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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1995

Dissipative rendering and neural network control system design

Model-based control system designs are limited by the accuracy of the models of the plant, plant uncertainty, and exogenous signals. Although better models can be obtained with system identification, the models and control designs still have limitations. One approach to reduce the dependency on particular models is to design a set of compensators that will guarantee robust stability to a set of plants. Optimization over the compensator parameters can then be used to get the desired performance. Conservativeness of this approach can be reduced by integrating fundamental properties of the plant models. This is the approach of dissipative control design. Dissipative control designs are based on several variations of the Passivity Theorem, which have been proven for nonlinear/linear and continuous-time/discrete-time systems. These theorems depend not on a specific model of a plant, but on its general dissipative properties. Dissipative control design has found wide applicability in flexible space structures and robotic systems that can be configured to be dissipative. Currently, there is ongoing research to improve the performance of dissipative control designs. For aircraft systems that are not dissipative active control may be used to make them dissipative and then a dissipative control design technique can be used. It is also possible that rendering a system dissipative and dissipative control design may be combined into one step. Furthermore, the transformation of a non-dissipative system to dissipative can be done robustly. One sequential design procedure for finite dimensional linear time-invariant systems has been developed. For nonlinear plants that cannot be controlled adequately with a single linear controller, model-based techniques have additional problems. Nonlinear system identification is still a research topic. Lacking analytical models for model-based design, artificial neural network algorithms have recently received considerable attention. Using their universal approximation property, neural networks have been introduced into nonlinear control designs in several ways. Unfortunately, little work has appeared that analyzes neural network control systems and establishes margins for stability and performance. One approach for this analysis is to set up neural network control systems in the framework presented above. For example, one neural network could be used to render a system to be dissipative, a second strictly dissipative neural network controller could be used to guarantee robust stability.

Gonzalez, Oscar R.↗
NASA NTRS1995

Geophysical phenomena classification by artificial neural networks

Space science information systems involve accessing vast data bases. There is a need for an automatic process by which properties of the whole data set can be assimilated and presented to the user. Where data are in the form of spectrograms, phenomena can be detected by pattern recognition techniques. Presented are the first results obtained by applying unsupervised Artificial Neural Networks (ANN's) to the classification of magnetospheric wave spectra. The networks used here were a simple unsupervised Hamming network run on a PC and a more sophisticated CALM network run on a Sparc workstation. The ANN's were compared in their geophysical data recognition performance. CALM networks offer such qualities as fast learning, superiority in generalizing, the ability to continuously adapt to changes in the pattern set, and the possibility to modularize the network to allow the inter-relation between phenomena and data sets. This work is the first step toward an information system interface being developed at Sussex, the Whole Information System Expert (WISE). Phenomena in the data are automatically identified and provided to the user in the form of a data occurrence morphology, the Whole Information System Data Occurrence Morphology (WISDOM), along with relationships to other parameters and phenomena.

