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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
NASA NTRS1996

Design and implementation of a Windows NT network to support CNC activities

The Manufacturing, Materials, & Processes Technology Division is undergoing dramatic changes to bring it's manufacturing practices current with today's technological revolution. The Division is developing Computer Automated Design and Computer Automated Manufacturing (CAD/CAM) abilities. The development of resource tracking is underway in the form of an accounting software package called Infisy. These two efforts will bring the division into the 1980's in relationship to manufacturing processes. Computer Integrated Manufacturing (CIM) is the final phase of change to be implemented. This document is a qualitative study and application of a CIM application capable of finishing the changes necessary to bring the manufacturing practices into the 1990's. The documentation provided in this qualitative research effort includes discovery of the current status of manufacturing in the Manufacturing, Materials, & Processes Technology Division including the software, hardware, network and mode of operation. The proposed direction of research included a network design, computers to be used, software to be used, machine to computer connections, estimate a timeline for implementation, and a cost estimate. Recommendation for the division's improvement include action to be taken, software to utilize, and computer configurations.

Shearrow, C. A.↗
NASA NTRS1999

Constellation Design of the Mars Network

Mars has become the focus of an unprecedented series of missions spanning many years, involving numerous nations and evolving from robotics to humans.

Constellation Design Communications Navigation↗
NASA NTRS2002

Evolutionary Design of a Robotic Material Defect Detection System

During the post-flight inspection of SSME engines, several inaccessible regions must be disassembled to inspect for defects such as cracks, scratches, gouges, etc. An improvement to the inspection process would be the design and development of very small robots capable of penetrating these inaccessible regions and detecting the defects. The goal of this research was to utilize an evolutionary design approach for the robotic detection of these types of defects. A simulation and visualization tool was developed prior to receiving the hardware as a development test bed. A small, commercial off-the-shelf (COTS) robot was selected from several candidates as the proof of concept robot. The basic approach to detect the defects was to utilize Cadmium Sulfide (CdS) sensors to detect changes in contrast of an illuminated surface. A neural network, optimally designed utilizing a genetic algorithm, was employed to detect the presence of the defects (cracks). By utilization of the COTS robot and US sensors, the research successfully demonstrated that an evolutionarily designed neural network can detect the presence of surface defects.

Ballard, Gary↗
NASA NTRS1995

Teledesic Global Wireless Broadband Network: Space Infrastructure Architecture, Design Features and Technologies

The Teledesic satellites are a new class of small satellites which demonstrate the important commercial benefits of using technologies developed for other purposes by U.S. National Laboratories. The Teledesic satellite architecture, subsystem design features, and new technologies are described. The new Teledesic satellite manufacturing, integration, and test approaches which use modern high volume production techniques and result in surprisingly low space segment costs are discussed. The constellation control and management features and attendant software architecture features are addressed. After briefly discussing the economic and technological impact on the USA commercial space industries of the space communications revolution and such large constellation projects, the paper concludes with observations on the trend toward future system architectures using networked groups of much smaller satellites.

Stuart, James R.↗
NASA NTRS2003

Neural Network and Regression Methods Demonstrated in the Design Optimization of a Subsonic Aircraft

