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At least 829 records · Page 46

A seven patch hexagonal CP subarray with a CPW/stripline feed network

A seven element microstrip subarray of hexagonal geometry were designed and tested at S-band frequencies. The microstrip patch antenna is excited at a single feed position using a direct probe type connection to generate a circularly polarized wave. The RF power is coupled to these feed positions by a novel coplanar waveguide/stripline feeding network. The subarray architecture and the feed network are described in detail. The measured results include the feed network characterization as well as the radiation patterns of the subarray.

Simons, R. N.↗

Identification and interpretation of patterns in rocket engine data: Artificial intelligence and neural network approaches

This paper describes an expert system which is designed to perform automatic data analysis, identify anomalous events, and determine the characteristic features of these events. We have employed both artificial intelligence and neural net approaches in the design of this expert system. The artificial intelligence approach is useful because it provides (1) the use of human experts' knowledge of sensor behavior and faulty engine conditions in interpreting data; (2) the use of engine design knowledge and physical sensor locations in establishing relationships among the events of multiple sensors; (3) the use of stored analysis of past data of faulty engine conditions; and (4) the use of knowledge-based reasoning in distinguishing sensor failure from actual faults. The neural network approach appears promising because neural nets (1) can be trained on extremely noisy data and produce classifications which are more robust under noisy conditions than other classification techniques; (2) avoid the necessity of noise removal by digital filtering and therefore avoid the need to make assumptions about frequency bands or other signal characteristics of anomalous behavior; (3) can, in effect, generate their own feature detectors based on the characteristics of the sensor data used in training; and (4) are inherently parallel and therefore are potentially implementable in special-purpose parallel hardware.

Ali, Moonis↗

X-band preamplifier filter

A low-loss bandstop filter designed and developed for the Deep Space Network's 34-meter high-efficiency antennas is described. The filter is used for protection of the X-band traveling wave masers from the 20-kW transmitter signal. A combination of empirical and theoretical techniques was employed as well as computer simulation to verify the design before fabrication.

Manshadi, F.↗

Structural fatigue in the 34-meter HA-dec antennas

Three 26-m hour-angle/declination (HA-dec) antennas, designed for a life span of 20 years, were built in the early 1960s for the NASA Deep Space Network. After 16 years the antennas were upgraded. The design required a structural weight increase of about 50 percent in both the HA and dec structures to achieve the desired improvements. The fatigue caused by the resulting stress-reversal conditions is discussed. The structural failures and their analyses are described.

Van Hek, Ronald A.↗

Verification and Validation of Adaptive and Intelligent Systems with Flight Test Results

F-15 IFCS project goals are: a) Demonstrate Control Approaches that can Efficiently Optimize Aircraft Performance in both Normal and Failure Conditions [A] & [B] failures. b) Advance Neural Network-Based Flight Control Technology for New Aerospace Systems Designs with a Pilot in the Loop. Gen II objectives include; a) Implement and Fly a Direct Adaptive Neural Network Based Flight Controller; b) Demonstrate the Ability of the System to Adapt to Simulated System Failures: 1) Suppress Transients Associated with Failure; 2) Re-Establish Sufficient Control and Handling of Vehicle for Safe Recovery. c) Provide Flight Experience for Development of Verification and Validation Processes for Flight Critical Neural Network Software.

Burken, John J.↗

Systems engineering technology for networks

The report summarizes research pursued within the Systems Engineering Design Laboratory at Virginia Polytechnic Institute and State University between May 16, 1993 and January 31, 1994. The project was proposed in cooperation with the Computational Science and Engineering Research Center at Howard University. Its purpose was to investigate emerging systems engineering tools and their applicability in analyzing the NASA Network Control Center (NCC) on the basis of metrics and measures.

Source record↗

NATO Human View Architecture and Human Networks

The NATO Human View is a system architectural viewpoint that focuses on the human as part of a system. Its purpose is to capture the human requirements and to inform on how the human impacts the system design. The viewpoint contains seven static models that include different aspects of the human element, such as roles, tasks, constraints, training and metrics. It also includes a Human Dynamics component to perform simulations of the human system under design. One of the static models, termed Human Networks, focuses on the human-to-human communication patterns that occur as a result of ad hoc or deliberate team formation, especially teams distributed across space and time. Parameters of human teams that effect system performance can be captured in this model. Human centered aspects of networks, such as differences in operational tempo (sense of urgency), priorities (common goal), and team history (knowledge of the other team members), can be incorporated. The information captured in the Human Network static model can then be included in the Human Dynamics component so that the impact of distributed teams is represented in the simulation. As the NATO militaries transform to a more networked force, the Human View architecture is an important tool that can be used to make recommendations on the proper mix of technological innovations and human interactions.