Gough, M. P.↗
NASA NTRS1997

Multiple Hub Network Choice in the Liberalized European Market

A key question that so far has received relatively little attention in the germane literature is that of the changes at various airports as a result of the EU liberalization policies. That is, presently, most major European airports still benefit from the so-called home-carrier phenomenon where the country's publicly or semi-publicly owned carrier uses the country's main airport as its gateway hub and, consequently, the home-carrier is also the principal user of this airport (in terms of proportion of total aircraft movements, number of passengers transported, connections, slots ownership, etc.). The country's main airport has substantially benefited from these monopoly conditions of airline captivity, strongly determined by the bilateral system of international air transport regulation. Therefore, European major airports were used to operate in essentially different markets, compared to the increasingly competitive markets of their home based carriers. This partly explains relative stability of transport volumes and financial results of European major airports compared to the relatively volatile financial results of most European national airlines. However, the liberalization of European aviation is likely to change this situation. Market access is open now to all community carriers, i.e. carriers with majority ownership and effective control in the hands of EU citizens. Ticket prices are free, governments can only intervene in case of dumping or excessive pricing. A community airline can choose its seat in any of the 15 member states. Licensing procedures are harmonized between member states. In the last few months community carriers have had unrestricted route access within the EU. Most probably this development will be extended to countries inside and outside Europe. Last year the European Commission got the mandate to start negotiations with 10 other European countries. In the meantime the EC has also started negotiations with the USA on so-called soft rights. In the meantime, open skies agreements have been concluded between the USA and most of the EU member states to facilitate strategic alliances between airlines of the states involved. As a result of this on-going liberalization the model of the single 'national' carrier using the national home base as its single hub for the designated third, fourth and sixth freedom operations will stepwise disappear. Within the EU the concept of the national carrier has already been replaced by that of the community carrier. State ownership in more and more European carriers is reduced. On the longer run mergers or even bankruptcy will further undermine the "single national carrier - single national hub" model in Europe. In the meantime, strategic alliances between national carriers in Europe will already reduce the airlines' loyalty to a single airport. Profit maximization and accountability to share holders will supersede the loyalty of these newly emerging alliances, probably looking for the opportunities of a multiple hub network to adequately cover the whole European market. As a consequence, some European airports might see a substantial decline in arriving, departing and transfer traffic, thus in revenues and financial solvency, as well as in their connection to other inter-continental and intra-European destinations. At the same time, other airports might realize a significant increase in traffic as they will be sought after by the profit maximizing airlines as their major gateway hubs. Which will be the losing airports and which will be the winning ones? Can airports anticipate the actions of airlines in deregulated markets and utilize policies which will improve their relative position? If so, what should be these anticipatory policies? These questions become the more urgent, since an increasing number of major European airports will be privatized in the near future. Although increasing airport congestion in Europe will also be reflected in a growing demand pressure for airport slots, this is not a guarantee for a stable transport volume growth of individual airports. The more volatile the market is, the more vulnerable privatized airports become. Therefore, the main issue of this study is the analysis of the opportunities of major European airports to become a central hub as a result of the network choices made by the new European airlines in a completely liberalized market. In a previous study (Berechman and de Wit, 1996), we already explored the potential of Amsterdam Airport Schiphol of becoming the major West-European hub, once European aviation markets are deregulated. A major hindrance of that study was the use of a single hub-and-spoke network. For example that model could not analyze the viability of different combinations of European hubs within a multiple hub network of alternative airline alliances. In this study, we have formulated the model of a multi-hub network where two West-European airports are used for inter-continental and intra-European travel to enable a more realistic analysis of hub choice. Like the previous one also this multi-hub model is primarily used to assess the potential ability of Amsterdam Airport Schiphol for becoming a major West-European hub. Thus, in particular, the policy tests focus on this airport in a double hub network.

Berechman, Joseph↗
NASA NTRS1993

Back Propagation Neural Networks for Predicting Ultimate Strengths of Unidirectional Graphite/Epoxy Tensile Specimens

The research presented herein demonstrates the feasibility of predicting ultimate strengths in simple composite structures through a neural network analysis of their acoustic emission (AE) amplitude distribution data. A series of eleven ASTM D-3039 unidirectional graphite/epoxy tensile samples were loaded to failure to generate the amplitude distributions for this analysis. A back propagation neural network was trained to correlate the AE amplitude distribution signatures generated during the first 25% of loading with the ultimate strengths of the samples. The network was trained using two sets of inputs: (1) the statistical parameters obtained from a Weibull distribution fit of the amplitude distribution data, and (2) the event frequency (amplitude) distribution itself. The neural networks were able to predict ultimate strengths with a worst case error of -8.99% for the Weibull modeled amplitude distribution data and 3.74% when the amplitude distribution itself was used to train the network. The principal reason for the improved prediction capability of the latter technique lies in the ability of the neural network to extract subtle features from within the amplitude distribution.

