpolated data is then saved to disk, and is used to create additional derived quantities. In order to translate the GMI model data to the spatial grid of the flight path as defined by the pressure, latitude, and longitude points at each flight time record, a weighted average is then calculated from the nearest neighbors in two dimensions (latitude, longitude). Using SciPya's Regular Grid Interpolator, interpolation functions are generated for the GMI model grid and the calculated weighted averages. The flight path points are then extracted from the ATom ICARTT instrument file, and are sent to the multi-dimensional interpolating functions to generate GMI field quantities along the spatial path of the flight. The interpolated field quantities are then written to a ICARTT data file, which is stored for further manipulation. The GMI-IPS is aware of a generic ATom ICARTT header format, containing basic information for all flight campaigns. The GMI-IPS includes logic to edit metadata for the derived field quantities, as well as modify the generic header data such as processing dates and associated instrument files. The ICARTT interpolated data is then appended to the modified header data, and the ICARTT processing is complete for the given flight and ready for collaboration. The output ICARTT data adheres to the ICARTT file format standards V1.1. The visualization component of the GMI-IPS uses Matplotlib extensively and has several functions ranging in complexity. First, it creates a model background curtain for the flight (time versus model eta levels) with the interpolated flight data superimposed on the curtain. Secondly, it creates a time-series plot of the interpolated flight data. Lastly, the visualization component creates averaged 2D model slices (longitude versus latitude) with overlaid flight track circles at key pressure levels. The GMI-IPS consists of a handful of classes and supporting functionality that have been generalized to be compatible with any ICARTT file that adheres to the base class definition. The base class represents a generic ICARTT entry, only defining a single time entry and 3D spatial positioning parameters. Other classes inherit from this base class; several classes for input ICARTT instrument files, which contain the necessary flight positioning information as a basis for data processing, as well as other classes for output ICARTT files, which contain the interpolated model data. Utility classes provide functionality for routine procedures such as: comparing field names among ICARTT files, reading ICARTT entries from a data file and storing them in data structures, and returning a reduced spatial grid based on a collection of ICARTT entries. Although the GMI-IPS is compatible with GMI model data, it can be adapted with reasonable effort for any simulation that creates Hierarchical Data Format (HDF) files. The same can be said of its adaptability to ICARTT files outside of the context of the ATom mission. The GMI-IPS contains just under 30,000 lines of code, eight classes, and a dozen drivers and utility programs. It is maintained with GIT source code management and has been used to deliver processed GMI model data for the ATom campaigns that have taken place to date.

Damon, M. R.↗
NASA NTRS1991

Intraseasonal oscillations in the global atmosphere. I - Northern Hemisphere and tropics

Oscillatory modes in the Northern Hemisphere and in the tropics were examined systematically. The 700 mb heights were used to analyze extratropical oscillations, and the outgoing longwave radiation to study tropical oscillations in convection. All datasets were band-pass filtered to focus on the intraseasonal (IS) band of 10-120 days. Leading spatial patterns of variability were obtained by applying empirical orthogonal function analysis to these IS data. The leading principal components were subjected to singular spectrum analysis. In the Northern Hemisphere, there are two important modes of oscillation with periods near 48 and 23 days, respectively. The 48-day mode is the most important of the two. It has both traveling and standing components, and is dominated by a zonal wavenumber two. The 23-day mode has the spatial structure and propagation properties described by Branstator and by Kushnir (1987). In the tropics, the 40-50 day oscillation documented by Madden and Julian (1972), Weickmann (1983), Lau, and their colleagues, dominates the Indian and Pacific oceans from 60 deg E to the date line. From 170 deg W to 90 deg W, however, a 24-28 day oscillation is equally strong. The extratropical modes are often independent of, and sometimes lead, the tropical modes.

Ghil, Michael↗
NASA NTRS1992

The NASA JSC Hypervelocity Impact Test Facility (HIT-F)

The NASA Johnson Space Center Hypervelocity Impact Test Facility was created in 1980 to study the hypervelocity impact characteristics of composite materials. The facility consists of the Hypervelocity Impact Laboratory (HIRL) and the Hypervelocity Analysis Laboratory (HAL). The HIRL supports three different-size light-gas gun ranges which provide the capability of launching particle sizes from 100 micron spheres to 12.7 mm cylinders. The HAL performs three functions: (1) the analysis of data collected from shots in the HIRL, (2) numerical and analytical modeling to predict impact response beyond test conditions, and (3) risk and damage assessments for spacecraft exposed to the meteoroid and orbital debris environments.