The neural network and regression methods of NASA Glenn Research Center s COMETBOARDS design optimization testbed were used to generate approximate analysis and design models for a subsonic aircraft operating at Mach 0.85 cruise speed. The analytical model is defined by nine design variables: wing aspect ratio, engine thrust, wing area, sweep angle, chord-thickness ratio, turbine temperature, pressure ratio, bypass ratio, fan pressure; and eight response parameters: weight, landing velocity, takeoff and landing field lengths, approach thrust, overall efficiency, and compressor pressure and temperature. The variables were adjusted to optimally balance the engines to the airframe. The solution strategy included a sensitivity model and the soft analysis model. Researchers generated the sensitivity model by training the approximators to predict an optimum design. The trained neural network predicted all response variables, within 5-percent error. This was reduced to 1 percent by the regression method. The soft analysis model was developed to replace aircraft analysis as the reanalyzer in design optimization. Soft models have been generated for a neural network method, a regression method, and a hybrid method obtained by combining the approximators. The performance of the models is graphed for aircraft weight versus thrust as well as for wing area and turbine temperature. The regression method followed the analytical solution with little error. The neural network exhibited 5-percent maximum error over all parameters. Performance of the hybrid method was intermediate in comparison to the individual approximators. Error in the response variable is smaller than that shown in the figure because of a distortion scale factor. The overall performance of the approximators was considered to be satisfactory because aircraft analysis with NASA Langley Research Center s FLOPS (Flight Optimization System) code is a synthesis of diverse disciplines: weight estimation, aerodynamic analysis, engine cycle analysis, propulsion data interpolation, mission performance, airfield length for landing and takeoff, noise footprint, and others.

Hopkins, Dale A.↗
NASA NTRS1991

An architecture for designing fuzzy logic controllers using neural networks

Described here is an architecture for designing fuzzy controllers through a hierarchical process of control rule acquisition and by using special classes of neural network learning techniques. A new method for learning to refine a fuzzy logic controller is introduced. A reinforcement learning technique is used in conjunction with a multi-layer neural network model of a fuzzy controller. The model learns by updating its prediction of the plant's behavior and is related to the Sutton's Temporal Difference (TD) method. The method proposed here has the advantage of using the control knowledge of an experienced operator and fine-tuning it through the process of learning. The approach is applied to a cart-pole balancing system.

Berenji, Hamid R.↗
NASA NTRS1989

DSN radio science system design and testing for Voyager-Neptune encounter

The Deep Space Network (DSN) Radio Science System presently implemented within the Deep Space Network was designed to meet stringent requirements imposed by the demands of the Voyager-Neptune encounter and future missions. One of the initial parameters related to frequency stability is discussed. The requirement, specification, design, and methodology for measuring this parameter are described. A description of special instrumentation that was developed for the test measurements and initial test data resulting from the system tests performed at Canberra, Australia and Usuda, Japan are given.

Ham, N. C.↗
NASA NTRS1992

Neural networks in structural analysis and design - An overview

The present paper provides an overview of the state-of-the-art in the application of neural networks in problems of structural analysis and design, including a survey of published applications in structural engineering. Such applications have included, among others, the use of neural networks in modeling nonlinear analysis of structures, as a rapid reanalysis capability in optimal design, and in developing problem parameter sensitivity of optimal solutions for use in multilevel decomposition based design. While most of the applications reported in the literature have been restricted to the use of the multilayer perceptron architecture and minor variations thereof, other network architectures have also been successfully explored, including the ART network, the counterpropagation network and the Hopfield-Tank model.

Hajela, P.↗
NASA NTRS1992

Full Service ISDN Satellite (FSIS) network model for advanced ISDN satellite design and experiments

The Full Service Integrated Services Digital Network (FSIS) network model for advanced satellite designs describes a model suitable for discrete event simulations. A top down model design uses the Advanced Communications Technology Satellite (ACTS) as its basis. The ACTS and the Interim Service ISDN Satellite (ISIS) perform ISDN protocol analyses and switching decisions in the terrestrial domain, whereas FSIS makes all its analyses and decisions on-board the ISDN satellite.