Walker, James L.↗
NASA NTRS1999

Cross-Sensor Calibration of the GAI Long Range Detection Network

The long range component of the North American Lightning Detection Network has been providing experimental data products since July 1996, offering cloud-to-ground lightning coverage throughout the Atlantic and Western Pacific oceans, as well as south to the Intertropical Convergence Zone. The network experiences a strong decrease in detection efficiency with range, which is also significantly modulated by differential propagation under day, night and terminator-crossing conditions. A climatological comparison of total lightning data observed by the Optical Transient Detector (OTD) and CG lightning observed by the long range network is conducted, with strict quality control and allowance for differential network performance before and after the activation of the Canadian Lightning Detection Network. This yields a first-order geographic estimate of long range network detection efficiency and its spatial variability. Intercomparisons are also performed over the continental US, allowing large scale estimates of the midlatitude climatological IC:CG ratio and its possible dependence on latitude.

Boccippio, Dennis J.↗
NASA NTRS1999

Satellite Network Performance Measurements Using Simulated Multi-User Internet Traffic

As a number of diverse satellite systems (both Low Earth Orbit and Geostationary systems) are being designed and deployed, it becomes increasingly important to be able to test these systems under realistic traffic loads. While software simulations can provide valuable input into the system design process, it is crucial that the physical system be tested so that actual network devices can be employed and tuned. These tests need to utilize traffic patterns that closely mirror the expected user load, without the need to actually deploy an end-user network for the test. In this paper, we present trafgen. trafgen uses statistical information about the characteristics of sampled network traffic to emulate the same type of traffic over the test network. This paper compares sampled terrestrial network traffic with emulated satellite network traffic over the NASA ACTS satellite.

Kruse, Hans↗
NASA NTRS2000

A New Neural Network Approach Including First-Guess for Retrieval of Atmospheric Water Vapor, Cloud Liquid Water Path, Surface Temperature and Emissivities Over Land From Satellite Microwave Observations

The analysis of microwave observations over land to determine atmospheric and surface parameters is still limited due to the complexity of the inverse problem. Neural network techniques have already proved successful as the basis of efficient retrieval methods for non-linear cases, however, first-guess estimates, which are used in variational methods to avoid problems of solution non-uniqueness or other forms of solution irregularity, have up to now not been used with neural network methods. In this study, a neural network approach is developed that uses a first-guess. Conceptual bridges are established between the neural network and variational methods. The new neural method retrieves the surface skin temperature, the integrated water vapor content, the cloud liquid water path and the microwave surface emissivities between 19 and 85 GHz over land from SSM/I observations. The retrieval, in parallel, of all these quantities improves the results for consistency reasons. A data base to train the neural network is calculated with a radiative transfer model and a a global collection of coincident surface and atmospheric parameters extracted from the National Center for Environmental Prediction reanalysis, from the International Satellite Cloud Climatology Project data and from microwave emissivity atlases previously calculated. The results of the neural network inversion are very encouraging. The r.m.s. error of the surface temperature retrieval over the globe is 1.3 K in clear sky conditions and 1.6 K in cloudy scenes. Water vapor is retrieved with a r.m.s. error of 3.8 kg/sq m in clear conditions and 4.9 kg/sq m in cloudy situations. The r.m.s. error in cloud liquid water path is 0.08 kg/sq m . The surface emissivities are retrieved with an accuracy of better than 0.008 in clear conditions and 0.010 in cloudy conditions. Microwave land surface temperature retrieval presents a very attractive complement to the infrared estimates in cloudy areas: time record of land surface temperature will be produced.

