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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRS1996

Response of Earth's Ecosystem to Global Change

The Earth is in the midst of rapid and unprecedented change, much of it caused by the enormous reproductive and resource acquisition success of the human population. For the first time in Earth's history, the actions of one species-humans-are altering the atmospheric, climatic, biospheric, and edaphic processes on a scale that rivals natural processes. How will ecosystems, involving those manipulated and managed by humans largely for human use, respond to these changes? Clearly ecosystems have been adjusting to change throughout Earth's history and evolving in ways to adapt and to maintain self-organizing behavior. And in this process, the metabolic activity of the biosphere has altered the environmental conditions it experiences. I am going to confine this presentation to a few thoughts on the present state of terrestrial ecosystems and the urgency that changes in it is bringing to all of us.

Peterson, David L.↗
NASA NTRS1997

Membrane-Based Functions in the Origin of Cellular Life

If peptides consist of nonpolar residues only, they become inserted into the nonpolar phase. As demonstrated by the example of the leucine undecamer, such peptides fold into an a-helix as they partition into the nonpolar medium. The folding proceeds through an intermediate, called the 310-helix, which remains in equilibrium with the a-helix. This process represents a simple, protobiologically relevant example of environmentally-mediated self-organization of biological molecules. Once in the nonpolar environment, the peptides can readily change their orientation with respect to the interface from parallel to perpendicular, especially in response to local electric fields. The ability of nonpolar peptides to modify both the structure and orientation with changing external conditions may have provided a simple mechanism of transmitting signals from the environment to the interior of a protocell.

Wilson, Michael↗
NASA NTRS1998

Ecosystems and the Biosphere as Complex Adaptive Systems

Ecosystems are prototypical examples of complex adaptive systems, in which patterns at higher levels emerge from localized interactions and selection processes acting at lower levels. An essential aspect of such systems is nonlinearity, leading to historical dependency and multiple possible outcomes of dynamics. Given this, it is essential to determine the degree to which system features are determined by environmental conditions, and the degree to which they are the result of self-organization. Furthermore, given the multiple levels at which dynamics become apparent and at which selection can act, central issues relate to how evolution shapes ecosystems properties, and whether ecosystems become buffered to changes (more resilient) over their ecological and evolutionary development or proceed to critical states and the edge of chaos.

Levin, Simon A.↗
NASA NTRS1999

Strong Evidence for Stochastic Growth of Langmuir-Like Waves in Earth's Foreshock

Bursty Langmuir-like waves driven by electron beams in Earth's foreshock have properties which are inconsistent with the standard plasma physics paradigm of uniform exponential growth saturated by nonlinear processes. Here it is demonstrated for a specific period that stochastic growth theory (SGT) quantitatively describes these waves throughout a large fraction of the foreshock. The statistical wave properties are inconsistent with nonlinear processes or self-organized criticality being important. SGT's success in explaining the foreshock waves and type III solar bursts suggests that SGT is widely applicable to wave growth in space, astrophysical, and laboratory plasmas.

Cairns, Iver H.↗
NASA NTRS1999

Statistical Properties of SGR 1900+14 Bursts

We study the statistics of soft gamma repeater (SGR) bursts, using a data base of 187 events detected with BATSE and 837 events detected with RXTE PCA, all from SGR 1900+14 during its 1998-1999 active phase. we find that the fluence or energy distribution of bursts is consistent with a power law of index 1.66, over 4 orders of magnitude. This scale-free distribution resembles the Gutenberg-Richter Law for earthquakes, and gives evidence for self-organized criticality in SGRS. The distribution of time intervals between successive bursts from SGR 1900+14 is consistent with a log-normal distribution. There is no correlation between burst intensity and the waiting times till the next burst, but there is some evidence for a correlation between burst intensity and the time elapsed since the previous burst. We also find a correlation between the duration and the energy of the bursts, but with significant scatter. In all these statistical properties, SGR bursts resemble earthquakes and solar flares more closely than they resemble any known accretion-powered or nuclear-powered phenomena. Thus our analysis lends support to the hypothesis that the energy source for SGR bursts is internal to the neutron star, and plausibly magnetic.

Gogus, Ersin↗
NASA NTRS1999

Statistical Properties of SGR 1806-20 Bursts

We find that the fluence distribution of bursts observed with each instrument are well described by power laws with indices 1.43, 1.67 and 1.76 respectively. The distribution of time intervals between successive bursts from SGR 1806-20 is described by a lognormal function with peak at 97 s. There is no correlation between burst intensity and either the waiting times till the next burst or the time elapsed since the previous burst, We find a correlation between the duration and fluence of the bursts, but with substantial scatter. In all these statistical properties, SGR bursts resemble self-organized critical systems, such as earthquakes and solar flares. Our results thus support the hypothesis that the energy source for SGR bursts is crustquakes due to the magnetic field of the neutron star, rather than any accretion- or nuclear-power.

