State criminal justice telecommunications (STACOM). Volume 3: Requirements analysis and design of Texas criminal Justice Telecommunications Network
For abstract, see N78-16218.
Fielding, J. E.↗
SEARCH · Engineering Papers
Results for “network analysis”
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Definition, analysis and development of an optical data distribution network for integrated avionics and control systems. Part 2: Component development and system integration
Fiber optic transmission is emerging as an attractive concept in data distribution onboard civil aircraft. Development of an Optical Data Distribution Network for Integrated Avionics and Control Systems for commercial aircraft will provide a data distribution network that gives freedom from EMI-RFI and ground loop problems, eliminates crosstalk and short circuits, provides protection and immunity from lightning induced transients and give a large bandwidth data transmission capability. In addition there is a potential for significantly reducing the weight and increasing the reliability over conventional data distribution networks. Wavelength Division Multiplexing (WDM) is a candidate method for data communication between the various avionic subsystems. With WDM all systems could conceptually communicate with each other without time sharing and requiring complicated coding schemes for each computer and subsystem to recognize a message. However, the state of the art of optical technology limits the application of fiber optics in advanced integrated avionics and control systems. Therefore, it is necessary to address the architecture for a fiber optics data distribution system for integrated avionics and control systems as well as develop prototype components and systems.
Yen, H. W.↗
Spatial analysis of storm depths from an Arizona raingage network
Eight years of summer rainstorm observations are analyzed by a dense network of 93 raingages operated by the U.S. Department of Agriculture, Agricultural Research Service, in the 150 km Walnut Gulch experimental catchment near Tucson, Arizona. Storms are defined by the total depths collected at each raingage during the noon-to-noon period for which there was depth recorded at any of the gages. For each of the resulting 428 storm days, the gage depths are interpolated onto a dense grid and the resulting random field analyzed to obtain moments, isohyetal plots, spatial correlation function, variance function, and the spatial distribution of storm depth.
Fennessey, N. M.↗
Analysis of adaptive algorithms for an integrated communication network
Techniques were examined that trade communication bandwidth for decreased transmission delays. When the network is lightly used, these schemes attempt to use additional network resources to decrease communication delays. As the network utilization rises, the schemes degrade gracefully, still providing service but with minimal use of the network. Because the schemes use a combination of circuit and packet switching, they should respond to variations in the types and amounts of network traffic. Also, a combination of circuit and packet switching to support the widely varying traffic demands imposed on an integrated network was investigated. The packet switched component is best suited to bursty traffic where some delays in delivery are acceptable. The circuit switched component is reserved for traffic that must meet real time constraints. Selected packet routing algorithms that might be used in an integrated network were simulated. An integrated traffic places widely varying workload demands on a network. Adaptive algorithms were identified, ones that respond to both the transient and evolutionary changes that arise in integrated networks. A new algorithm was developed, hybrid weighted routing, that adapts to workload changes.
Reed, Daniel A.↗
Analysis of exhaustive limited service for token ring networks
Token ring operation is well-understood in the cases of exhaustive, gated, gated limited, and ordinary cyclic service. There is no current data, however, on queueing models for the exhaustive limited service type. This service type differs from the others in that there is a preset maximum (omega) on the number of packets which may be transmitted per token reception, and packets which arrive after token reception may still be transmitted if the preset packet limit has not been reached. Exhaustive limited service is important since it closely approximates a timed token service discipline (the approximation becomes exact if packet lengths are constant). A method for deriving the z-transforms of the distributions of the number of packets present at both token departure and token arrival for a system using exhaustive limited service is presented. This allows for the derivation of a formula for mean queueing delay and queue lengths. The method is theoretically applicable to any omega. Fortunately, as the value of omega becomes large (typically values on the order of omega = 8 are considered large), the exhaustive limited service discipline closely approximates an exhaustive service discipline.
Peden, Jeffery H.↗
An Analysis for the Use of Research and Education Networks and Commercial Network Vendors in Support of Space Based Mission Critical and Non-Critical Networking
Currently, and in the past, dedicated communication circuits and "network services" with very stringent performance requirements are being used to support manned and unmanned mission critical ground operations at GSFC, JSC, MSFC, KSC and other NASA facilities. Because of the evolution of network technology, it is time to investigate using other approaches to providing mission services for space ground operations. The current NASA approach is not in keeping with the evolution of network technologies. In the past decade various research and education networks dedicated to scientific and educational endeavors have emerged, as well as commercial networking providers, that employ advanced networking technologies. These technologies have significantly changed networking in recent years. Significant advances in network routing techniques, various topologies and equipment have made commercial networks very stable and virtually error free. Advances in Dense Wave Division Multiplexing will provide tremendous amounts of bandwidth for the future. The question is: Do these networks, which are controlled and managed centrally, provide a level of service that equals the stringent NASA performance requirements. If they do, what are the implication(s) of using them for critical space based ground operations as they are, without adding high cost contractual performance requirements? A second question is the feasibility of applying the emerging grid technology in space operations. Is it feasible to develop a Space Operations Grid and/or a Space Science Grid? Since these network's connectivity is substantial, both nationally and internationally, development of these sorts of grids may be feasible. The concept of research and education networks has evolved to the international community as well. Currently there are international RENs connecting the US in Chicago to and from Europe, South America, Asia and the Pacific rim, Russia and Canada. And most countries in these areas have their own research and education network as do many states in the USA.
