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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS1977

Operational data processing: The first ten years are the hardest

A historical perspective of operational data processing and its development in the National Environmental Satellite Service is presented. The types of sensor data to be used in operational data processing are specified through the time period of the 1980's. Features that are essential for the design and implementation of a good data base system are outlined. Realistic standards for optimal data productions are discussed.

Leese, J. A.↗
NASA NTRS1986

International Solar-Terrestrial Program Data Processing Consortium

The present conception of the data processing scheme is described including the Main Processing Units (MPU) and Satellite Processing Units (SPU) which will acquire the data for the instruments presently planned in the International Solar Terrestrial Physics (ISTP) Project.

Torbert, R. B.↗
NASA NTRS1983

Spacelab Data Processing Facility

The capabilities of the Spacelab Data Processing Facility (SPDPF) are highlighted. The capturing, quality monitoring, processing, accounting, and forwarding of vital Spacelab data to various user facilities around the world are described.

Source record↗
NASA NTRS2010

HypsIRI On-Board Science Data Processing

Topics include On-board science data processing, on-board image processing, software upset mitigation, on-board data reduction, on-board 'VSWIR" products, HyspIRI demonstration testbed, and processor comparison.

Flatley, Tom↗
NASA NTRS1994

David Florida Laboratory Thermal Vacuum Data Processing System

During 1991, the Space Simulation Facility conducted a survey to assess the requirements and analyze the merits for purchasing a new thermal vacuum data processing system for its facilities. A new, integrated, cost effective PC-based system was purchased which uses commercial off-the-shelf software for operation and control. This system can be easily reconfigured and allows its users to access a local area network. In addition, it provides superior performance compared to that of the former system which used an outdated mini-computer and peripheral hardware. This paper provides essential background on the old data processing system's features, capabilities, and the performance criteria that drove the genesis of its successor. This paper concludes with a detailed discussion of the thermal vacuum data processing system's components, features, and its important role in supporting our space-simulation environment and our capabilities for spacecraft testing. The new system was tested during the ANIK E spacecraft test, and was fully operational in November 1991.

Choueiry, Elie↗
NASA NTRS1968

Principles of optical-data processing techniques

Document presents optical-data processing information on a level which will convey the basic principles involved to those having a general technical background. Mathematical discussions are included but are not required for a basic understanding.

Shulman, A. R.↗
NASA NTRS1974

On the access to an earth resources data processing system

The Purdue/LARS earth resources data processing system is briefly described. The considerations to which an organization would want to give attention before obtaining a remote terminal to this system are discussed. The support of such a terminal which Purdue/LARS is willing to propose is described.

Phillips, T. L.↗
NASA NTRS1976

Optical data processing study

An onboard coherent optical data processing system was designed to handle large information content of imagery at high speeds, reduce redundancy in picture transmission, and detect specific image features. Theoretically derived Fourier transform characteristics for simple but representative two dimensional images served as a basis for predicting expected features of actual target images. Fourier transformation and spatial filtering of coherent optical images was accomplished theoretically and in the laboratory. The effect of various parameters such as optical aperature, incidence angles, the transparency assumption, the thin lens approximation on resolution, and performance of the system are predicted and tested.

Pinson, L. J.↗
NASA NTRS1991

Computing and data processing

The applications of computers and data processing to astronomy are discussed. Among the topics covered are the emerging national information infrastructure, workstations and supercomputers, supertelescopes, digital astronomy, astrophysics in a numerical laboratory, community software, archiving of ground-based observations, dynamical simulations of complex systems, plasma astrophysics, and the remote control of fourth dimension supercomputers.

Smarr, Larry↗
NASA NTRS1992

Incomplete fuzzy data processing systems using artificial neural network

In this paper, the implementation of a fuzzy data processing system using an artificial neural network (ANN) is discussed. The binary representation of fuzzy data is assumed, where the universe of discourse is decartelized into n equal intervals. The value of a membership function is represented by a binary number. It is proposed that incomplete fuzzy data processing be performed in two stages. The first stage performs the 'retrieval' of incomplete fuzzy data, and the second stage performs the desired operation on the retrieval data. The method of incomplete fuzzy data retrieval is proposed based on the linear approximation of missing values of the membership function. The ANN implementation of the proposed system is presented. The system was computationally verified and showed a relatively small total error.