Aires, F.↗
NASA NTRS2000

Reliability Modeling of Microelectromechanical Systems Using Neural Networks

Microelectromechanical systems (MEMS) are a broad and rapidly expanding field that is currently receiving a great deal of attention because of the potential to significantly improve the ability to sense, analyze, and control a variety of processes, such as heating and ventilation systems, automobiles, medicine, aeronautical flight, military surveillance, weather forecasting, and space exploration. MEMS are very small and are a blend of electrical and mechanical components, with electrical and mechanical systems on one chip. This research establishes reliability estimation and prediction for MEMS devices at the conceptual design phase using neural networks. At the conceptual design phase, before devices are built and tested, traditional methods of quantifying reliability are inadequate because the device is not in existence and cannot be tested to establish the reliability distributions. A novel approach using neural networks is created to predict the overall reliability of a MEMS device based on its components and each component's attributes. The methodology begins with collecting attribute data (fabrication process, physical specifications, operating environment, property characteristics, packaging, etc.) and reliability data for many types of microengines. The data are partitioned into training data (the majority) and validation data (the remainder). A neural network is applied to the training data (both attribute and reliability); the attributes become the system inputs and reliability data (cycles to failure), the system output. After the neural network is trained with sufficient data. the validation data are used to verify the neural networks provided accurate reliability estimates. Now, the reliability of a new proposed MEMS device can be estimated by using the appropriate trained neural networks developed in this work.

Perera. J. Sebastian↗
NASA NTRS2001

Achieving QoS for Aeronautical Telecommunication Networks Over Differentiated Services

Aeronautical Telecommunication Network (ATN) has been developed by the International Civil Aviation Organization to integrate Air-Ground and Ground-Ground data communication for aeronautical applications into a single network serving Air Traffic Control and Aeronautical Operational Communications. To carry time critical information required for aeronautical applications, ATN provides different Quality of Services (QoS) to applications. ATN has therefore, been designed as a stand alone network which implies building an expensive separate network for ATN However, the cost of operating ATN can be reduced if it can be run over a public network such as the Internet. Although the current Internet does not provide QoS the next generation Internet is expected to provide QoS to applications. The objective of this paper is to investigate the possibility of providing QoS to ATN applications when it is run over the next generation Internet. Differentiated Services (DiffServ), one of the protocols proposed for the next generation Internet, will allow network service providers to offer different QoS to customers. Our results show that it is possible to provide QoS to ATN applications when they run over a DiffServ backbone.

Bai, Haowei↗
NASA NTRS1998

A Comparison Between Publish-and-Subscribe and Client-Server Models in Distributed Control System Networks

The BIO-Plex control system requires real-time, flexible, and reliable data delivery. There is no simple "off-the-shelf 'solution. However, several commercial packages will be evaluated using a testbed at ARC for publish- and-subscribe and client-server communication architectures. Point-to-point communication architecture is not suitable for real-time BIO-Plex control system. Client-server architecture provides more flexible data delivery. However, it does not provide direct communication among nodes on the network. Publish-and-subscribe implementation allows direct information exchange among nodes on the net, providing the best time-critical communication. In this work Network Data Delivery Service (NDDS) from Real-Time Innovations, Inc. ARTIE will be used to implement publish-and subscribe architecture. It offers update guarantees and deadlines for real-time data delivery. Bridgestone, a data acquisition and control software package from National Instruments, will be tested for client-server arrangement. A microwave incinerator located at ARC will be instrumented with a fieldbus network of control devices. BridgeVIEW will be used to implement an enterprise server. An enterprise network consisting of several nodes at ARC and a WAN connecting ARC and RISC will then be setup to evaluate proposed control system architectures. Several network configurations will be evaluated for fault tolerance, quality of service, reliability and efficiency. Data acquired from these network evaluation tests will then be used to determine preliminary design criteria for the BIO-Plex distributed control system.

Boulanger, Richard P., Jr.↗
NASA NTRS1998

A More Accurate Characterization of UH-60A Pitch Link Loads Using Neural Networks

A more accurate, neural-network-based characterization of the full-scale UH-60A maximum, vibratory pitch link loads (MXVPLL) was obtained. The MXVPLL data were taken from the NASA/Army UH-60A Airloads Program flight test database. This database includes data from level flights, and both simple and "complex" maneuvers. In the present context, a complex maneuver was defined as one which involved simultaneous, non-zero aircraft angle-of-bank (associated with turns) and aircraft pitch-rate (associated with a pull-up or a push-over). The present approach combines physical insight followed by the neural networks application. Since existing load factors do not represent the above-defined complex maneuver, a new, combined load factor ('p resent-load-factor') was introduced. A back-propagation type of neural network with five inputs and one output was used to characterize the UH-60A MXVPLL. The neural network inputs were as follows: rotor advance ratio, aircraft gross weight, rotor RPM, air density ratio, and the present-load-factor. The neural network output was the maximum, vibratory pitch link load (MXVPLL). It was shown that a more accurate characterization of the full-scale flight test pitch link loads can be obtained by combining physical insight with a neural-network-based approach.

