Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “self organization”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 469 records · Page 26

Artificial Cells: Prospects for Biotechnology

A variety of techniques can now be used to alter the genome of a cell. Although these techniques are very powerful, they also have limitations related to cost and efficiency of scale. Artificial cells designed for specific applications combine properties of biological systems such as nano-scale efficiency, self-organization and adaptability at relatively low cost. Individual components needed for such structures have already been developed, and now the main challenge is to integrate them in functional microscopic compartments. It will then become possible to design and construct communities of artificial cells that can perform different tasks related to therapeutic and diagnostic applications.

Pohorille, Andrew↗

SOM Classification of Martian TES Data

A classification scheme based on unsupervised self-organizing maps (SOM) is described. Results from its application to the ASU mineral spectral database are presented. Applications to the Martian Thermal Emission Spectrometer data are discussed. Additional information is contained in the original extended abstract.

Hogan, R. C.↗

Fatigue Crack Measurement in Composite Materials by Ultrasonic Methods

The nondestructive detection of intra-ply microcracking in unlined pressure vessels fabricated from composite materials is critical to ensuring mission success. Microcracking in composite structures due to combined fatigue and cryogenic thermal loading can be very troublesome to detect in-service and when it begins to link through the thickness can cause leakage and failure of the structure. These leaks may lead to loss of pressure/propellant, increased risk of explosion and possible cryo-pumping. The work presented herein develops a method and an instrument to locate and measure intraply fatigue cracking through the thickness of laminated composite material by means of correlation with ultrasonic resonance. Resonant ultrasound spectroscopy provides measurements which are, sensitive to both the microscopic and macroscopic properties of an object. Elastic moduli, acoustic attenuation, and geometry can all be probed. The approach is based on the premise of half-wavelength resonance. The method injects a broadband ultrasonic wave into the test structure using a swept frequency technique. This method provides dramatically increased energy input into the test article, as compared to conventional spike pulsed ultrasonics. This relative energy increase improves the ability to measure finer details in the materials character, such as micro-cracking and porosity. As the micro-crack density increases, more interactions occur with the higher frequency (small wavelength) components of the signal train causing the spectrum to shift toward lower frequencies. Preliminary experiments have verified a measurable effect on the resonance spectrum of the ultrasonic data to detect microcracking. Methods involving self organizing neural networks and other clustering algorithms show that the resonance ultrasound signatures from composites vary with the degree of microcracking and can be separated and identified.

Walker, James L.↗

Ultrasonic Characterization of Fatigue Cracks in Composite Materials

Microcracking in composite structures due to combined fatigue and cryogenic loading can cause leakage and failure of the structure and can be difficult to detect in-service. In aerospace systems, these leaks may lead to loss of pressure/propellant, increased risk of explosion and possible cryo-pumping. The success of nondestructive evaluation to detect intra-ply microcracking in unlined pressure vessels fabricated from composite materials is critical to the use of composite structures in future space systems. The work presented herein characterizes measurements of intraply fatigue cracking through the thickness of laminated composite material by means of correlation with ultrasonic resonance. Resonant ultrasound spectroscopy provides measurements which are sensitive to both the microscopic and macroscopic properties of the test article. Elastic moduli, acoustic attenuation, and geometry can all be probed. The approach is based on the premise of half-wavelength resonance. The method injects a broadband ultrasonic wave into the test structure using a swept frequency technique. This method provides dramatically increased energy input into the test article, as compared to conventional pulsed ultrasonics. This relative energy increase improves the ability to measure finer details in the materials characterization, such as microcracking and porosity. As the microcrack density increases, more interactions occur with the higher frequency (small wavelength) components of the signal train causing the spectrum to shift toward lower frequencies. Several methods are under investigation to correlate the degree of microcracking from resonance ultrasound measurements on composite test articles including self organizing neural networks, chemometric techniques used in optical spectroscopy and other clustering algorithms.

Workman, Gary L.↗

An Intelligent System for Monitoring the Microgravity Environment Quality On-Board the International Space Station

An intelligent system for monitoring the microgravity environment quality on-board the International Space Station is presented. The monitoring system uses a new approach combining Kohonen's self-organizing feature map, learning vector quantization, and back propagation neural network to recognize and classify the known and unknown patterns. Finally, fuzzy logic is used to assess the level of confidence associated with each vibrating source activation detected by the system.