Handley, Holly A. H.↗

Using neural networks and Dyna algorithm for integrated planning, reacting and learning in systems

The traditional AI answer to the decision making problem for a robot is planning. However, planning is usually CPU-time consuming, depending on the availability and accuracy of a world model. The Dyna system generally described in earlier work, uses trial and error to learn a world model which is simultaneously used to plan reactions resulting in optimal action sequences. It is an attempt to integrate planning, reactive, and learning systems. The architecture of Dyna is presented. The different blocks are described. There are three main components of the system. The first is the world model used by the robot for internal world representation. The input of the world model is the current state and the action taken in the current state. The output is the corresponding reward and resulting state. The second module in the system is the policy. The policy observes the current state and outputs the action to be executed by the robot. At the beginning of program execution, the policy is stochastic and through learning progressively becomes deterministic. The policy decides upon an action according to the output of an evaluation function, which is the third module of the system. The evaluation function takes the following as input: the current state of the system, the action taken in that state, the resulting state, and a reward generated by the world which is proportional to the current distance from the goal state. Originally, the work proposed was as follows: (1) to implement a simple 2-D world where a 'robot' is navigating around obstacles, to learn the path to a goal, by using lookup tables; (2) to substitute the world model and Q estimate function Q by neural networks; and (3) to apply the algorithm to a more complex world where the use of a neural network would be fully justified. In this paper, the system design and achieved results will be described. First we implement the world model with a neural network and leave Q implemented as a look up table. Next, we use a lookup table for the world model and implement the Q function with a neural net. Time limitations prevented the combination of these two approaches. The final section discusses the results and gives clues for future work.

Lima, Pedro↗

The 1991 3rd NASA Symposium on VLSI Design

Papers from the symposium are presented from the following sessions: (1) featured presentations 1; (2) very large scale integration (VLSI) circuit design; (3) VLSI architecture 1; (4) featured presentations 2; (5) neural networks; (6) VLSI architectures 2; (7) featured presentations 3; (8) verification 1; (9) analog design; (10) verification 2; (11) design innovations 1; (12) asynchronous design; and (13) design innovations 2.

Maki, Gary K.↗

Aladyn - Adaptive Neural Network Molecular Dynamics Simulation Code: Computational Materials Mini-Application

This report provides an overview and commands description of the Computational Materials mini-application, Aladyn. Aladyn is a simple molecular dynamics code written in FORTRAN 2008, which is designed to demonstrate the use of adaptive neural networks (ANNs) in atomistic simulations. The role of ANNs is to reproduce the very complex energy landscape resulting from the atomic interactions in materials with the accuracy of quantum mechanics-based energy calculations. The ANN is trained on a large set of atomic structures calculated using the density functional theory (DFT) method. The Aladyn code is being released to serve as a training testbed for students and professors in academia to explore possible optimization algorithms for parallel computing on multicore central processing unit (CPU) computers or computers utilizing many core architectures based on graphic processing units (GPUs). The effort is related to the High Performance Computing Incubator (HPCI) project at NASA Langley Research Center.

Yamakov, Vesselin I.↗

VLBI System (BLK I) If-video down Conversion Design

The prototype intermediate frequency video down converter of the Deep Space Network (BLK 1) Very Long Base Interferometry system, a hybrid of analog and digital circuits, was completed and tested. The initial results met all design specifications, establishing a milestone in new design technology for such devices. This device has uses in other similar applications and can form the basis for expanded design and applications.

Ham, N. C.↗

Neural network based decomposition in optimal structural synthesis

The present paper describes potential applications of neural networks in the multilevel decomposition based optimal design of structural systems. The generic structural optimization problem of interest, if handled as a single problem, results in a large dimensionality problem. Decomposition strategies allow for this problem to be represented by a set of smaller, decoupled problems, for which solutions may either be obtained with greater ease or may be obtained in parallel. Neural network models derived through supervised training, are used in two distinct modes in this work. The first uses neural networks to make available efficient analysis models for use in repetitive function evaluations as required by the optimization algorithm. In the second mode, neural networks are used to represent the coupling that exists between the decomposed subproblems. The approach is illustrated by application to the multilevel decomposition-based synthesis of representative truss and frame structures.

