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At least 739 records · Page 41

Information processing in the primate visual system - An integrated systems perspective

The primate visual system contains dozens of distinct areas in the cerebral cortex and several major subcortical structures. These subdivisions are extensively interconnected in a distributed hierarchical network that contains several intertwined processing streams. A number of strategies are used for efficient information processing within this hierarchy. These include linear and nonlinear filtering, passage through information bottlenecks, and coordinated use of multiple types of information. In addition, dynamic regulation of information flow within and between visual areas may provide the computational flexibility needed for the visual system to perform a broad spectrum of tasks accurately and at high resolution.

Van Essen, David C.↗

On the origin of streaks in turbulent shear flows

The paper substantiates the notion that selective amplification and direct resonance, based on linear theory, does not provide a selection mechanism for the well-defined streak spacing of about 100 wall units observed in wall-bounded turbulent shear flows. For the direct resonance theory, it is shown that the streaks are created by the nonlinear self-interaction of the vertical velocity rather than that of the directly forced vertical vorticity. It is proposed that the selection mechanism must be inherently nonlinear and correspond to a self-sustaining process. For the case of plane Poiseuille flow the 100-wall-unit criterion corresponds to a critical Reynolds number of 1250, based on the centerline velocity and the channel half-width, which is close to the usually quoted value of about 1000. In plane Couette flow, it corresponds to a critical Reynolds number of 625, based on the half-velocity difference and the half-width.

Waleffe, Fabian↗

Coherent structures in the universe and the adhesion model

An adhesion model is used to study the formation process of large-scale structures due to nonlinear gravitational growth of small initial fluctuations in the universe dominated by dark matter. The model is compared with 2D N-body simulations with initial power-law spectral indices n = -2, 0, +2, and various cutoffs. It is found that the adhesion model imitates the skeleton of the structure extremely well for the parameters of the initial spectra until the stage when the nonlinear scale reaches the correlation length R(phi) of the initial gravitational potential. The model explains the origin of large-scale coherent sructures, such as superpancakes and superfilaments, as a result of coherent motion of clumps due to large-scale inhomogeneities in the initial gravitational potential. It is found that clumps of mass identified in the N-body simulations correspond to several knots in the adhesion model, which influences the way of calculating the mass distribution function. The distribution functions of velocities and masses of clumps and areas of cells in the adhesion model satisfy self-similar scaling laws of the n = 2 model.

Kofman, Lev↗

On chaotic conductivity in the magnetotail

The concept of chaotic conductivity and the acceleration of particles due to a constant dawn dusk electric field are studied in a magnetotail-like magnetic field. A test particle simulation is used including the full nonlinear dynamics. It is found that the acceleration process can be understood without invoking chaos and that the cross tail current is determined by the particle dynamics and distributions. It is concluded that in general there is no simple relationship between the electric field and the current.

Holland, Daniel L.↗

CONCAP 4: A Complex Autonomous Payload (CAP) for growing organic thin films in microgravity

A GAS facility has been developed for carrying out low temperature experiments. The arrangement being used on CONCAP IV-01 is designed for thin film growth in microgravity and can process up to twelve samples per mission. The nonlinear optical oven hardware can also be made suitable for other low temperature applications, such as gradient freeze and solution growth of crystals.

Carswell, W. E.↗

High-resolution gravity model of Venus

The anomalous gravity field of Venus shows high correlation with surface features revealed by radar. We extract gravity models from the Doppler tracking data from the Pioneer Venus Orbiter by means of a two-step process. In the first step, we solve the nonlinear spacecraft state estimation problem using a Kalman filter-smoother. The Kalman filter has been evaluated through simulations. This evaluation and some unusual features of the filter are discussed. In the second step, we perform a geophysical inversion using a linear Bayesian estimator. To allow an unbiased comparison between gravity and topography, we use a simulation technique to smooth and distort the radar topographic data so as to yield maps having the same characteristics as our gravity maps. The maps presented cover 2/3 of the surface of Venus and display the strong topography-gravity correlation previously reported. The topography-gravity scatter plots show two distinct trends.

Reasenberg, R. D.↗

Nonlinear acoustics and the thermal expansivity of glass

The paper shows the intrinsic relationship between acoustical nonlinearity and the thermal expansivity of crystalline solids (a thermal measure of anharmonicity) from consideration of the 'static' radiation field generated by the vibrating lattice (atomic) sources of the crystal. A modification of the theory to account for long-range structural disorder in glass is proposed and applied to an explanation of the zero thermal expansivity at the cross-over temperature in silicate and titanium silicate glasses. Experimental evidence which validates the essential features of the theory is presented. An application of nonlinearity measurement, based on these results, to the processing of ULE glass, where the addition of titanium in various amounts is used to establish the temperature at which the zero thermal expansivity occurs, is suggested.

Cantrell, John H.↗

Venus gravity

The anomalous gravity field of Venus shows high correlation with surface features revealed by radar. We extract gravity models from the Doppler tracking data from the Pioneer Venus Orbiter (PVO) by means of a two-step process. In the first step, we solve the nonlinear spacecraft state estimation problem using a Kalman filter-smoother. The Kalman filter was evaluated through simulations. This evaluation and some unusual features of the filter are discussed. In the second step, we perform a geophysical inversion using a linear Bayesian estimator. To allow an unbiased comparison between gravity and topography, we use a simulation technique to smooth and distort the radar topographic data so as to yield maps having the same characteristics as our gravity maps. The maps presented cover 2/3 of the surface of Venus and display the strong topography-gravity correlation previously reported. The topography-gravity scatter plots show two distinct trends.