Patyra, Marek J.↗
NASA NTRS2003

On the Hilbert-Huang Transform Data Processing System Development

One of the main heritage tools used in scientific and engineering data spectrum analysis is the Fourier Integral Transform and its high performance digital equivalent - the Fast Fourier Transform (FFT). The Fourier view of nonlinear mechanics that had existed for a long time, and the associated FFT (fairly recent development), carry strong a-priori assumptions about the source data, such as linearity and of being stationary. Natural phenomena measurements are essentially nonlinear and nonstationary. A very recent development at the National Aeronautics and Space Administration (NASA) Goddard Space Flight Center (GSFC), known as the Hilbert-Huang Transform (HHT) proposes a novel approach to the solution for the nonlinear class of spectrum analysis problems. Using the Empirical Mode Decomposition (EMD) followed by the Hilbert Transform of the empirical decomposition data (HT), the HHT allows spectrum analysis of nonlinear and nonstationary data by using an engineering a-posteriori data processing, based on the EMD algorithm. This results in a non-constrained decomposition of a source real value data vector into a finite set of Intrinsic Mode Functions (IMF) that can be further analyzed for spectrum interpretation by the classical Hilbert Transform. This paper describes phase one of the development of a new engineering tool, the HHT Data Processing System (HHTDPS). The HHTDPS allows applying the "T to a data vector in a fashion similar to the heritage FFT. It is a generic, low cost, high performance personal computer (PC) based system that implements the HHT computational algorithms in a user friendly, file driven environment. This paper also presents a quantitative analysis for a complex waveform data sample, a summary of technology commercialization efforts and the lessons learned from this new technology development.

Kizhner, Semion↗
NASA NTRS1985

Mathematical analysis study for radar data processing and enhancement. Part 1: Radar data analysis

A study is performed under NASA contract to evaluate data from an AN/FPS-16 radar installed for support of flight programs at Dryden Flight Research Facility of NASA Ames Research Center. The purpose of this study is to provide information necessary for improving post-flight data reduction and knowledge of accuracy of derived radar quantities. Tracking data from six flights are analyzed. Noise and bias errors in raw tracking data are determined for each of the flights. A discussion of an altiude bias error during all of the tracking missions is included. This bias error is defined by utilizing pressure altitude measurements made during survey flights. Four separate filtering methods, representative of the most widely used optimal estimation techniques for enhancement of radar tracking data, are analyzed for suitability in processing both real-time and post-mission data. Additional information regarding the radar and its measurements, including typical noise and bias errors in the range and angle measurements, is also presented. This is in two parts. This is part 1, an analysis of radar data.

James, R.↗
DOE OSTI2014

A Scientific Data Processing Framework for Time Series NetCDF Data

ARM Data Integrator (ADI) is a framework to streamline the development of scientific algorithms that analyze time-series NetCDF data, and to improve the content and consistency of the output data products produced by these algorithms. ADI achieves these goals by automating the process of retrieving and preparing data for analysis, supporting the definition of output data products through a graphical interface, and providing a modular, flexible software development architecture. The input data, preprocessing, and output data specifications are defined through a graphical interface and stored in a database. ADI also includes a workflow for data integration, a library of software modules to support the workflow, and a source code generator that produces C, IDL and Python templates. Data preparation support includes automated retrieval of data from input files, merging the retrieved data into appropriately sized chunks, and transformation of the data onto a common coordinate system grid. Through the graphical interface, users can view the details of both their data products and those in the ARM catalog. The variable and attribute definitions of the existing data products can be used to build new output data products. In addition, the rules that make up the ARM archive’s data standards are laid on top of the view of the new data product providing the user with a visual cue indicating where their output violates an archive standard. The necessary configurations are stored in a database that is accessed by the ADI libraries. This paper discusses the ADI framework, its supporting components, and how ADI can significantly decrease the time and cost of implementing scientific algorithms while improving the ability of scientists to disseminate their results.

Atmospheric Science↗