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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 NTRS2003

XML-Based Generator of C++ Code for Integration With GUIs

An open source computer program has been developed to satisfy a need for simplified organization of structured input data for scientific simulation programs. Typically, such input data are parsed in from a flat American Standard Code for Information Interchange (ASCII) text file into computational data structures. Also typically, when a graphical user interface (GUI) is used, there is a need to completely duplicate the input information while providing it to a user in a more structured form. Heretofore, the duplication of the input information has entailed duplication of software efforts and increases in susceptibility to software errors because of the concomitant need to maintain two independent input-handling mechanisms. The present program implements a method in which the input data for a simulation program are completely specified in an Extensible Markup Language (XML)-based text file. The key benefit for XML is storing input data in a structured manner. More importantly, XML allows not just storing of data but also describing what each of the data items are. That XML file contains information useful for rendering the data by other applications. It also then generates data structures in the C++ language that are to be used in the simulation program. In this method, all input data are specified in one place only, and it is easy to integrate the data structures into both the simulation program and the GUI. XML-to-C is useful in two ways: 1. As an executable, it generates the corresponding C++ classes and 2. As a library, it automatically fills the objects with the input data values.

Hua, Hook↗
NASA NTRS1990

Simplified detection and correction of critical data for ill-conditioned systems

Ill-conditioned systems arising in analysis and optimization can display a high sensitivity to numerical precision for changes and errors in data input. Such data may be in the form of system parameter input or desired system response. The ill-conditioning referred to generally arises from the lack of sufficient independent data to define a complex system or the weak sensitivity of response to source input parameters. It is shown how small errors in data and assumed fixed and known parameters can lead to highly erroneous results in ill-conditioned linear algebraic equations. A simplified detection and correction of critical input data arising in the coefficient matrix and desired response (i.e., right hand side) is proposed.

Ojalvo, Irving U.↗
NASA NTRS1980

Shipboard fisheries management terminals

The needs of the National Marine Fisheries Service (NMGS), National Weather Service, and the U.S. Coast Guard for locational, biological, and environmental data were assessed. The fisheries conservation zones and the yellowfin tuna jurisdiction of the NMFS operates observer programs on foreign and domestic fishing vessels. Data input terminal and data transfer and processing technology are reviewed to establish available capability. A matrix of implementation options is generated to identify the benefits of each option, and preliminary cost estimates are made. Recommendations are made for incremental application of available off the shelf hardware to obtain improved performance and benefits within a well bounded cost. Terminal recommendations are made for three interdependent shipboard units emphasizing: (1) the determination of location and fishing activity; (2) hand held data inputting and formatting in the fishing work areas; and (3) data manipulation, merging, and editing.

Nagler, R. G.↗
NASA NTRS1981

Laboratory data manipulation tools basic data handling programs. Volume 2: Detailed software/hardware documentation

The set of computer programs described allows for data definition, data input, and data transfer between the LSI-11 microcomputers and the VAX-11/780 minicomputer. Program VAXCOM allows for a simple method of textual file transfer from the LSI to the VAX. Program LSICOM allows for easy file transfer from the VAX to the LSI. Program TTY changes the LSI-11 operators console to the LSI's printing device. Program DICTIN provides a means for defining a data set for input to either computer. Program DATAIN is a simple to operate data entry program which is capable of building data files on either machine. Program LEDITV is an extremely powerful, easy to use, line oriented text editor. Program COPYSBF is designed to print out textual files on the line printer without character loss from FORTRAN carriage control or wide record transfer.