Pepin, Gerard R.↗
NASA NTRS1993

The GPS Topex/Poseidon precise orbit determination experiment - Implications for design of GPS global networks

Topex/Poseidon, a cooperative satellite mission between United States and France, aims to determine global ocean circulation patterns and to study their influence on world climate through precise measurements of sea surface height above the geoid with an on-board altimeter. To achieve the mission science aims, a goal of 13-cm orbit altitude accuracy was set. Topex/Poseidon includes a Global Positioning System (GPS) precise orbit determination (POD) system that has now demonstrated altitude accuracy better than 5 cm. The GPS POD system includes an on-board GPS receiver and a 6-station GPS global tracking network. This paper reviews early GPS results and discusses multi-mission capabilities available from a future enhanced global GPS network, which would provide ground-based geodetic and atmospheric calibrations needed for NASA deep space missions while also supplying tracking data for future low Earth orbiters. Benefits of the enhanced global GPS network include lower operations costs for deep space tracking and many scientific and societal benefits from the low Earth orbiter missions, including improved understanding of ocean circulation, ocean-weather interactions, the El Nino effect, the Earth thermal balance, and weather forecasting.

Lindqwister, Ulf J.↗
NASA NTRS2019

Quantum Technologies for UAS (QTech)

Recent advances in small Unmanned Aerial System (sUAS) technologies lower the barriers for use by both private and commercial entities. However, these advances are also likely to lead to greater vehicle densities, a more heterogenous mix of vehicles and equipment and greater levels of vehicle autonomy, which can increase the chance for communications disruptions. For the safe and secure operation of these vehicles, it is essential to have a robust communications network. This work is focused on harnessing the power of quantum technologies to enable this robust communications network by: (1) utilizing quantum optimization algorithms to design robust network with routing redundancy that can respond adaptively to dynamically changing real-time environment and disruptions, (2) utilize quantum optimization algorithms resource allocation for detection, localization, and tracking of mobile communication disruption agents and (3) utilize quantum key distribution (QKD) to execute secure key sharing in anti-jamming protocols for secure radio frequency (RF) communication. Efforts to map these quantum optimization algorithms to commercially available quantum annealers and soon to be available general-purpose gate-model quantum hardware architectures will be reviewed, and plans for testing the solutions to these algorithms through indoor sUAS flight tests will be discussed. Lastly, efforts to miniaturize and practically deploy Quantum Key Distribution (QKD) hardware, which could ultimately be used to securely exchange encryption keys, in sUAS networks will be reviewed.

Quantum Computing↗
NASA NTRS1991

Design of multi-layer neural networks for accurate identification of nonlinear mappings

Guidelines for the design of multilayer neural networks for the identification of nonlinear mappings are considered. Since nonlinear mappings can be approximated by a one-hidden-layer neural network, an approach to determine the sufficient number of hidden layer nodes to achieve a global minima of the identification error function is considered.

Teixeira, Edilberto↗
NASA NTRS1998

The P-Mesh: A Commodity-based Scalable Network Architecture for Clusters

We designed a new network architecture, the P-Mesh which combines the scalability and fault resilience of a torus with the performance of a switch. We compare the scalability, performance, and cost of the hub, switch, torus, tree, and P-Mesh architectures. The latter three are capable of scaling to thousands of nodes, however, the torus has severe performance limitations with that many processors. The tree and P-Mesh have similar latency, bandwidth, and bisection bandwidth, but the P-Mesh outperforms the switch architecture (a lower bound for tree performance) on 16-node NAB Parallel Benchmark tests by up to 23%, and costs 40% less. Further, the P-Mesh has better fault resilience characteristics. The P-Mesh architecture trades increased management overhead for lower cost, and is a good bridging technology while the price of tree uplinks is expensive.

Nitzberg, Bill↗
NASA NTRS1989

Design issues in 2-port network models of bilateral remote manipulation

A two-port impedance-network model of a single-degree-of-freedom remote manipulation system in which a human operator at the master port interacts with a task object at the slave port in a remote location is presented. The design of the network involves the selection of feedback gains for the servomechanisms that transmit motion and force information from one port of the two-port to the other in both directions. The proposed methodology allows this selection to be based on both stability requirements and specifications of desired port impedances, given models of the task and the human operator. The resulting design guidelines guarantee stability for any passive task object at the slave port and any passive human impedance at the master port.

Raju, G. Jagannath↗