Hajela, P.↗

Feasibility study, software design, layout and simulation of a two-dimensional fast Fourier transform machine for use in optical array interferometry

The NASA-Cornell Univ.-Worcester Polytechnic Institute Fast Fourier Transform (FFT) chip based on the architecture of the systolic FFT computation as presented by Boriakoff is implemented into an operating device design. The kernel of the system, a systolic inner product floating point processor, was designed to be assembled into a systolic network that would take incoming data streams in pipeline fashion and provide an FFT output at the same rate, word by word. It was thoroughly simulated for proper operation, and it has passed a comprehensive set of tests showing no operational errors. The black box specifications of the chip, which conform to the initial requirements of the design as specified by NASA, are given. The five subcells are described and their high level function description, logic diagrams, and simulation results are presented. Some modification of the Read Only Memory (ROM) design were made, since some errors were found in it. Because a four stage pipeline structure was used, simulating such a structure is more difficult than an ordinary structure. Simulation methods are discussed. Chip signal protocols and chip pinout are explained.

Boriakoff, Valentin↗

Design considerations for the beam-waveguide retrofit of a ground antenna station

Retrofitting an antenna that was originally designed without a beam waveguide introduces special difficulties because it is desirable to minimize alteration of the original mechanical truss work and to image the actual feed without distortion at the focal point of the dual-shaped reflector. To obtain an acceptable image, certain Geometrical Optics (GO) design criteria are followed as closely as possible. The problems associated with applying these design criteria to a 34-meter dual-shaped DSN (Deep Space Network) antenna are discussed. The use of various diffraction analysis techniques in the design process is also discussed. GTD and FFT algorithms are particularly necessary at the higher frequencies, while Physical Optics and Spherical Wave Expansions proved necessary at the lower frequencies.

Veruttipong, T.↗

Feasibility of Using Neural Network Models to Accelerate the Testing of Mechanical Systems

Verification testing is an important aspect of the design process for mechanical mechanisms, and full-scale, full-length life testing is typically used to qualify any new component for use in space. However, as the required life specification is increased, full-length life tests become more costly and lengthen the development time. At the NASA Lewis Research Center, we theorized that neural network systems may be able to model the operation of a mechanical device. If so, the resulting neural network models could simulate long-term mechanical testing with data from a short-term test. This combination of computer modeling and short-term mechanical testing could then be used to verify the reliability of mechanical systems, thereby eliminating the costs associated with long-term testing. Neural network models could also enable designers to predict the performance of mechanisms at the conceptual design stage by entering the critical parameters as input and running the model to predict performance. The purpose of this study was to assess the potential of using neural networks to predict the performance and life of mechanical systems. To do this, we generated a neural network system to model wear obtained from three accelerated testing devices: 1) A pin-on-disk tribometer; 2) A line-contact rub-shoe tribometer; 3) A four-ball tribometer.

Fusaro, Robert L.↗

Steady-State Thermal-Analysis Program For Microcomputers

Nodal-network model of heat flow implemented by computer program. Steady State Thermal Analysis Program, STEADY, provides thermal designer with quick and convenient method for calculation of heat loads and temperatures. Used on small nodal networks for conceptual or preliminary thermal design and analysis. Accepts up to 20 nodes of fixed or variable temperatures, with constant or temperature-dependent thermal conductivities, and any set of consistent units. Written in FORTRAN 77.

Petrick, S. W.↗

MSAT network architecture

The Mobile Satellite (MSAT) communications system will support mobile voice and data services using circuit switched and packet switched facilities with interconnection to the public switched telephone network and private networks. Control of the satellite network will reside in a Network Control System (NCS) which is being designed to be extremely flexible to provide for the operation of the system initially with one multi-beam satellite, but with capability to add additional satellites which may have other beam configurations. The architecture of the NCS is described. The signalling system must be capable of supporting the protocols for the assignment of circuits for mobile public telephone and private network calls as well as identifying packet data networks. The structure of a straw-man signalling system is discussed.

Davies, N. G.↗

COMPASS Final Report: Lunar Network Satellite-High Rate (LNS-HR)

Two design options were explored to address the requirement to provide lunar piloted missions with continuous communications for outpost and sortie missions. Two unique orbits were assessed, along with the appropriate spacecraft (S/C) to address these requirements. Both constellations (with only two S/C each) provide full time coverage (24 hr/7 d) for a south polar base and also provide continuous 7 day coverage for sorties for specified sites and periodic windows. Thus a two-satellite system can provide full coverage for sorties for selected windows of opportunity without reconfiguring the constellation.

oleson, Steven R.↗