Lin, Paul P.↗

Monitoring the Microgravity Environment Quality On-board the International Space Station Using Soft Computing Techniques: Preliminary System Performance Results - Part 2

This paper presents the preliminary performance results of the artificial intelligence monitoring system in full operational mode using near real time acceleration data downlinked from the International Space Station. Preliminary microgravity environment characterization analysis result for the International Space Station (Increment-2), using the monitoring system is presented. Also, comparison between the system predicted performance based on ground test data for the US laboratory "Destiny" module and actual on-orbit performance, using measured acceleration data from the U.S. laboratory module of the International Space Station is presented. Finally, preliminary on-orbit disturbance magnitude levels are presented for the Experiment of Physics of Colloids in Space, which are compared with on ground test data. The ground test data for the Experiment of Physics of Colloids in Space were acquired from the Microgravity Emission Laboratory, located at the NASA Glenn Research Center, Cleveland, Ohio. The artificial intelligence was developed by the NASA Glenn Principal Investigator Microgravity Services Project to help the principal investigator teams identify the primary vibratory disturbance sources that are active, at any moment of time, on-board the International Space Station, which might impact the microgravity environment their experiments are exposed to. From the Principal Investigator Microgravity Services' web site, the principal investigator teams can monitor via a dynamic graphical display, implemented in Java, in near real time, which event(s) is/are on, such as crew activities, pumps, fans, centrifuges, compressor, crew exercise, structural modes, etc., and decide whether or not to run their experiments, whenever that is an option, based on the acceleration magnitude and frequency sensitivity associated with that experiment. This monitoring system detects primarily the vibratory disturbance sources. The system has built-in capability to detect both known and unknown vibratory disturbance sources. Several soft computing techniques such as Kohonen's Self-Organizing Feature Map, Learning Vector Quantization, Back-Propagation Neural Networks, and Fuzzy Logic were used to design the system.

Jules, Kenol↗

Phase Transition in Dusty Plasmas: A Microphysical Description

Dust grains immersed in plasma discharges acquire a large negative charge and settle into a dust cloud at the edge of the sheath. In this region, the plasma ions stream toward the electrode at a velocity u approx. cs=(T(sub e)/m(sub i))(exp 1/2). Experimentally at sufficiently high gas pressure P, the random kinetic energy of the grains is damped by gas friction, and the grains are strongly coupled and self-organize into a crystalline configuration. For lower pressures despite the dissipation of grain kinetic energy to gas friction, the dust grains reach a steady-state kinetic temperature T(sub d) which is much larger than the temperature of any other component in the plasma. T(sub d) is so large that the dust acts like a fluid. We have used the dynamically shielded dust (DSD) model to simulate these physical processes. We find that the known experimental features are nicely reproduced in the simulations, and that additional features are revealed. In the figure we plot the variation of T(sub d) as P is continuously varied in a DSD code run. A marked difference is evident between the critical pressure P(sub m) for the melting transition as P is decreased, and the critical pressure P(sub c) for the condensation transition as P is increased. For P(sub m) is less than P is less than P(sub c), mixed phase states are seen. This hysteresis occurs because the instability which triggers melting is different from the instability that heats the dust in the fluid phase and inhibits freezing. At low pressure, the dust is subject to a two-stream instability with the ions. This instability is responsible for the high temperature of the dust at low pressure. The basic physics underlying the melting transition has been elucidated in a series of papers. We are developing a first-principles analytic approach to the melting transition, which embodies the same physics that is present in the DSD code.

Joyce, Glenn↗

Applicability of Complexity Theory to Martian Fluvial Systems: A Preliminary Analysis

In the last 15 years, terrestrial geomorphology has been revolutionized by the theories of chaotic systems, fractals, self-organization, and selforganized criticality. Except for the application of fractal theory to the analysis of lava flows and rampart craters on Mars, these theories have not yet been applied to problems of Martian landscape evolution. These complexity theories are elucidated below, along with the methods used to relate these theories to the realities of Martian fluvial systems.

Rosenshein, E. B.↗

Computer Modeling of the Earliest Cellular Structures and Functions

In the absence of extinct or extant record of protocells (the earliest ancestors of contemporary cells). the most direct way to test our understanding of the origin of cellular life is to construct laboratory models of protocells. Such efforts are currently underway in the NASA Astrobiology Program. They are accompanied by computational studies aimed at explaining self-organization of simple molecules into ordered structures and developing designs for molecules that perform proto-cellular functions. Many of these functions, such as import of nutrients, capture and storage of energy. and response to changes in the environment are carried out by proteins bound to membrane< We will discuss a series of large-scale, molecular-level computer simulations which demonstrate (a) how small proteins (peptides) organize themselves into ordered structures at water-membrane interfaces and insert into membranes, (b) how these peptides aggregate to form membrane-spanning structures (eg. channels), and (c) by what mechanisms such aggregates perform essential proto-cellular functions, such as proton transport of protons across cell walls, a key step in cellular bioenergetics. The simulations were performed using the molecular dynamics method, in which Newton's equations of motion for each item in the system are solved iteratively. The problems of interest required simulations on multi-nanosecond time scales, which corresponded to 10(exp 6)-10(exp 8) time steps.