Bradford, Robert N.↗
A Network Based Approach to Data Access, Visualization, Interactive Analysis and Distribution
In today's heterogeneous computing environment of proliferating platforms and operating systems, the Internet, through the World Wide Web (WWW), is becoming the preferred interface to much of the world's archive of digital data.
data access visualization interactive analysis and↗
The Effect of Missing Groups in the Calculation of the Solar Irradiance Deficit: Analysis of the Sunspot Areas from the SOON Network
Sunspot areas are one of the most important indices of solar activity. To obtain an extended time series covering multiple solar cycles one must combine data from different observatories after a proper comparison and calibration of the individual data sets. We compare the daily and group values of sunspot areas provided by the different stations from the Solar Optical Observing Network, SOON, which are determined using similar instruments and techniques. We investigate if there are systematic differences among the stations and whether the differences in the daily values can be attributed to missing groups in the records or errors in the measurements. We find significant differences among the stations of the SOON network in terms of sizes (average daily and group values), quality of observations and coverage (considering number of missing groups and data gaps). Our results indicate that calibration factors for daily values can be used with confidence to combine data sets from different stations. However, for some applications which require the location of the sunspot groups the same correction factors should not be used. We estimate the irradiance deficit due to sunspot through the Photometric Sunspot Index and compare the output from similar data sets to quantify the effect of missing groups. We find differences as high as 150 ppm during the maximum of solar cycle. The effect increases for sunspot groups near the center of the disk accounting for about 80% of the observed differences.
Luis Leuzzi↗
The Space Superhighway: Systems Analysis of an In-Space Logistics Delivery Network
The number of assets in cislunar space is anticipated to dramatically increase in the coming decades. Many of these newer spacecraft are being designed to take advantage of capabilities currently in development like In-Space Servicing Assembly and Manufacturing (ISAM). Additionally, the National Aeronautics and Space Administration (NASA) intends to develop and maintain a human-lunar presence that will then serve as a steppingstone for human missions to Mars. With continued growth in space operations, the combined demand for payload and propellant delivery in cislunar space could exceed 1,000 t annually in the next decade. The Space Superhighway principally consists of a logistics network and is intended to both use and proliferate ISAM in order to meet projected payload demands. Several architecture and vehicle-level trade studies are explored in order to better understand what in-space logistics networks may be feasible. The network consists of commercial launch vehicles, resupply tankers, orbital depots, and in-space tugs. This work specifically analyzes high-level trades such as: launch and in-space vehicle propulsion systems, vehicle size, staging orbit, level of vehicle reuse, reuse method, and propellant management strategy. Each of the trades are analyzed across several destination orbits such as Low-Earth Orbit (LEO) and Near-Rectilinear Halo Orbit (NRHO). Several payload types are also considered such as storable and cryogenic chemical propellants, electric propellants, crew logistics, spares, smallsats, and satellite piece parts.
Daniel J Tiffin↗
Analysis of Traffic Flow in Structured Urban Airspace Networks with MFD-based Feedback Control
This research delves into applying the Macroscopic Fundamental Diagram (MFD) concept to structured airspace networks for comprehensive aggregate modeling and introduces a feedback-based departure function aimed at optimizing traffic flow. Previous studies have rarely examined structured airspace networks featuring non-stationary vehicles through the MFD perspective. We devised a scenario grounded in practical applications, featuring a multi-lane network with explicit lane-changing behavior. The MFD effectively captured the open-loop response, displaying a low-scatter, unimodal curve on the flow versus occupancy plot. Drawing inspiration from the ground transportation ramp-metering strategies, a proportional-integral-based controller was developed. Extensive simulation outcomes suggest that feedback control, informed by MFD, holds significant potential for managing traffic flow in Urban Air Mobility (UAM) environments; a reduction of 80% in the peak number of vehicles in a holding pattern was observed for a slight reduction in throughput in this study.