Kottapalli, Sesi↗
NASA NTRS2003

A TDMA Broadcast Satellite/Ground Architecture for the Aeronautical Telecommunications Network

An initial evaluation of a TDMA satellite broadcast architecture with an integrated ground network is proposed in this study as one option for the Aeronautical Telecommunications Network (ATN). The architecture proposed consists of a ground based network that is dedicated to the reception and transmissions of Automatic Dependent Surveillance Broadcast (ADS-B) messages from Mode-S or UAT type systems, along with tracks from primary and secondary surveillance radars. Additionally, the ground network could contain VHF Digital Link Mode 2, 3 or 4 transceivers for the reception and transmissions of Controller-Pilot Data Link Communications (CPDLC) messages and for voice. The second part of the ATN network consists of a broadcast satellite based system that is mainly dedicated for the transmission of surveillance data as well as En-route Flight Information Service Broadcast (FIS-B) to all aircraft. The system proposed integrates those two network to provide a nation wide comprehensive service utilizing near term or existing technologies and hence keeping the economic factor in prospective. The next few sections include a background introduction, the ground subnetwork, the satellite subnetwork, modeling and simulations, and conclusion and recommendations.

Shamma, Mohammed A.↗
NASA NTRS1995

Performance Modeling of Network-Attached Storage Device Based Hierarchical Mass Storage Systems

Network attached storage devices improve I/O performance by separating control and data paths and eliminating host intervention during the data transfer phase. Devices are attached to both a high speed network for data transfer and to a slower network for control messages. Hierarchical mass storage systems use disks to cache the most recently used files and a combination of robotic and manually mounted tapes to store the bulk of the files in the file system. This paper shows how queuing network models can be used to assess the performance of hierarchical mass storage systems that use network attached storage devices as opposed to host attached storage devices. Simulation was used to validate the model. The analytic model presented here can be used, among other things, to evaluate the protocols involved in 1/0 over network attached devices.

Menasce, Daniel A.↗
NASA NTRS2004

The NASA Micro-Pulse Lidar Network (MPLNET): Co-location of Lidars with AERONET

We present the formation of a global-ground based eye-safe lidar network, the NASA Micro-Pulse Lidar Network (MPLNET). The aim of MPLNET is to acquire long-term observations of aerosol and cloud vertical profiles at unique geographic sites within the NASA Aerosol Robotic Network (AERONET). Network growth follows a federated approach, pioneered by AERONET, wherein independent research groups may join MPLNET with their own instrument and site. MPLNET utilizes standard instrumentation and data processing algorithms for efficient network operations and direct comparison of data between each site. The micro-pulse lidar is eye-safe, compact, and commercially available, and most easily allows growth of the network without sacrificing standardized instrumentation gods. Red-time data products (next-day) are available, and include Level 1 daily lidar signal images from the surface to -2Okm, and Level 1.5 aerosol extinction provides at times co-incident with AERONET observations. Testing of our quality assured aerosol extinction products, Level 2, is near completion and data will soon be available. Level 3 products, continuous daylight aerosol extinction profiles, are under development and testing has begun. An overview of h4PL" will be presented. Successful methods of merging standardized lidar operations with AERONET will also be discussed, with the first 4 years of MPLNET results serving as an example.