Gogus, E.↗
NASA NTRS2000

Statistical Properties of SGR 1806-20 Bursts

We present statistics of SGR 1806-20 bursts, combining 290 events detected with the Rossi X-Ray Timing Explorer/Proportional Counter Array, 111 events detected with the Burst and Transient Source Experiment, and 134 events detected with the International Cometary, Explorer. We find that the fluence distribution of bursts observed with each instrument are well described by power laws with indices 1.43, 1.76, and 1.67, respectively. The distribution of time intervals between successive bursts from SGR 1806-20 is described by a lognormal function with a peak at 103 s. There is no correlation between the burst intensity and either the waiting times until the next burst or the time elapsed since the previous burst. In all these statistical properties, SGR 1806-20 bursts resemble a self-organized critical system, similar to earthquakes and solar flares. Our results thus support the hypothesis that the energy source for soft gamma repeater bursts is crustquakes due to the evolving, strong magnetic field of the neutron star, rather than any accretion or nuclear power.

Gogus, Ersin↗
NASA NTRS1999

Statistical Properties of SGR 1900+14 Bursts

We study the statistics of soft gamma repeater (SGR) bursts using a database of 187 events detected with BATSE and 837 events detected with the Rossi X-Ray Timing Explorer Proportional Counter Array: all events are from SGR 1900+14 during its 1998-1999 active phase. We find that the fluence or energy distribution of bursts is consistent with a power law of index 1.66, over 4 orders of magnitude. This scale-free distribution resembles the Gutenberg-Richter law for earthquakes and gives evidence for self-organized criticality in SGRS. The distribution of time intervals between successive bursts from SGR 1900+14 is consistent with a lognormal distribution. There is no correlation between burst intensity and the waiting times till the next burst, but there is some evidence for a correlation between burst intensity and the time elapsed since the previous burst. We also find a correlation between the duration and the energy of the bursts, but with significant scatter. In all these statistical properties, SGR bursts resemble earthquakes and solar flares more closely than they resemble any known accretion-powered or nuclear-powered phenomena. Thus, our analysis lends support to the hypothesis that the energy source for SGR bursts is internal to the neutron star and plausibly magnetic.

Gogus, Ersin↗
NASA NTRS1999

Dynamical Signatures of Living Systems

One of the main challenges in modeling living systems is to distinguish a random walk of physical origin (for instance, Brownian motions) from those of biological origin and that will constitute the starting point of the proposed approach. As conjectured, the biological random walk must be nonlinear. Indeed, any stochastic Markov process can be described by linear Fokker-Planck equation (or its discretized version), only that type of process has been observed in the inanimate world. However, all such processes always converge to a stable (ergodic or periodic) state, i.e., to the states of a lower complexity and high entropy. At the same time, the evolution of living systems directed toward a higher level of complexity if complexity is associated with a number of structural variations. The simplest way to mimic such a tendency is to incorporate a nonlinearity into the random walk; then the probability evolution will attain the features of diffusion equation: the formation and dissipation of shock waves initiated by small shallow wave disturbances. As a result, the evolution never "dies:" it produces new different configurations which are accompanied by an increase or decrease of entropy (the decrease takes place during formation of shock waves, the increase-during their dissipation). In other words, the evolution can be directed "against the second law of thermodynamics" by forming patterns outside of equilibrium in the probability space. Due to that, a specie is not locked up in a certain pattern of behavior: it still can perform a variety of motions, and only the statistics of these motions is constrained by this pattern. It should be emphasized that such a "twist" is based upon the concept of reflection, i.e., the existence of the self-image (adopted from psychology). The model consists of a generator of stochastic processes which represents the motor dynamics in the form of nonlinear random walks, and a simulator of the nonlinear version of the diffusion equation which represents the mental dynamics. It has been demonstrated that coupled mental-motor dynamics can simulate emerging self-organization, prey-predator games, collaboration and competition, "collective brain," etc.

Zak, M.↗
NASA NTRS1999

Condensed Plasmas under Microgravity

Experiments under microgravity conditions were carried out to study 'condensed' (liquid and crystalline) states of a colloidal plasma (ions, electrons, and charged microspheres). Systems with approximately 10(exp 6) microspheres were produced. The observed systems represent new forms of matter--quasineutral, self-organized plasmas--the properties of which are largely unexplored. In contrast to laboratory measurements, the systems under microgravity are clearly three dimensional (as expected); they exhibit stable vortex flows, sometimes adjacent to crystalline regions, and a central 'void,' free of microspheres.