Crews, Jeanne L.↗
NASA NTRS2012

Analysis of Suomi - NPP VIIRS Vignetting Functions Based on Yaw Maneuver Data

The Suomi NPP Visible Infrared Imager Radiometer Suite (VIIRS) reflective bands are calibrated on-orbit via reference to regular solar observations through a solar attenuation screen (SAS) and diffusely reflected off a Spectralon (Registered Trademark) panel. The degradation of the Spectralon panel BRDF due to UV exposure is tracked via a ratioing radiometer (SDSM) which compares near simultaneous observations of the panel with direct observations of the sun (through a separate attenuation screen). On-orbit, the vignetting functions of both attenuation screens are most easily measured when the satellite performs a series of yaw maneuvers over a short period of time (thereby covering the yearly angular variation of solar observations in a couple of days). Because the SAS is fixed, only the product of the screen transmission and the panel BRDF was measured. Moreover, this product was measured by both VIIRS detectors as well as the SDSM detectors (albeit at different reflectance angles off the Spectralon panel). The SDSM screen is also fixed; in this case, the screen transmission was measured directly. Corrections for instrument drift and degradation, solar geometry, and spectral effects were taken into consideration. The resulting vignetting functions were then compared to the pre-launch measurements as well as models based on screen geometry.

Xiong, Xiaoxiong↗
NASA NTRS1987

Subcentimeter-size particle distribution functions in planetary rings from Voyager radio and photopolarimeter occultation data

Analysis of measurements of the scattered and direct components of Voyager 1 radio occultation signals at 3.5 and 13 cm wavelengths yield estimates of the distribution functions of supracentimeter-size particles and thickness of relatively broad regions in Saturn's rings. If mearurements of signal amplitude at a shorter wavelength are combined with the previously analyzed data, the shape of the distribution functions characterizing the smaller particles can be constrained. If size distributions of arbitrary form were considered, many solutions are found that are consistent with the three available observations of signal amplitude. The best-fit power law was calculated to the three observations at three wavelengths for several of the embedded Saturn ringlets. Mie scattering theory predicts that the measured phase of the radio occultation signal is highly sensitive to particles ranging from 0.1 to 1.0 wavelengths in size, thus additional constraints on the subcentimeter-size distribution functions for both the Saturn and Uranus rings can in principle be derived from radio phase measurements.

Zebker, Howard A.↗
NASA NTRS1992

Compiler analysis for irregular problems in FORTRAN D

We developed a dataflow framework which provides a basis for rigorously defining strategies to make use of runtime preprocessing methods for distributed memory multiprocessors. In many programs, several loops access the same off-processor memory locations. Our runtime support gives us a mechanism for tracking and reusing copies of off-processor data. A key aspect of our compiler analysis strategy is to determine when it is safe to reuse copies of off-processor data. Another crucial function of the compiler analysis is to identify situations which allow runtime preprocessing overheads to be amortized. This dataflow analysis will make it possible to effectively use the results of interprocedural analysis in our efforts to reduce interprocessor communication and the need for runtime preprocessing.

Vonhanxleden, Reinhard↗
NASA NTRS1978

Digital image analysis of Landsat data

The paper defines some basic processing functions than can be performed digitally, discusses a variety of computer peripherals including hard copy output devices and television terminals, compares the characteristics of stand-alone image analysis systems, and briefly describes the important features of image processing and geographic information systems software. Several examples are discussed to demonstrate the efficient use of computers through implementation of hard copy image recorders and television display terminals. The commercially available stand-alone image analysis systems include a computer, appropriate peripherals, and sufficient software to perform analysis without other computational support.

Alford, W. L.↗
NASA NTRS1977

Interpolation algorithms and image data artifacts

Interpolation, or resampling coefficients, which are generated from low pass filter Fourier transforms yield more accurate resampled values than those obtained using cubic spline techniques. This is due to the utilization of six data points rather than four as currently used in cubic spline analysis. After resampling functions are applied to image data, artifacts which are similar to ringing may become pronounced. These effects are often present in the original data and the interpolation merely enhances them.

Forman, M. L.↗
NASA NTRS1989

DATAMAP upgrade version 4.0

The changes made on the data analysis and management program DATAMAP (Data from Aeromechanics Test and Analytics - Management and Analysis Package) are detailed. These changes are made to Version 3.07 (released February, 1981) and are called Version 4.0. Version 4.0 improvements were performed by Sterling Software under contract to NASA Ames Research Center. The increased capabilities instituted in this version include the breakout of the source code into modules for ease of modification, addition of a more accurate curve fit routine, ability to handle higher frequency data, additional data analysis features, and improvements in the functionality of existing features. These modification will allow DATAMAP to be used on more data sets and will make future modifications and additions easier to implement.

Watts, Michael E.↗
NASA NTRS1974

Rational functional representation of flap noise spectra including correction for reflection effects

A rational function is presented for the acoustic spectra generated by deflection of engine exhaust jets for under-the-wing and over-the-wing versions of externally blown flaps. The functional representation is intended to provide a means for compact storage of data and for data analysis. The expressions are based on Fourier transform functions for the Strouhal normalized pressure spectral density, and on a correction for reflection effects based on Thomas' (1969) N-independent-source model extended by use of a reflected ray transfer function. Curve fit comparisons are presented for blown-flap data taken from turbofan engine tests and from large-scale cold-flow model tests. Application of the rational function to scrubbing noise theory is also indicated.

Miles, J. H.↗