Source record↗
NASA NTRS1992

Earth observing system. Output data products and input requirements, version 2.0. Volume 1: Instrument data product characteristics

Information on Earth Observing System (EOS) output data products and input data requirements that has been compiled by the Science Processing Support Office (SPSO) at GSFC is presented. Since Version 1.0 of the SPSO Report was released in August 1991, there have been significant changes in the EOS program. In anticipation of a likely budget cut for the EOS Project, NASA HQ restructured the EOS program. An initial program consisting of two large platforms was replaced by plans for multiple, smaller platforms, and some EOS instruments were either deselected or descoped. Updated payload information reflecting the restructured EOS program superseding the August 1991 version of the SPSO report is included. This report has been expanded to cover information on non-EOS data products, and consists of three volumes (Volumes 1, 2, and 3). Volume 1 provides information on instrument outputs and input requirements. Volume 2 is devoted to Interdisciplinary Science (IDS) outputs and input requirements, including the 'best' and 'alternative' match analysis. Volume 3 provides information about retrieval algorithms, non-EOS input requirements of instrument teams and IDS investigators, and availability of non-EOS data products at seven primary Distributed Active Archive Centers (DAAC's).

Lu, Yun-Chi↗
NASA NTRS1972

TRW vortex-lattice method subsonic aerodynamic analysis for multiple-lifting-surfaces (N. surface) TRW program number HA010B

The program was designed to provide solutions of engineering accuracy for determining the aerodynamic loads on single- or multiple-lifting-surface configurations that represent vehicles in subsonic flight, e.g., wings, wing-tail, wing-canard, lifting bodies, etc. The preparation is described of the input data, associated input arrangement, and the output format for the program data, including specification of the various operational details of the program such as array sizes, tape numbers utilized, and program dumps. A full description of the underlying theory used in the program development and a review of the program qualification tests are included.

Gomez, A. V.↗
NASA NTRS2021

Harmonized Emissions Component (HEMCO) 3.0 as a Versatile Emissions Component for Atmospheric Models: Application in the GEOS-Chem, NASA GEOS, WRF-GC, CESM2, NOAA GEFS-Aerosol, and NOAA UFS Models

Emissions are a central component of atmospheric chemistry models. The Harmonized Emissions Component (HEMCO) is a software component for computing emissions from a user-selected ensemble of emission inventories and algorithms. It allows users to re-grid, combine, overwrite, subset, and scale emissions from different inventories through a configuration file and with no change to the model source code. The configuration file also maps emissions to model species with appropriate units. HEMCO can operate in offline stand-alone mode, but more importantly it provides an online facility for models to compute emissions at runtime. HEMCO complies with the Earth System Modeling Framework (ESMF) for portability across models. We present a new version here, HEMCO 3.0, that features an improved three-layer architecture to facilitate implementation into any atmospheric model and improved capability for calculating emissions at any model resolution including multiscale and unstructured grids. The three-layer architecture of HEMCO 3.0 includes (1) the Data Input Layer that reads the configuration file and accesses the HEMCO library of emission inventories and other environmental data, (2) the HEMCO Core that computes emissions on the user-selected HEMCO grid, and (3) the Model Interface Layer that re-grids (if needed) and serves the data to the atmospheric model and also serves model data to the HEMCO Core for computing emissions dependent on model state (such as from dust or vegetation). The HEMCO Core is common to the implementation in all models, while the Data Input Layer and the Model Interface Layer are adaptable to the model environment. Default versions of the Data Input Layer and Model Interface Layer enable straightforward implementation of HEMCO in any simple model architecture, and options are available to disable features such as re-gridding that may be done by independent couplers in more complex architectures. The HEMCO library of emission inventories and algorithms is continuously enriched through user contributions so that new inventories can be immediately shared across models. HEMCO can also serve as a general data broker for models to process input data not only for emissions but for any gridded environmental datasets. We describe existing implementations of HEMCO 3.0 in (1) the GEOS-Chem “Classic” chemical transport model with shared-memory infrastructure, (2) the high-performance GEOS-Chem (GCHP) model with distributed-memory architecture, (3) the NASA GEOS Earth System Model (GEOS ESM), (4) the Weather Research and Forecasting model with GEOS-Chem (WRF-GC), (5) the Community Earth System Model Version 2 (CESM2), and (6) the NOAA Global Ensemble Forecast System – Aerosols (GEFS-Aerosols), as well as the planned implementation in the NOAA Unified Forecast System (UFS). Implementation of HEMCO in CESM2 contributes to the Multi-Scale Infrastructure for Chemistry and Aerosols (MUSICA) by providing a common emissions infrastructure to support different simulations of atmospheric chemistry across scales.

