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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 NTRS1988

Adaptive parallel logic networks

Adaptive, self-organizing concurrent systems (ASOCS) that combine self-organization with massive parallelism for such applications as adaptive logic devices, robotics, process control, and system malfunction management, are presently discussed. In ASOCS, an adaptive network composed of many simple computing elements operating in combinational and asynchronous fashion is used and problems are specified by presenting if-then rules to the system in the form of Boolean conjunctions. During data processing, which is a different operational phase from adaptation, the network acts as a parallel hardware circuit.

Martinez, Tony R.↗
NASA NTRS1991

Avalanches and the distribution of solar flares

The solar coronal magnetic field is proposed to be in a self-organized critical state, thus explaining the observed power-law dependence of solar-flare-occurrence rate on flare size which extends over more than five orders of magnitude in peak flux. The physical picture that arises is that solar flares are avalanches of many small reconnection events, analogous to avalanches of sand in the models published by Bak and colleagues in 1987 and 1988. Flares of all sizes are manifestations of the same physical processes, where the size of a given flare is determined by the number of elementary reconnection events. The relation between small-scale processes and the statistics of global-flare properties which follows from the self-organized magnetic-field configuration provides a way to learn about the physics of the unobservable small-scale reconnection processes. A simple lattice-reconnection model is presented which is consistent with the observed flare statistics. The implications for coronal heating are discussed and some observational tests of this picture are given.

Lu, Edward T.↗
NASA NTRS1972

Computers formed by the problems rather than problems deformed by the computers.

Description of an approach to computer programming which tries to minimize the time required for retranslation from the computer language into the language of the original process. A notion of a programmable network is introduced which allows the abstract machines that are a model of the processes in the user's mind to be put into a rigorous and simple form. Each process is then modeled as a particular finite-state machine, a circulating page loose system being employed as an architecture for implementing these finite-state machines. An experiment is discussed in which the use of abstract machines as a language for modeling processes, in conjunction with the use of a self-organizing computer, decreases user effort, eliminates the need for compilation, facilitates debugging, and decreases computer time.

Schaffner, M. R.↗
NASA NTRS1978

Effect of various features on the life cycle cost of the timing/synchronization subsystem of the DCS digital communications network

The effect on the life cycle cost of the timing subsystem was examined, when these optional features were included in various combinations. The features included mutual control, directed control, double-ended reference links, independence of clock error measurement and correction, phase reference combining, self-organization, smoothing for link and nodal dropouts, unequal reference weightings, and a master in a mutual control network. An overall design of a microprocessor-based timing subsystem was formulated. The microprocessor (8080) implements the digital filter portion of a digital phase locked loop, as well as other control functions such as organization of the network through communication with processors at neighboring nodes.

Kimsey, D. B.↗
NASA NTRS1979

CLASSY: An adaptive maximum likelihood clustering algorithm

The CLASSY clustering method alternates maximum likelihood iterative techniques for estimating the parameters of a mixture distribution with an adaptive procedure for splitting, combining, and eliminating the resultant components of the mixture. The adaptive procedure is based on maximizing the fit of a mixture of multivariate normal distributions to the observed data using its first through fourth central moments. It generates estimates of the number of multivariate normal components in the mixture as well as the proportion, mean vector, and covariance matrix for each component. The basic mathematical model for CLASSY and the actual operation of the algorithm as currently implemented are described. Results of applying CLASSY to real and simulated LANDSAT data are presented and compared with those generated by the iterative self-organizing clustering system algorithm on the same data sets.

Lennington, R. K.↗
NASA NTRS1981

An evaluation of ISOCLS and CLASSY clustering algorithms for forest classification in northern Idaho

Both the iterative self-organizing clustering system (ISOCLS) and the CLASSY algorithms were applied to forest and nonforest classes for one 1:24,000 quadrangle map of northern Idaho and the classification and mapping accuracies were evaluated with 1:30,000 color infrared aerial photography. Confusion matrices for the two clustering algorithms were generated and studied to determine which is most applicable to forest and rangeland inventories in future projects. In an unsupervised mode, ISOCLS requires many trial-and-error runs to find the proper parameters to separate desired information classes. CLASSY tells more in a single run concerning the classes that can be separated, shows more promise for forest stratification than ISOCLS, and shows more promise for consistency. One major drawback to CLASSY is that important forest and range classes that are smaller than a minimum cluster size will be combined with other classes. The algorithm requires so much computer storage that only data sets as small as a quadrangle can be used at one time.

