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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 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
NASA NTRS1979

SAINT: A combined simulation language for modeling man-machine systems

SAINT (Systems Analysis of Integrated Networks of Tasks) is a network modeling and simulation technique for design and analysis of complex man machine systems. SAINT provides the conceptual framework for representing systems that consist of discrete task elements, continuous state variables, and interactions between them. It also provides a mechanism for combining human performance models and dynamic system behaviors in a single modeling structure. The SAINT technique is described and applications of the SAINT are discussed.

Seifert, D. J.↗
NASA NTRS1991

Terminal Attractors In Neural Networks

Neural networks made to "learn" faster. Report presents theoretical study of terminal attractors in neural networks. Includes systematic analysis of applications to activation dynamics of neural networks.

Zak, Michail A.↗
NASA NTRS1995

Linear and nonlinear trending and prediction for AVHRR time series data

The variability of AVHRR calibration coefficient in time was analyzed using algorithms of linear and non-linear time series analysis. Specifically we have used the spline trend modeling, autoregressive process analysis, incremental neural network learning algorithm and redundancy functional testing. The analysis performed on available AVHRR data sets revealed that (1) the calibration data have nonlinear dependencies, (2) the calibration data depend strongly on the target temperature, (3) both calibration coefficients and the temperature time series can be modeled, in the first approximation, as autonomous dynamical systems, (4) the high frequency residuals of the analyzed data sets can be best modeled as an autoregressive process of the 10th degree. We have dealt with a nonlinear identification problem and the problem of noise filtering (data smoothing). The system identification and filtering are significant problems for AVHRR data sets. The algorithms outlined in this study can be used for the future EOS missions. Prediction and smoothing algorithms for time series of calibration data provide a functional characterization of the data. Those algorithms can be particularly useful when calibration data are incomplete or sparse.

Smid, J.↗
NASA NTRS1991

Multi-channel holographic birfurcative neural network system for real-time adaptive EOS data analysis

Viewgraphs on multi-channel holographic bifurcative neural network system for real-time adaptive Earth Observing System (EOS) data analysis are presented. The objective is to research and develop an optical bifurcating neuromorphic pattern recognition system for making optical data array comparisons and to evaluate the use of the system for EOS data classification, reduction, analysis, and other applications.

Liu, Hua-Kuang↗
NASA NTRSDate not supplied

Refined Analysis of CO2 Emissions in Urban Air Mobility Networks

In this study, we examine the environmental impact of Urban Air Mobility (UAM) operations as measured via carbon dioxide (CO2) emissions by leveraging a computational model from previous studies that has been refined and expanded. Several scenarios are examined in which total transportation emissions for a representative day in a metro area are distributed differently among vehicle types and transportation modes. Specifically, we investigate the use of electric air vehicles in a UAM network; the increasing presence of electric ground vehicles for ground transportation; the impacts from implementing ridesharing in the UAM mode; and the effects of varying the electricity grid emissions. Results for a case study in the Chicago, IL metro area indicate that incorporating electric ground vehicles and UAM ridesharing can both lead to reduced CO2 emissions. These preliminary results indicate that carbon emissions from a UAM system leveraging ridesharing and all-electric aircraft may not be a practical operational limit on UAM, though further improvements to the modeling are warranted.

advanced air mobility↗
NASA NTRSDate not supplied

Refined Analysis of CO2 Emissions in Urban Air Mobility Networks

In this study, we examine the environmental impact of Urban Air Mobility (UAM) operations as measured via carbon dioxide (CO2) emissions by leveraging a computational model from previous studies that has been refined and expanded. Several scenarios are examined in which total transportation emissions for a representative day in a metro area are distributed differently among vehicle types and transportation modes. Specifically, we investigate the use of electric air vehicles in a UAM network; the increasing presence of electric ground vehicles for ground transportation; the impacts from implementing ridesharing in the UAM mode; and the effects of varying the electricity grid emissions. Results for a case study in the Chicago, IL metro area indicate that incorporating electric ground vehicles and UAM ridesharing can both lead to reduced CO2 emissions. These preliminary results indicate that carbon emissions from a UAM system leveraging ridesharing and all-electric aircraft may not be a practical operational limit on UAM, though further improvements to the modeling are warranted.

advanced air mobility↗
NASA NTRS1992

An extended abstract: A heuristic repair method for constraint-satisfaction and scheduling problems

The work described in this paper was inspired by a surprisingly effective neural network developed for scheduling astronomical observations on the Hubble Space Telescope. Our heuristic constraint satisfaction problem (CSP) method was distilled from an analysis of the network. In the process of carrying out the analysis, we discovered that the effectiveness of the network has little to do with its connectionist implementation. Furthermore, the ideas employed in the network can be implemented very efficiently within a symbolic CSP framework. The symbolic implementation is extremely simple. It also has the advantage that several different search strategies can be employed, although we have found that hill-climbing methods are particularly well-suited for the applications that we have investigated. We begin the paper with a brief review of the neural network. Following this, we describe our symbolic method for heuristic repair.