Haipeng Lin↗
NASA NTRS1988

Dewar to dewar model for superfluid helium transfer

A model has been developed to predict the flow of He II between a source and a receiving dewar. The model uses a finite difference aproximation to integrate the describing equations. The transfer path may contain porous plugs or mechanical pumps, heater sections, heat leaks, constrictions due to valves, and bends. These line elements may occur in any order and in any quantity. The line elements are easily reconfigured by changing the input data. The input consists of the number of finite element cells, the pressure in each dewar, the heat input to each section and the dimensions of each section. The output is the temperature, pressure, flow rate, velocities and heat flux in each section. An internal reference table provides the properties of He II. The model is programmed for a LOTUS work sheet. It converges rapidly and usually requires 10 to 15 iterations. For most applications an iteration takes 30 s on an AT. The predictions agree well with experimental data.

Snyder, H. A.↗
NASA NTRS1974

Earth Observatory Satellite system definition study. Report 5: System design and specifications. Volume 6: Specification for EOS Central Data Processing Facility (CDPF)

The specifications and functions of the Central Data Processing (CDPF) Facility which supports the Earth Observatory Satellite (EOS) are discussed. The CDPF will receive the EOS sensor data and spacecraft data through the Spaceflight Tracking and Data Network (STDN) and the Operations Control Center (OCC). The CDPF will process the data and produce high density digital tapes, computer compatible tapes, film and paper print images, and other data products. The specific aspects of data inputs and data processing are identified. A block diagram of the CDPF to show the data flow and interfaces of the subsystems is provided.

Source record↗
NASA NTRS1993

A review and analysis of neural networks for classification of remotely sensed multispectral imagery

A literature survey and analysis of the use of neural networks for the classification of remotely sensed multispectral imagery is presented. As part of a brief mathematical review, the backpropagation algorithm, which is the most common method of training multi-layer networks, is discussed with an emphasis on its application to pattern recognition. The analysis is divided into five aspects of neural network classification: (1) input data preprocessing, structure, and encoding; (2) output encoding and extraction of classes; (3) network architecture, (4) training algorithms; and (5) comparisons to conventional classifiers. The advantages of the neural network method over traditional classifiers are its non-parametric nature, arbitrary decision boundary capabilities, easy adaptation to different types of data and input structures, fuzzy output values that can enhance classification, and good generalization for use with multiple images. The disadvantages of the method are slow training time, inconsistent results due to random initial weights, and the requirement of obscure initialization values (e.g., learning rate and hidden layer size). Possible techniques for ameliorating these problems are discussed. It is concluded that, although the neural network method has several unique capabilities, it will become a useful tool in remote sensing only if it is made faster, more predictable, and easier to use.

Paola, Justin D.↗
NASA NTRS2000

Access to Space Interactive Design Web Site

The Access To Space (ATS) Group at NASA's Goddard Space Flight Center (GSFC) supports the science and technology community at GSFC by facilitating frequent and affordable opportunities for access to space. Through partnerships established with access mode suppliers, the ATS Group has developed an interactive Mission Design web site. The ATS web site provides both the information and the tools necessary to assist mission planners in selecting and planning their ride to space. This includes the evaluation of single payloads vs. ride-sharing opportunities to reduce the cost of access to space. Features of this site include the following: (1) Mission Database. Our mission database contains a listing of missions ranging from proposed missions to manifested. Missions can be entered by our user community through data input tools. Data is then accessed by users through various search engines: orbit parameters, ride-share opportunities, spacecraft parameters, other mission notes, launch vehicle, and contact information. (2) Launch Vehicle Toolboxes. The launch vehicle toolboxes provide the user a full range of information on vehicle classes and individual configurations. Topics include: general information, environments, performance, payload interface, available volume, and launch sites.