Pohorille, Andrew↗

Artificial cells: prospects for biotechnology

A variety of techniques can now be used to alter the genome of a cell. Although these techniques are very powerful, they have limitations related to cost and efficiency of scale. Artificial cells designed for specific applications combine properties of biological systems such as nanoscale efficiency, self-organization and adaptability at relatively low cost. Individual components needed for such structures have already been developed, and now the main challenge is to integrate them in functional microscopic compartments. It will then become possible to design and construct communities of artificial cells that can perform different tasks related to therapeutic and diagnostic applications.

Review↗

Whole-cell biocomputing

The ability to manipulate systems on the molecular scale naturally leads to speculation about the rational design of molecular-scale machines. Cells might be the ultimate molecular-scale machines and our ability to engineer them is relatively advanced when compared with our ability to control the synthesis and direct the assembly of man-made materials. Indeed, engineered whole cells deployed in biosensors can be considered one of the practical successes of molecular-scale devices. However, these devices explore only a small portion of cellular functionality. Individual cells or self-organized groups of cells perform extremely complex functions that include sensing, communication, navigation, cooperation and even fabrication of synthetic nanoscopic materials. In natural systems, these capabilities are controlled by complex genetic regulatory circuits, which are only partially understood and not readily accessible for use in engineered systems. Here, we focus on efforts to mimic the functionality of man-made information-processing systems within whole cells.

Non-NASA Center↗

Shape-dependent control of cell growth, differentiation, and apoptosis: switching between attractors in cell regulatory networks

Development of characteristic tissue patterns requires that individual cells be switched locally between different phenotypes or "fates;" while one cell may proliferate, its neighbors may differentiate or die. Recent studies have revealed that local switching between these different gene programs is controlled through interplay between soluble growth factors, insoluble extracellular matrix molecules, and mechanical forces which produce cell shape distortion. Although the precise molecular basis remains unknown, shape-dependent control of cell growth and function appears to be mediated by tension-dependent changes in the actin cytoskeleton. However, the question remains: how can a generalized physical stimulus, such as cell distortion, activate the same set of genes and signaling proteins that are triggered by molecules which bind to specific cell surface receptors. In this article, we use computer simulations based on dynamic Boolean networks to show that the different cell fates that a particular cell can exhibit may represent a preprogrammed set of common end programs or "attractors" which self-organize within the cell's regulatory networks. In this type of dynamic network model of information processing, generalized stimuli (e.g., mechanical forces) and specific molecular cues elicit signals which follow different trajectories, but eventually converge onto one of a small set of common end programs (growth, quiescence, differentiation, apoptosis, etc.). In other words, if cells use this type of information processing system, then control of cell function would involve selection of preexisting (latent) behavioral modes of the cell, rather than instruction by specific binding molecules. Importantly, the results of the computer simulation closely mimic experimental data obtained with living endothelial cells. The major implication of this finding is that current methods used for analysis of cell function that rely on characterization of linear signaling pathways or clusters of genes with common activity profiles may overlook the most critical features of cellular information processing which normally determine how signal specificity is established and maintained in living cells. Copyright 2000 Academic Press.

Review↗

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.↗

Dissipating Step Bunches during Crystallization under Transport Control

In studies of crystal formation by the generation and spreading of layers, equidistant step trains are considered unstable---bunches and other spatiotemporal patterns of the growth steps are viewed as ubiquitous. We provide an example to the opposite. We monitor the spatiotemporal dynamics of steps and the resulting step patterns during crystallization of the proteins ferritin and apoferritin using the atomic force microscope. The variations in step velocity and density are not correlated, indicating the lack of a long-range attraction between the steps. We show that (i) because of its coupling to bulk transport, nucleation of new layers is chaotic and occurs at the facet edges, where the interfacial supersaturation is higher; (ii) step bunches self-organize via the competition for supply from the solution; and, (iii) bunches of weakly interacting steps decay as they move along the face. Tests by numerical modeling support the conclusions about the mechanisms underlying our observations. The results from these systems suggest that during crystallization controlled by transport, with weakly or noninteracting growth steps, the stable kinetic state of the surface is an equidistant step train, and step bunches only arise during nucleation of new layers. Since nucleation only occurs at a few sites on the surface, the surface morphology may be controllably patterned or smoothened by locally controlling nucleation.

Lin, Hong↗

Gene Expression Dynamics Inspector (GEDI): for integrative analysis of expression profiles

Genome-wide expression profiles contain global patterns that evade visual detection in current gene clustering analysis. Here, a Gene Expression Dynamics Inspector (GEDI) is described that uses self-organizing maps to translate high-dimensional expression profiles of time courses or sample classes into animated, coherent and robust mosaics images. GEDI facilitates identification of interesting patterns of molecular activity simultaneously across gene, time and sample space without prior assumption of any structure in the data, and then permits the user to retrieve genes of interest. Important changes in genome-wide activities may be quickly identified based on 'Gestalt' recognition and hence, GEDI may be especially useful for non-specialist end users, such as physicians. AVAILABILITY: GEDI v1.0 is written in Matlab, and binary Matlab.dll files which require Matlab to run can be downloaded for free by academic institutions at http://www.chip.org/~ge/gedihome.html Supplementary information: http://www.chip.org/~ge/gedihome.html.