MFD↗
Analysis of Traffic Flow in Structured Urban Airspace Networks with MFD-based Feedback Control
This research delves into applying the Macroscopic Fundamental Diagram (MFD) concept to structured airspace networks for comprehensive aggregate modeling and introduces a feedback-based departure function aimed at optimizing traffic flow. Previous studies have rarely examined structured airspace networks featuring non-stationary vehicles through the MFD perspective. We devised a scenario grounded in practical applications, featuring a multi-lane network with explicit lane-changing behavior. The MFD effectively captured the open-loop response, displaying a low-scatter, unimodal curve on the flow versus occupancy plot. Drawing inspiration from the ground transportation ramp-metering strategies, a proportional-integral-based controller was developed. Extensive simulation outcomes suggest that feedback control, informed by MFD, holds significant potential for managing traffic flow in Urban Air Mobility (UAM) environments; a reduction of 80% in the peak number of vehicles in a holding pattern was observed for a slight reduction in throughput in this study.
MFD↗
Explaining Neural Network Predictions for Functional Data Using Principal Component Analysis and Feature Importance.
Abstract not provided.
Goode, Katherine Jean↗
Explaining Neural Network Predictions for Functional Data Using Principal Component Analysis and Feature Importance.
Abstract not provided.
Goode, Katherine Jean↗
Techno-Economic Analysis of Blending Hydrogen into Natural Gas Transmission Networks
This presentation provides an overview of NREL's research in the Pipeline Blending CRADA (a HyBlend project) to the 2023 Fuel Cell and Hydrogen Energy Association Seminar.
DIRECT ENERGY CONVERSION,HYDROGEN↗
Sequence-Based Anomaly Detection in Critical Infrastructure Networks
United States critical infrastructure faces new cyber threats from adversarial nation-state actors in the form of malware-free attacks. Traditional cybersecurity techniques use rules-based methods to identify indicators of compromise on networks, often missing these sophisticated attacks. Our approach leverages multiple state of the art machine learning models in a pipeline to identify abnormal network events through sequential analysis. We combine both device and packet-level information into individual events to characterize anomalous network actions. The model is trained and tested on real network traffic from the Idaho National Lab High Performance Computing (HPC) with greater than 98% precision. It is capable of flagging malicious tactics used by adversaries in malware-free attacks, severe changes to the network, and abnormal user activity by network devices.
99 - GENERAL AND MISCELLANEOUS↗
Networks for image acquisition, processing and display
The human visual system comprises layers of networks which sample, process, and code images. Understanding these networks is a valuable means of understanding human vision and of designing autonomous vision systems based on network processing. Ames Research Center has an ongoing program to develop computational models of such networks. The models predict human performance in detection of targets and in discrimination of displayed information. In addition, the models are artificial vision systems sharing properties with biological vision that has been tuned by evolution for high performance. Properties include variable density sampling, noise immunity, multi-resolution coding, and fault-tolerance. The research stresses analysis of noise in visual networks, including sampling, photon, and processing unit noises. Specific accomplishments include: models of sampling array growth with variable density and irregularity comparable to that of the retinal cone mosaic; noise models of networks with signal-dependent and independent noise; models of network connection development for preserving spatial registration and interpolation; multi-resolution encoding models based on hexagonal arrays (HOP transform); and mathematical procedures for simplifying analysis of large networks.
Ahumada, Albert J., Jr.↗
Power Sharing-Based Framework for Allocating Automatic Generation Control in Distributed Energy Resources: Preprint
The recent proliferation of distributed energy resources (DERs) in the power network along with the retirement of conventional generators has made it challenging to regulate system frequency. In this paper, we present a centralized control framework to leverage the potential of DERs in the distribution network in provisioning secondary frequency control services to the grid. The proposed framework is based on network volt-watt sensitivity analysis and takes into account DER operational and network-imposed constraints to allocate the automatic generation control (AGC) request among the aggregated units. The proposed framework was implemented on the IEEE 8500-node test feeder and results were validated against a standard linear programming-based scheme. Numerical results indicate that the proposed framework can successfully utilize the available power production headroom of the network to meet the AGC request while maintaining nodal voltages within acceptable limits.
distributed energy resources↗
System and method for structural characterization of materials by supervised machine learning-based analysis of their spectra
A method of supervised machine learning-based spectrum analysis information, using a neural network trained with spectrum information, to identify a specified feature of a given material, a system for supervised machine learning-based spectrum analysis, and a method of training a neural network to analyze spectrum data. The method of supervised machine learning-base spectrum analysis comprises inputting into the neural network spectrum data obtained from a sample of the given material; and the neural network processing the spectrum data, in accordance with the training of the neural network, and outputting one or more values for the specified feature of the sample of the material. In an embodiment, the training set of data includes x-ray absorption spectroscopy data for the given material. In an embodiment, the training set of data includes electron energy loss spectra (EELS) data.
Frenkel, Anatoly↗