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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

NCCDS performance model

The NASA/GSFC Network Control Center (NCC) provides communication services between ground facilities and spacecraft missions in near-earth orbit that use the Space Network. The NCC Data System (NCCDS) provides computational support and is expected to be highly utilized by the service requests needed in the future years. A performance model of the NCCDS has been developed to assess the future workload and possible enhancements. The model computes message volumes from mission request profiles and SN resource levels and generates the loads for NCCDS configurations as a function of operational scenarios and processing activities. The model has been calibrated using the results of benchmarks performed on the operational NCCDS facility and used to assess some future SN service request scenarios.

Richmond, Eric↗
NASA NTRS1991

TCP Packet Trace Analysis

Examination of a trace of packets collected from the network is often the only method available for diagnosing protocol performance problems in computer networks. This thesis explores the use of packet traces to diagnose performance problems of the transport protocol TCP. Unfortunately, manual examination of these traces can be so tedious that effective analysis is not possible. The primary contribution of this thesis is a graphical method of displaying the packet trace which greatly reduce, the tediousness of examining a packet trace. The graphical method is demonstrated by the examination of some packet traces of typical TCP connections. The performance of two different implementations of TCP sending data across a particular network path is compared. Traces many thousands of packets long are used to demonstrate how effectively the graphical method simplifies examination of long complicated traces. In the comparison of the two TCP implementations, the burstiness of the TCP transmitter appeared to be related to the achieved throughput. A method of quantifying this burstiness is presented and its possible relevance to understanding the performance of TCP is discussed.

Shepard, Timothy J.↗
NASA NTRS2010

Spacecraft Multiple Array Communication System Performance Analysis

The Communication Systems Simulation Laboratory (CSSL) at the NASA Johnson Space Center is tasked to perform spacecraft and ground network communication system simulations, design validation, and performance verification. The CSSL has developed simulation tools that model spacecraft communication systems and the space and ground environment in which the tools operate. In this paper, a spacecraft communication system with multiple arrays is simulated. Multiple array combined technique is used to increase the radio frequency coverage and data rate performance. The technique is to achieve phase coherence among the phased arrays to combine the signals at the targeting receiver constructively. There are many technical challenges in spacecraft integration with a high transmit power communication system. The array combining technique can improve the communication system data rate and coverage performances without increasing the system transmit power requirements. Example simulation results indicate significant performance improvement can be achieved with phase coherence implementation.

Hwu, Shian U.↗
NASA NTRS1990

Evaluating scheduling algorithms for traffic with heterogeneous performance objectives

Two types of network traffic are considered: traffic with deadlines, for which the most important performance objective is based on loss rate, and packets without deadlines, for which the most important performance objective is based on mean delay. An optimal scheduling algorithm is presented to minimize weighted loss rate and weighted mean delay in the queues that form at the switches and at the network access points of a packet-switched network, where weights reflect the relative importance of packets. Although not practical for implementation, the algorithm is intended as a standard for the comparison of the performance of other scheduling algorithms. The algorithm is more general and lower computational complexity than previously published algorithms, enabling performance evaluation of some important scenarios that could not previously have been considered. Using the optimal performance results of this algorithm, the performance of the first-come-first-served, static priority, and earliest deadline first scheduling algorithms is evaluated. The results suggest that network efficiency could be improved by using a more sophisticated heuristic scheduling algorithm rather than one of the aforementioned algorithms.