Database Management Systems↗

Intermittent Turbulence and SOC Dynamics in a 2-D Driven Current-Sheet Model

Borovsky et al. have shown that Earth's magnetotail plasma sheet is strongly turbulent. More recently, Borovsky and Funsten have shown that eddy turbulence dominates and have suggested that the eddy turbulence is driven by fast flows that act as jets in the plasma. Through basic considerations of energy and magnetic flux conservation, these fast flows are thought to be localized to small portions of the total plasma sheet and to be generated by magnetic flux reconnection that is similarly localized. Angelopoulos et al., using single spacecraft Geotail data, have shown that the plasma sheet turbulence exhibits signs of intermittence and Weygand et al., using four spacecraft Cluster data, have confirmed and expanded on this conclusion. Uritsky et al., using Polar UVI image data, have shown that the evolution of bright, nightside, UV auroral emission regions is consistent with many of the properties of systems in self-organized criticality (SOC). Klimas et al. have suggested that the auroral dynamics is a reflection of the dynamics of the fast flows in the plasma. sheet. Their hypothesis is that the transport of magnetic fludenergy through the magnetotail is enabled by scale-free avalanches of localized reconnection whose SOC dynamics are reflected in the auroral UV emission dynamics. A corollary of this hypothesis is that the strong, intermittent, eddy turbulence of the plasma sheet is closely related to its critical dynamics. The question then arises: Can in situ evidence for the SOC dynamics be found in the properties of the plasma sheet turbulence? A 2-dimensional numerical driven current-sheet model of the central plasma sheet has been developed that incorporates an idealized current-driven instability with a resistive MHD system. It has been shown that the model can evolve into SOC in a physically relevant parameter regime. Initial results from a study of intermittent turbulence in this model and the relationship of this turbulence to the model's known SOC dynamics will be discussed.

Klimas, A. J.↗

'Heat from Above' Heat Capacity Measurements in Liquid He-4

We have made heat capacity measurements of superfluid He-4 at temperatures very close to the lambda point, T(sub lambda) , in a constant heat flux, Q, when the helium sample is heated from above. In this configuration the helium enters a self-organized (SOC) heat transport state at a temperature T(sub SOC)(Q), which for Q greater than or = 100 nW/sq cm lies below T(sub lambda). At low Q we observe little or no deviation from the bulk Q = 0 heat capacity up to T(sub SOC)(Q); beyond this temperature the heat capacity appears to be sharply depressed, deviating dramatically from its bulk behaviour. This marks the formation and propagation of a SOC/superfluid two phase state, which we confirm with a simple model. The excellent agreement between data and model serves as an independent confirmation of the existence of the SOC state. As Q is increased (up to 6 micron W/sq cm) we observe a Q dependant depression in the heat capacity that occurs just below T(sub SOC)(Q), when the entire sample is still superfluid. This is due to the emergence of a large thermal resistance in the sample, which we have measured and used to model the observed heat capacity depression. Our measurements of the superfluid thermal resistivity are a factor of ten larger than previous measurements by Baddar et al.

Lee, R. A. M.↗

Control Algorithms and Simulated Environment Developed and Tested for Multiagent Robotics for Autonomous Inspection of Propulsion Systems

The NASA Glenn Research Center and academic partners are developing advanced multiagent robotic control algorithms that will enable the autonomous inspection and repair of future propulsion systems. In this application, on-wing engine inspections will be performed autonomously by large groups of cooperative miniature robots that will traverse the surfaces of engine components to search for damage. The eventual goal is to replace manual engine inspections that require expensive and time-consuming full engine teardowns and allow the early detection of problems that would otherwise result in catastrophic component failures. As a preliminary step toward the long-term realization of a practical working system, researchers are developing the technology to implement a proof-of-concept testbed demonstration. In a multiagent system, the individual agents are generally programmed with relatively simple controllers that define a limited set of behaviors. However, these behaviors are designed in such a way that, through the localized interaction among individual agents and between the agents and the environment, they result in self-organized, emergent group behavior that can solve a given complex problem, such as cooperative inspection. One advantage to the multiagent approach is that it allows for robustness and fault tolerance through redundancy in task handling. In addition, the relatively simple agent controllers demand minimal computational capability, which in turn allows for greater miniaturization of the robotic agents.

Wong, Edmond↗