Werth, L. F.↗
NASA NTRS1987

Intelligent signal analysis and recognition

Progress in the research and development of self-organizing database system that can support the identification and characterization of signals in an RF environment is described. As the radio frequency spectrum becomes more crowded, there are a number of situations that require a characterization of the RF environment. This database system is designed to be practical in applications where communications and other instruments encounter a time varying and complex RF environment. The primary application of this system is the guidance and control of NASA's SETI Microwave Observing Project. Other possible applications include selection of telemety bands for communication with spacecraft, and the scheduling of antenna for radio astronomy are two examples where characterization of the RF environment is required. In these applications, the RF environment is constantly changing, and even experienced operators cannot quickly identify the multitude of signals that can be encountered. Some of these signals are repetitive, others appear to occur sporadically.

Levinson, Robert↗
NASA NTRS1987

Optoelectronic analogs of self-programming neural nets - Architecture and methodologies for implementing fast stochastic learning by simulated annealing

Self-organization and learning is a distinctive feature of neural nets and processors that sets them apart from conventional approaches to signal processing. It leads to self-programmability which alleviates the problem of programming complexity in artificial neural nets. In this paper architectures for partitioning an optoelectronic analog of a neural net into distinct layers with prescribed interconnectivity pattern to enable stochastic learning by simulated annealing in the context of a Boltzmann machine are presented. Stochastic learning is of interest because of its relevance to the role of noise in biological neural nets. Practical considerations and methodologies for appreciably accelerating stochastic learning in such a multilayered net are described. These include the use of parallel optical computing of the global energy of the net, the use of fast nonvolatile programmable spatial light modulators to realize fast plasticity, optical generation of random number arrays, and an adaptive noisy thresholding scheme that also makes stochastic learning more biologically plausible. The findings reported predict optoelectronic chips that can be used in the realization of optical learning machines.

Farhat, Nabil H.↗
NASA NTRS1988

Planetary environments and the conditions of life

Geophysical models of the first 600 Ma ofthe earth's history following accretion and core formation point to a period of great environmental disequilibrium. In such an environment, the passage of energy from the earth's interior and from the sun through gas-liquid-solid domains and their boundaries with each other generated a dynamically interacting, complex hierarchy of self-organized structures ranging from bubbles at the sea-air interface to tectonic plates. The ability of a planet to produce such a hierarchy is speculated to be a prerequisite to the origin and sustenance of life. The application of this criterion to Mars argues against the origin of Martian life.

Chang, S.↗
NASA NTRS1989

Oligomerization of deoxynucleoside-biphosphate dimers - Template and linkage specificity

The oligomerization of the activated 3-prime-5-prime pyrophosphate-linked dimer, pdAppdAp, is presently noted to be selectively favored by a poly(U) template over the 3-prime-3-prime and 5-prime-5-prime linked dimers. Both overall yields and the production of the longest oligomers were markedly stimulated by poly(U)'s presence; in its absence, the 5-prime-5-prime linked dimer became the most reactive, yielding chains of the order of 60 monomer-unit lengths. Remarkable self-organization properties are noted for the 5-prime-5-prime dimer of pdAp.

Visscher, J.↗
NASA NTRS1989

Terminal attractors in neural networks

A new type of attractor (terminal attractors) for content-addressable memory, associative memory, and pattern recognition in artificial neural networks operating in continuous time is introduced. The idea of a terminal attractor is based upon a violation of the Lipschitz condition at a fixed point. As a result, the fixed point becomes a singular solution which envelopes the family of regular solutions, while each regular solution approaches such an attractor in finite time. It will be shown that terminal attractors can be incorporated into neural networks such that any desired set of these attractors with prescribed basins is provided by an appropriate selection of the synaptic weights. The applications of terminal attractors for content-addressable and associative memories, pattern recognition, self-organization, and for dynamical training are illustrated.