Peha, Jon M.↗
NASA NTRS2019

Complex Dynamics of Air Traffic Flow

Air traffic in the United States has continued to grow at a steady pace since 1980, except for a dip immediately after the tragic events of September 11, 2001. There are different growth scenarios associated both with the magnitude and the composition of the future air traffic. The Terminal Area Forecast (TAF), prepared every year by the FAA, projects the growth of traffic in the United States. Both Boeing and Airbus publish market outlooks for air travel annually. Although predicting the future growth of traffic is difficult, there are two significant trends: heavily congested major airports continue to see an increase in traffic, and the emergence of regional jets and other smaller aircraft with fewer passengers operating directly between non-major airports. The interaction between air traffic demand and the ability of the system to provide the necessary airport and airspace resources can be modeled as a network. The size of the resulting network varies depending on the choice of its nodes. It would be useful to understand the properties of this network to guide future design and development. Many questions, such as the growth of delay with increasing traffic demand and impact of the en route weather on future air traffic, require a systematic understanding of the properties of the air traffic network. There has been a major advance in the understanding of the behavior of networks with a large number of components. Several theories have been advanced about the evolution of large biological and engineering networks by authors in diversified disciplines like physics, mathematics, biology and computer science. Several networks exhibit a scale-free property in the sense that the probabilistic distribution of their nodes as a function of connections decreases slower than an exponential. These networks are characterized by the fact that a small number of components have a disproportionate influence on the performance of the network. Scale-free networks are tolerant to random failure of components, but are vulnerable to selective attack on components. This paper examines two network representations for the baseline air traffic system. A network defined with the 40 major airports as nodes and with standard flight routes as links has a characteristic scale: all nodes have 60 or more links and no node has more than 460 links. Another network is defined with baseline aircraft routing structure exhibits an exponentially truncated scale-free behavior. Its degree ranges from 2 connections to 2900 connections, and 225 nodes have more than 250 connections. Furthermore, those high-degree nodes are homogeneously distributed in the airspace. A consequence of this scale-free behavior is that the random loss of a single node has little impact, but the loss of multiple high-degree nodes (such as occurs during major storms in busy airspace) can adversely impact the system. Two future scenarios of air traffic growth are used to predict the growth of air traffic in the United States. It is shown that a three-times growth in the overall traffic may result in a ten-times impact on the density of traffic in certain parts of the United States.

Scale-free Networks↗
NASA NTRS1993

Cost and reliability study for a large array of small reflector antennas for JPL/NASA Deep Space Network (DSN)

A study performed to estimate the cost of an array of small aperture reflector antennas to be used instead of or in conjunction with the current large reflector antennas of the JPL/NASA Deep Space Network (DSN) is described. The arrays are used for servicing present and future NASA missions that involve smaller spacecraft with limited power and smaller, lower-gain antennas. The advantages of the array configuration in terms of cost and reliability are discussed. A probabilistic determination of the reliability and availability of the array as a function of the number of array elements and the availability of individual array elements is made. The impact of additional marginal elements on the operational availability of the array is studied. Parametric cost and reliability plots are presented and directions for further investigation are outlined.

Jamnejad, Vahraz↗
NASA NTRS1994

Mobile Computing for Aerospace Applications

The use of commercial computer technology in specific aerospace mission applications can reduce the cost and project cycle time required for the development of special-purpose computer systems. Additionally, the pace of technological innovation in the commercial market has made new computer capabilities available for demonstrations and flight tests. Three areas of research and development being explored by the Portable Computer Technology Project at NASA Ames Research Center are the application of commercial client/server network computing solutions to crew support and payload operations, the analysis of requirements for portable computing devices, and testing of wireless data communication links as extensions to the wired network. This paper will present computer architectural solutions to portable workstation design including the use of standard interfaces, advanced flat-panel displays and network configurations incorporating both wired and wireless transmission media. It will describe the design tradeoffs used in selecting high-performance processors and memories, interfaces for communication and peripheral control, and high resolution displays. The packaging issues for safe and reliable operation aboard spacecraft and aircraft are presented. The current status of wireless data links for portable computers is discussed from a system design perspective. An end-to-end data flow model for payload science operations from the experiment flight rack to the principal investigator is analyzed using capabilities provided by the new generation of computer products. A future flight experiment on-board the Russian MIR space station will be described in detail including system configuration and function, the characteristics of the spacecraft operating environment, the flight qualification measures needed for safety review, and the specifications of the computing devices to be used in the experiment. The software architecture chosen shall be presented. An analysis of the performance characteristics of wireless data links in the spacecraft environment will be discussed. Network performance and operation will be modeled and preliminary test results presented. A crew support application will be demonstrated in conjunction with the network metrics experiment.

Alena, Richard↗
NASA NTRS1992

Neural networks application to divergence-based passive ranging

The purpose of this report is to summarize the state of knowledge and outline the planned work in divergence-based/neural networks approach to the problem of passive ranging derived from optical flow. Work in this and closely related areas is reviewed in order to provide the necessary background for further developments. New ideas about devising a monocular passive-ranging system are then introduced. It is shown that image-plan divergence is independent of image-plan location with respect to the focus of expansion and of camera maneuvers because it directly measures the object's expansion which, in turn, is related to the time-to-collision. Thus, a divergence-based method has the potential of providing a reliable range complementing other monocular passive-ranging methods which encounter difficulties in image areas close to the focus of expansion. Image-plan divergence can be thought of as some spatial/temporal pattern. A neural network realization was chosen for this task because neural networks have generally performed well in various other pattern recognition applications. The main goal of this work is to teach a neural network to derive the divergence from the imagery.