Leon, John↗
NASA NTRS2010

Device and method to enhance availability of cluster-based processing systems

An electronic computing device including at least one processing unit that implements a specific fault signal upon experiencing an associated fault, a control unit that generates a specific recovery signal upon receiving the fault signal from the at least one processing unit, and at least one input memory unit. The recovery signal initiates specific recovery processes in the at least one processing unit. The input memory buffers input data signals input to the at least one processing unit that experienced the fault during the recovery period.

Lupia, David J.↗
NASA NTRS1973

An interactive NASTRAN preprocessor

A Langley Research Center version of NASTRAN Level 15.1.0 designed to provide the analyst with an added tool for debugging massive NASTRAN input data is described. The program checks all NASTRAN input data cards and displays on a CRT the graphic representation of the undeformed structure. In addition, the program permits the display and alteration of input data and allows reexecution without physically resubmitting the job. Core requirements on the CDC 6000 computer are approximately 77,000 octal words of central memory.

Smith, W. W.↗
NASA NTRS1989

Application of the p-version of the finite-element method to global-local problems

A brief survey is given of some recent developments in finite-element analysis technology which bear upon the three main research areas under consideration in this workshop: (1) analysis methods; (2) software testing and quality assurance; and (3) parallel processing. The variational principle incorporated in a finite-element computer program, together with a particular set of input data, determines the exact solution corresponding to that input data. Most finite-element analysis computer programs are based on the principle of virtual work. In the following, researchers consider only programs based on the principle of virtual work and denote the exact displacement vector field corresponding to some specific set of input data by vector u(EX). The exact solution vector u(EX) is independent of the design of the mesh or the choice of elements. Except for very simple problems, or specially constructed test problems, vector u(EX) is not known. Researchers perform a finite-element analysis (or any other numerical analysis) because they wish to make conclusions concerning the response of a physical system to certain imposed conditions, as if vector u(EX) were known.

Szabo, Barna A.↗
NASA NTRS2012

Directed Design of Experiments for Validating Probability of Detection Capability of a Testing System

A method of validating a probability of detection (POD) testing system using directed design of experiments (DOE) includes recording an input data set of observed hit and miss or analog data for sample components as a function of size of a flaw in the components. The method also includes processing the input data set to generate an output data set having an optimal class width, assigning a case number to the output data set, and generating validation instructions based on the assigned case number. An apparatus includes a host machine for receiving the input data set from the testing system and an algorithm for executing DOE to validate the test system. The algorithm applies DOE to the input data set to determine a data set having an optimal class width, assigns a case number to that data set, and generates validation instructions based on the case number.

Generazio, Edward R.↗
NASA NTRS1993

Intelligent data presentation for real-time spacecraft monitoring

This paper describes an intelligent user interface that is currently under development. The interface serves as a front end for real-time spacecraft monitoring software. The software operates under circumstances in which neither an intelligent human without automated assistance nor an automated system without intelligence are sufficiently effective. The user interface is supported by dynamic trade-off evaluation (DTE), a new technique that has been developed to automate general types of performance trade-offs in real-time problem solving systems. In this application, DTE is used to perform dynamic input data management for the purpose of determining which input data should be monitored in time constrained situations and how to present the monitoring information to a human analyst who has the ultimate responsibility for the spacecraft. This application has demonstrated that DTE can be used to dynamically vary the data that is monitored, making it possible to detect and correctly analyze all anomalous data by examining only a subset of the total input data. In carefully structured experimental evaluations that use real spacecraft data and real decision making, DTE provides the ability to handle a three-fold increase in input data (in real-time) without loss of performance and to intelligently present the information to a mission analyst.

Schwuttke, U. M.↗
NASA NTRS1991

Program Analyzes Errors In STAGS

EAC computer program designed for analysis of errors in results of STAGS computer program (COSMIC Program HQN-10967). Requires input data for geometry of plate, properties of material, and set of boundary conditions. These input data come from STAGS code. (The specific link between input and output data from STAGS and input data for EAC is POSTP, postprocessor program in STAGS processors.) EAC computes continuous solution from discrete results of STAGS in order to estimate error of results of STAGS. Written in FORTRAN 77.

Thurston, Gaylen A.↗