Minton, Steven↗
NASA NTRS1991

Smoothed perturbation analysis algorithms for estimating the derivatives of occupancy-related functions in serial queueing networks

The authors present smoothed perturbation analysis (SPA) estimators for the derivative of a number of occupancy-related functions in serial queuing networks with finite buffer spaces. The functions are the average number of customers at a network as seen by an arrival, the probability that a customer is blocked at a particular queue, and the probability that a customer leaves a queue empty. In all three cases, the variable is a parameter of the distribution of service times at one of the queues. The derivative estimators considered are very simple and flexible, and they easily lend themselves to analysis of unbiasedness. Unlike most of the established SPA estimators, the present ones are not based on the computation of hazard rates.

Wardi, Y.↗
NASA NTRS1973

NASCOM network: Ground communications reliability report

A reliability performance analysis of the NASCOM Network circuits is reported. Network performance narrative summary is presented to include significant changes in circuit configurations, current figures, and trends in each trouble category with notable circuit totals specified. Lost time and interruption tables listing circuits which were affected by outages showing their totals category are submitted. A special analysis of circuits with low reliabilities is developed with tables depicting the performance and graphs for individual reliabilities.

Source record↗
NASA NTRS1993

Using neural networks to assist in OPAD data analysis

The space shuttle main engine (SSME) became the subject of plume emission spectroscopy in 1986 when researchers from NASA-Marshall Space Flight Center (MSFC), Arnold Engineering Development Center (AEDC), and Rocketdyne went to the SSME test stands at the NASA-Stennis Space Center and at Rocketdyne's Santa Susan Field Laboratory to optically observe the plume. Since then, plume spectral acquisitions have recorded many nominal tests and the qualitative spectral features of the SSME plume are now well established. Significant discoveries made with both wide-band and narrow-band plume emission spectroscopy systems led MSFC to promote the Optical Plume Anomaly Detection (OPAD) program with a goal of instrumenting all SSME test stands with customized spectrometer systems. A prototype OPAD system is now installed on the SSME Technology Test Bed (TTB) at MSFC. The OPAD system instrumentation consists of a broad-band, optical multiple-channel analyzer (OMA) and a narrow-band device called a polychrometer. The OMA is a high-resolution (1.5-2.0 Angstroms) 'super-spectrometer' covering the near-ultraviolet to near-infrared waveband (2800-7400 Angstroms), providing two scans per second. The polychrometer consists of sixteen narrow-band radiometers: fourteen monitoring discrete wavelengths of health and condition monitoring elements and two dedicated to monitoring background emissions. All sixteen channels are capable of providing 500 samples per second. To date, the prototype OPAD system has been used during 43 SSME firings on the TTB, collecting well over 250 megabytes of plume spectral data. One goal of OPAD data analysis is to determine interatively with the help of a computer code, SPECTRA4, developed at AEDC. Experience has shown that iteration with SPECTRA4 is an incredibly labor intensive task and not one to be performed by band. What is really needed is the 'inverse' of SPECTRA4 but the mathematical model for this inverse mapping is tenuous at best. However, the robustness of PSECTRA4 run in the 'forward' direction means that accurate input/output mappings can be obtained. If the mappings were inverted (i.e., input becomes output and output becomes input) then an 'inverse' of SPECTRA4 would be at hand but the 'model' would be specific to the data utilized and would in no way be general. Building a generalized model based upon known input/output mappings while ignoring the details of the governing physical model is possible through the use of a neural network. The research investigation described involves the development of a neural network to provide a generalized 'inverse' of SPECTRA4. The objectives of the research were to design an appropriate neural network architecture, train the network, and then evaluate its performance.

Whitaker, Kevin W.↗
NASA NTRS1992

Spreadsheet Analysis Of Queuing In A Computer Network

Method of analyzing responses of computer network based on simple queuing-theory mathmatical models via spreadsheet program. Effects of variations in traffic, capacities of channels, and message protocols assessed.

Galant, David C.↗
NASA NTRS1991

Analysis of NASA communications (Nascom) II network protocols and performance

The NASA Communications (Nascom) Division of the Mission Operations and Data Systems Directorate is to undertake a major initiative to develop the Nascom II (NII) network to achieve its long-range service objectives for operational data transport to support the Space Station Freedom Program, the Earth Observing System, and other projects. NII is the Nascom ground communications network being developed to accommodate the operational traffic of the mid-1990s and beyond. The authors describe various baseline protocol architectures based on current and evolving technologies. They address the internetworking issues suggested for reliable transfer of data over heterogeneous segments. They also describe the NII architecture, topology, system components, and services. A comparative evaluation of the current and evolving technologies was made, and suggestions for further study are described. It is shown that the direction of the NII configuration and the subsystem component design will clearly depend on the advances made in the area of broadband integrated services.

Omidyar, Guy C.↗