Barniv, Yair↗
NASA NTRS2014

EDSN Development Lessons Learned

The Edison Demonstration of Smallsat Networks (EDSN) is a technology demonstration mission that provides a proof of concept for a constellation or swarm of satellites performing coordinated activities. Networked swarms of small spacecraft will open new horizons in astronomy, Earth observations and solar physics. Their range of applications include the formation of synthetic aperture radars for Earth sensing systems, large aperture observatories for next generation telescopes and the collection of spatially distributed measurements of time varying systems, probing the Earths magnetosphere, Earth-Sun interactions and the Earths geopotential. EDSN is a swarm of eight 1.5U Cubesats with crosslink, downlink and science collection capabilities developed by the NASA Ames Research Center under the Small Spacecraft Technology Program (SSTP) within the NASA Space Technology Mission Directorate (STMD). This paper describes the concept of operations of the mission and planned scientific measurements. The development of the 8 satellites for EDSN necessitated the fabrication of prototypes, Flatsats and a total of 16 satellites to support the concurrent engineering and rapid development. This paper has a specific focus on the development, integration and testing of a large number of units including the lessons learned throughout the project development.

Technology Demonstration↗
NASA NTRS1984

Performance and cost of energy transport and storage systems for dish applications using reversible chemical reactions

The use of reversible chemical reactions for energy transport and storage for parabolic dish networks is considered. Performance and cost characteristics are estimated for systems using three reactions (sulfur-trioxide decomposition, steam reforming of methane, and carbon-dioxide reforming of methane). Systems are considered with and without storage, and in several energy-delivery configurations that give different profiles of energy delivered versus temperature. Cost estimates are derived assuming the use of metal components and of advanced ceramics. (The latter reduces the costs by three- to five-fold). The process that led to the selection of the three reactions is described, and the effects of varying temperatures, pressures, and heat exchanger sizes are addressed. A state-of-the-art survey was performed as part of this study. As a result of this survey, it appears that formidable technical risks exist for any attempt to implement the systems analyzed in this study, especially in the area of reactor design and performance. The behavior of all components and complete systems under thermal energy transients is very poorly understood. This study indicates that thermochemical storage systems that store reactants as liquids have efficiencies below 60%, which is in agreement with the findings of earlier investigators.

Schredder, J. M.↗
NASA NTRS1999

Classification of ion mobility spectra by functional groups using neural networks

Neural networks were trained using whole ion mobility spectra from a standardized database of 3137 spectra for 204 chemicals at various concentrations. Performance of the network was measured by the success of classification into ten chemical classes. Eleven stages for evaluation of spectra and of spectral pre-processing were employed and minimums established for response thresholds and spectral purity. After optimization of the database, network, and pre-processing routines, the fraction of successful classifications by functional group was 0.91 throughout a range of concentrations. Network classification relied on a combination of features, including drift times, number of peaks, relative intensities, and other factors apparently including peak shape. The network was opportunistic, exploiting different features within different chemical classes. Application of neural networks in a two-tier design where chemicals were first identified by class and then individually eliminated all but one false positive out of 161 test spectra. These findings establish that ion mobility spectra, even with low resolution instrumentation, contain sufficient detail to permit the development of automated identification systems.

Non-NASA Center↗
NASA NTRS1968

Correction for losses in optical birefringent networks, a concept

Technique determines the effects of losses upon the performance of a birefringent network and shows how the desired amplitude transmittance of the network may be corrected /or predistorted/, prior to synthesizing the birefringent network, to prevent the effects of crystal losses.