Zak, Michail↗
NASA NTRS1990

Integrated communication and information fabric for space applications

The results of preliminary research into infrastructures for integrated communication and information fabrics, which can meet the needs of space applications of the future, are presented. Technologies that foster scaleability and adaptability and support self-organizing mechanisms are needed to effectively integrate the working fabric of a large-scale distributed system. A multigrid network architecture that uses a completely distributed packet-routing scheme is derived. The first part of the paper introduces a simple model of a communication and information system for space applications, the second discusses the known limitations of the large-scale future communication and information systems, and the third part describes the results of preliminary research in this area. It is expected that this technology will result in inexpensive networks utilizing multigigabit-per-second data links.

Maitan, J.↗
NASA NTRS1990

Observation of seeded second harmonic generation in bulk germanosilicate fiber preforms

Simultaneous irradiation of a bulk fiber preform with molar concentrations of 3 pct Ge and 0.5 pct P doped silica core region resulted in self-organized second harmonic generation with an effective chi(2) of about 1.2 x 10 to the -16th m/V. The experiments revealed that the bulk preform requires the same critical IR intensity (10 GW/sq cm) as the drawn fibers to prepare. Attempts to self-prepare the preform field, indicating that self-preparation in fibers is most likely initiated by second harmonic generation associated with the core-cladding interface.

Lawandy, N. M.↗
NASA NTRS1991

A multidisciplinary approach to the development of low-cost high-performance lightwave networks

Our research focuses on high-speed distributed systems. We anticipate that our results will allow the fabrication of low-cost networks employing multi-gigabit-per-second data links for space and military applications. The recent development of high-speed low-cost photonic components and new generations of microprocessors creates an opportunity to develop advanced large-scale distributed information systems. These systems currently involve hundreds of thousands of nodes and are made up of components and communications links that may fail during operation. In order to realize these systems, research is needed into technologies that foster adaptability and scaleability. Self-organizing mechanisms are needed to integrate a working fabric of large-scale distributed systems. The challenge is to fuse theory, technology, and development methodologies to construct a cost-effective, efficient, large-scale system.

Maitan, Jacek↗
NASA NTRS1990

Cosmic instability from radiation pressure

The Cosmic Background Explorer has recently confirmed the blackbody character of the microwave background to high accuracy (Mather et al., 1990), and will have the capability to detect other cosmic backgrounds throughout the infrared. A detection of cosmic background radiation dating from the pregalactic era would have important consequences for theories of cosmic structure. During the creation of such a background the pressure of the radiation itself causes an instability which leads inevitably to the growth of large-scale structure in the matter distribution. In contrast to conventional gravitational-instability models, the statistical properties of this structure are determined primarily by the self-organizing dynamics of the instability rather than details of cosmological initial conditions. The behavior of the instability is described here.

Hogan, Craig J.↗
NASA NTRS1991

Communications and control for electric power systems

The first section of the report describes the AbNET system, a hardware and software communications system designed for distribution automation (it can also find application in substation monitoring and control). The topology of the power system fixes the topology of the communications network, which can therefore be expected to include a larger number of branch points, tap points, and interconnections. These features make this communications network unlike any other. The network operating software has to solve the problem of communicating to all the nodes of a very complex network in as reliable a way as possible even if the network is damaged, and it has to do so with minimum transmission delays and at minimum cost. The design of the operating protocols is described within the framework of the seven-layer Open System Interconnection hierarchy of the International Standards Organization. Section 2 of the report describes the development and testing of a high voltage sensor based on an electro-optic polymer. The theory of operation is reviewed. Bulk fabrication of the polymer is discussed, as well as results of testing of the electro-optic coefficient of the material. Fabrication of a complete prototype sensor suitable for use in the range 1-20 kV is described. The electro-optic polymer is shown to be an important material for fiber optic sensing applications. Appendix A is theoretical support for this work. The third section of the report presents the application of an artificial neural network, Kohonen's self-organizing feature map, for the classification of power system states. This classifier maps vectors of an N-dimensional space to a 2-dimensional neural net in a nonlinear way preserving the topological order of the input vectors. These mappings are studied using a nonlinear power system model.

Kirkham, H.↗