Welton, Ellsworth J.↗
NASA NTRS2001

A Closed-Loop Optimal Neural-Network Controller to Optimize Rotorcraft Aeromechanical Behaviour: Output from Two Sample Cases - Volume 2

A closed-loop optimal neural-network controller technique was developed to optimize rotorcraft aeromechanical behaviour. This technique utilities a neural-network scheme to provide a general non-linear model of the rotorcraft. A modem constrained optimisation method is used to determine and update the constants in the neural-network plant model as well as to determine the optimal control vector. Current data is read, weighted, and added to a sliding data window. When the specified maximum number of data sets allowed in the data window is exceeded, the oldest data set is and the remaining data sets are re-weighted. This procedure provides at least four additional degrees-of-freedom in addition to the size and geometry of the neural-network itself with which to optimize the overall operation of the controller. These additional degrees-of-freedom are: 1. the maximum length of the sliding data window, 2. the frequency of neural-network updates, 3. the weighting of the individual data sets within the sliding window, and 4. the maximum number of optimisation iterations used for the neural-network updates.

Leyland, Jane Anne↗
NASA NTRS2004

Using an Extended Kalman Filter Learning Algorithm for Feed-Forward Neural Networks to Describe Tracer Correlations

In this study a new extended Kalman filter (EKF) learning algorithm for feed-forward neural networks (FFN) is used. With the EKF approach, the training of the FFN can be seen as state estimation for a non-linear stationary process. The EKF method gives excellent convergence performances provided that there is enough computer core memory and that the machine precision is high. Neural networks are ideally suited to describe the spatial and temporal dependence of tracer-tracer correlations. The neural network performs well even in regions where the correlations are less compact and normally a family of correlation curves would be required. For example, the CH4-N2O correlation can be well described using a neural network trained with the latitude, pressure, time of year, and CH4 volume mixing ratio (v.m.r.). The neural network was able to reproduce the CH4-N2O correlation with a correlation coefficient between simulated and training values of 0.9997. The neural network Fortran code used is available for download.

Lary, David J.↗
NASA NTRS2001

Achieving QoS for Aeronautical Telecommunication Networks over Differentiated Services

Aeronautical Telecommunication Network (ATN) has been developed by the International Civil Aviation Organization to integrate Air-Ground and Ground-Ground data communication for aeronautical applications into a single network serving Air Traffic Control and Aeronautical Operational Communications. To carry time critical information required for aeronautical applications, ATN provides different Quality of Services (QoS) to applications. ATN has therefore, been designed as a standalone network which implies building an expensive separate network for ATN. However, the cost of operating ATN can be reduced if it can be run over a public network such as the Internet. Although the current Internet does not provide QoS, the next generation Internet is expected to provide QoS to applications. The objective of this paper is to investigate the possibility of providing QoS to ATN applications when it is run over the next generation Internet. Differentiated Services (DiffServ), one of the protocols proposed for the next generation Internet, will allow network service providers to offer different QoS to customers. Our results show that it is possible to provide QoS to ATN applications when they run over a DiffServ backbone.

Bai, Haowei↗
NASA NTRS2005

Effective Utilization of Commercial Wireless Networking Technology in Planetary Environments

The purpose of this research is to investigate the use of commercial, off-the-shelf wireless networking technology in planetary exploration applications involving rovers and sensor webs. The three objectives of this research project are to: 1) simulate the radio frequency environment of proposed landing sites on Mars using actual topographic data, 2) analyze the performance of current wireless networking standards in the simulated radio frequency environment, and 3) propose modifications to the standards for more efficient utilization. In this annual report, we present our results for the second year of research. During this year, the effort has focussed on the second objective of analyzing the performance of the IEEE 802.11a and IEEE 802.1lb wireless networking standards in the simulated radio frequency environment of Mars. The approach builds upon our previous results which deterministically modelled the RF environment at selected sites on Mars using high-resolution topographical data. These results provide critical information regarding antenna coverage patterns, maximum link distances, effects of surface clutter, and multipath effects. Using these previous results, the physical layer of these wireless networking standards has now been simulated and analyzed in the Martian environment. We are looking to extending these results to the and medium access layer next. Our results give us critical information regarding the performance (data rates, packet error rates, link distances, etc.) of IEEE 802.1 la/b wireless networks. This information enables a critical examination of how these wireless networks may be utilized in future Mars missions and how they may be possibly modified for more optimal usage.

Caulev, Michael↗