Morfill, G. E.↗
NASA NTRS1993

A Probabilistic Model for Simulating Magnetoacoustic Emission Responses in Ferromagnets

Magnetoacoustic emission (MAE) is a phenomenon where acoustic noise is generated due to the motion of non-180 magnetic domain walls in a ferromagnet with non-zero magnetostrictive constants. MAE has been studied extensively for many years and has even been applied as an NDE tool for characterizing the heat treatment of high-yield low carbon steels. A complete theory which fully accounts for the magnetoacoustic response, however, has not yet emerged. The motion of the domain walls appears to be a totally random process, however, it does exhibit features of regularity which have been identified by studying phenomena such as 1/f flicker noise and self-organized criticality (SOC). In this paper, a probabilistic model incorporating the effects of SOC has been developed to help explain the MAE response. The model uses many simplifying assumptions yet yields good qualitative agreement with observed experimental results and also provides some insight into the possible underlying mechanisms responsible for MAE. We begin by providing a brief overview of magnetoacoustic emission and the experimental set-up used to obtain the MAE signal. We then describe a pseudo-probabilistic model used to predict the MAE response and give an example of the predicted result. Finally, the model is modified to account for SOC and the new predictions are shown and compared with experiment.

Namkung, M.↗
NASA NTRS1997

On Hardware Evolvability and Levels of Granularity

Evolvable hardware addresses hardware that self-organizes/reconfigures under the guidance of evolutionary mechanisms. Some experiments in evolving at transistor level are briefly presented and the perspective of trnsistors as functional approximators is suggested.

Granularity Hardware↗
NASA NTRS1996

Probability Simulations by Non-Lipschitz Chaos

It has been demonstrated that classical probabilities, and in particular, probabilistic Turing machine, can be simulated by combining chaos and non-Lipschitz dynamics, without utilization of any man-made devices. Self-organizing properties of systems coupling simulated and calculated probabilities and their link to quantum computations are discussed.

classical dynamics classical probabilities probabi↗
NASA NTRS1993

Image and Video Compression with VLSI Neural Networks

An advanced motion-compensated predictive video compression system based on artificial neural networks has been developed to effectively eliminate the temporal and spatial redundancy of video image sequences and thus reduce the bandwidth and storage required for the transmission and recording of the video signal. The VLSI neuroprocessor for high-speed high-ratio image compression based upon a self-organization network and the conventional algorithm for vector quantization are compared. The proposed method is quite efficient and can achieve near-optimal results.

compression artificial neural networks VLSI↗
NASA NTRS1996

Simulations of Probabilities for Quantum Computing

It has been demonstrated that classical probabilities, and in particular, probabilistic Turing machine, can be simulated by combining chaos and non-LIpschitz dynamics, without utilization of any man-made devices (such as random number generators). Self-organizing properties of systems coupling simulated and calculated probabilities and their link to quantum computations are discussed.

Turing machines↗
NASA NTRS1998

Probabilistic resource allocation system with self-adaptive capability

A probabilistic resource allocation system is disclosed containing a low capacity computational module (Short Term Memory or STM) and a self-organizing associative network (Long Term Memory or LTM) where nodes represent elementary resources, terminal end nodes represent goals, and weighted links represent the order of resource association in different allocation episodes. Goals and their priorities are indicated by the user, and allocation decisions are made in the STM, while candidate associations of resources are supplied by the LTM based on the association strength (reliability). Weights are automatically assigned to the network links based on the frequency and relative success of exercising those links in the previous allocation decisions. Accumulation of allocation history in the form of an associative network in the LTM reduces computational demands on subsequent allocations. For this purpose, the network automatically partitions itself into strongly associated high reliability packets, allowing fast approximate computation and display of allocation solutions satisfying the overall reliability and other user-imposed constraints. System performance improves in time due to modification of network parameters and partitioning criteria based on the performance feedback.

Yufik, Yan M.↗
NASA NTRS1996

Probabilistic resource allocation system with self-adaptive capability

A probabilistic resource allocation system is disclosed containing a low capacity computational module (Short Term Memory or STM) and a self-organizing associative network (Long Term Memory or LTM) where nodes represent elementary resources, terminal end nodes represent goals, and directed links represent the order of resource association in different allocation episodes. Goals and their priorities are indicated by the user, and allocation decisions are made in the STM, while candidate associations of resources are supplied by the LTM based on the association strength (reliability). Reliability values are automatically assigned to the network links based on the frequency and relative success of exercising those links in the previous allocation decisions. Accumulation of allocation history in the form of an associative network in the LTM reduces computational demands on subsequent allocations. For this purpose, the network automatically partitions itself into strongly associated high reliability packets, allowing fast approximate computation and display of allocation solutions satisfying the overall reliability and other user-imposed constraints. System performance improves in time due to modification of network parameters and partitioning criteria based on the performance feedback.

Yufik, Yan M.↗