Amman, E. O.↗
NASA NTRS1992

Antenna analysis using neural networks

Conventional computing schemes have long been used to analyze problems in electromagnetics (EM). The vast majority of EM applications require computationally intensive algorithms involving numerical integration and solutions to large systems of equations. The feasibility of using neural network computing algorithms for antenna analysis is investigated. The ultimate goal is to use a trained neural network algorithm to reduce the computational demands of existing reflector surface error compensation techniques. Neural networks are computational algorithms based on neurobiological systems. Neural nets consist of massively parallel interconnected nonlinear computational elements. They are often employed in pattern recognition and image processing problems. Recently, neural network analysis has been applied in the electromagnetics area for the design of frequency selective surfaces and beam forming networks. The backpropagation training algorithm was employed to simulate classical antenna array synthesis techniques. The Woodward-Lawson (W-L) and Dolph-Chebyshev (D-C) array pattern synthesis techniques were used to train the neural network. The inputs to the network were samples of the desired synthesis pattern. The outputs are the array element excitations required to synthesize the desired pattern. Once trained, the network is used to simulate the W-L or D-C techniques. Various sector patterns and cosecant-type patterns (27 total) generated using W-L synthesis were used to train the network. Desired pattern samples were then fed to the neural network. The outputs of the network were the simulated W-L excitations. A 20 element linear array was used. There were 41 input pattern samples with 40 output excitations (20 real parts, 20 imaginary). A comparison between the simulated and actual W-L techniques is shown for a triangular-shaped pattern. Dolph-Chebyshev is a different class of synthesis technique in that D-C is used for side lobe control as opposed to pattern shaping. The interesting thing about D-C synthesis is that the side lobes have the same amplitude. Five-element arrays were used. Again, 41 pattern samples were used for the input. Nine actual D-C patterns ranging from -10 dB to -30 dB side lobe levels were used to train the network. A comparison between simulated and actual D-C techniques for a pattern with -22 dB side lobe level is shown. The goal for this research was to evaluate the performance of neural network computing with antennas. Future applications will employ the backpropagation training algorithm to drastically reduce the computational complexity involved in performing EM compensation for surface errors in large space reflector antennas.

Smith, William T.↗
NASA NTRSDate not supplied

INSPiRE – An Approach to Mission Quality Management using Network Slicing for Space Applications

Managing traffic between the Earth-Moon and Earth-Mars is a complex process requiring significant investment in resources and expertise at NASA. INSPiRE improves the performance of space networks by enabling a dynamic re-configuration process that works for any mixed topology over a heterogeneous and multi-vendor network. To achieve the desired functionality, INSPiRE incorporates a set of algorithms, machine learning processes, and policy inference to handle unpredictable, disruptive events. INSPiRE draws parallels from the current notion of the 3GPP (5G and beyond) Network Slicing approach, where the same physical network divides into several virtual networks, and for each of these virtual networks, there is a guaranteed Quality of Service for the missions that they serve.

cognitive communications↗
NASA NTRS2002

Multipoint sensing by intelligent collectives

Many remote sensing applications require that multiple sensors collect data simultaneously at spatially distributed locations and their information combined in order to characterize the phenomena of interest. Several basic classes of such multipoint measurement systems may be identified. For each, centralized methods exist for combining the raw data from the various sensors. However, recent advancements have given rise to small, integrated nodes comprised of one or more miniaturized sensors, processor, wireless communications capability and power supplies. Collections of these may be deployed and self-organized into intelligent sensor networks capable of performing cooperative signal processing locally, thereby providing substantial benefits.

multipoint measurement sensor networks↗
NASA NTRS1985

System Analysis for the Huntsville Operation Support Center, Distributed Computer System

HOSC as a distributed computing system, is responsible for data acquisition and analysis during Space Shuttle operations. HOSC also provides computing services for Marshall Space Flight Center's nonmission activities. As mission and nonmission activities change, so do the support functions of HOSC change, demonstrating the need for some method of simulating activity at HOSC in various configurations. The simulation developed in this work primarily models the HYPERchannel network. The model simulates the activity of a steady state network, reporting statistics such as, transmitted bits, collision statistics, frame sequences transmitted, and average message delay. These statistics are used to evaluate such performance indicators as throughout, utilization, and delay. Thus the overall performance of the network is evaluated, as well as predicting possible overload conditions.

Ingels, F. M.↗
NASA NTRS1988

A fiber optic tactical voice/data network based on FDDI

An asynchronous high-speed fiber optic local area network is described that supports ordinary data packet traffic simultaneously with synchronous Tl voice traffic over a common FDDI token ring channel. A voice interface module was developed that parses, buffers, and resynchronizes the voice data to the packet network. The technique is general, however, and can be applied to any deterministic class of networks, including multi-tier backbones. A conventional single token access protocol was employed at the lowest layer, with fixed packet sizes for voice and variable for data. In addition, the higher layer packet data protocols are allowed to operate independently of those for the voice thereby permitting great flexibility in reconfiguring the network. Voice call setup and switching functions were performed external to the network with PABX equipment.

Bergman, L. A.↗