Reasenberg, Robert D.↗

Canonical forms of multidimensional steady inviscid flows

Canonical forms and canonical variables for inviscid flow problems are derived. In these forms the components of the system governed by different types of operators (elliptic and hyperbolic) are separated. Both the incompressible and compressible cases are analyzed, and their similarities and differences are discussed. The canonical forms obtained are block upper triangular operator form in which the elliptic and non-elliptic parts reside in different blocks. The full nonlinear equations are treated without using any linearization process. This form enables a better analysis of the equations as well as better numerical treatment. These forms are the analog of the decomposition of the one dimensional Euler equations into characteristic directions and Riemann invariants.

Taasan, Shlomo↗

The Communication Link and Error ANalysis (CLEAN) simulator

During the period July 1, 1993 through December 30, 1993, significant developments to the Communication Link and Error ANalysis (CLEAN) simulator were completed and include: (1) Soft decision Viterbi decoding; (2) node synchronization for the Soft decision Viterbi decoder; (3) insertion/deletion error programs; (4) convolutional encoder; (5) programs to investigate new convolutional codes; (6) pseudo-noise sequence generator; (7) soft decision data generator; (8) RICE compression/decompression (integration of RICE code generated by Pen-Shu Yeh at Goddard Space Flight Center); (9) Markov Chain channel modeling; (10) percent complete indicator when a program is executed; (11) header documentation; and (12) help utility. The CLEAN simulation tool is now capable of simulating a very wide variety of satellite communication links including the TDRSS downlink with RFI. The RICE compression/decompression schemes allow studies to be performed on error effects on RICE decompressed data. The Markov Chain modeling programs allow channels with memory to be simulated. Memory results from filtering, forward error correction encoding/decoding, differential encoding/decoding, channel RFI, nonlinear transponders and from many other satellite system processes. Besides the development of the simulation, a study was performed to determine whether the PCI provides a performance improvement for the TDRSS downlink. There exist RFI with several duty cycles for the TDRSS downlink. We conclude that the PCI does not improve performance for any of these interferers except possibly one which occurs for the TDRS East. Therefore, the usefulness of the PCI is a function of the time spent transmitting data to the WSGT through the TDRS East transponder.

Ebel, William J.↗

Parallelization of a Parabolized Navier-Stokes Solver with a Design Optimizer

The design of future supersonic aircraft, such as the High Speed Civil Transport (HSCT), will rely heavily on computational methods for aircraft design and the prediction of the complex aerodynamics encountered in flight. Parabolized Navier-Stokes (PNS) equation flow solvers are recognized as efficient and accurate computational tools for the solution of supersonic and hypersonic flow-fields, while design optimizers have the potential to be valuable tools within the overall design process. Presently, however, the execution of the flow solver in conjunction with a design optimizer presents a computationally intensive and formidable problem. To meet the challenges and increasing demand for multidisciplinary numerical tools which are faster, more robust and provide greater functionality, alternative strategies are explored to increase computational throughput by coupling a design optimizer and flow solver in a parallel processing environment. To address this problem the parallel processing of a PNS flow solver with a nonlinear constraint design optimizer is investigated as an alternative computational method.

Pallis, J. M.↗

Vapor Flow Patterns During a Start-Up Transient in Heat Pipes

The vapor flow patterns in heat pipes are examined during the start-up transient phase. The vapor core is modelled as a channel flow using a two dimensional compressible flow model. A nonlinear filtering technique is used as a post process to eliminate the non-physical oscillations of the flow variables. For high-input heat flux, multiple shock reflections are observed in the evaporation region. The reflections cause a reverse flow in the evaporation and circulations in the adiabatic region. Furthermore, each shock reflection causes a significant increase in the local pressure and a large pressure drop along the heat pipe.

Issacci, F.↗

Overview of Sensitivity Analysis and Shape Optimization for Complex Aerodynamic Configurations

This paper presents a brief overview of some of the more recent advances in steady aerodynamic shape-design sensitivity analysis and optimization, based on advanced computational fluid dynamics. The focus here is on those methods particularly well- suited to the study of geometrically complex configurations and their potentially complex associated flow physics. When nonlinear state equations are considered in the optimization process, difficulties are found in the application of sensitivity analysis. Some techniques for circumventing such difficulties are currently being explored and are included here. Attention is directed to methods that utilize automatic differentiation to obtain aerodynamic sensitivity derivatives for both complex configurations and complex flow physics. Various examples of shape-design sensitivity analysis for unstructured-grid computational fluid dynamics algorithms are demonstrated for different formulations of the sensitivity equations. Finally, the use of advanced, unstructured-grid computational fluid dynamics in multidisciplinary analyses and multidisciplinary sensitivity analyses within future optimization processes is recommended and encouraged.

Newman, Perry A.↗

Overview of Sensitivity Analysis and Shape Optimization for Complex Aerodynamic Configurations

This paper presents a brief overview of some of the more recent advances in steady aerodynamic shape-design sensitivity analysis and optimization, based on advanced computational fluid dynamics (CFD). The focus here is on those methods particularly well-suited to the study of geometrically complex configurations and their potentially complex associated flow physics. When nonlinear state equations are considered in the optimization process, difficulties are found in the application of sensitivity analysis. Some techniques for circumventing such difficulties are currently being explored and are included here. Attention is directed to methods that utilize automatic differentiation to obtain aerodynamic sensitivity derivatives for both complex configurations and complex flow physics. Various examples of shape-design sensitivity analysis for unstructured-grid CFD algorithms are demonstrated for different formulations of the sensitivity equations. Finally, the use of advanced, unstructured-grid CFDs in multidisciplinary analyses and multidisciplinary sensitivity analyses within future optimization processes is recommended and encouraged.

Newman, James C., III↗

Fast Quantum Algorithm for Predicting Descriptive Statistics of Stochastic Processes

Stochastic processes are used as a modeling tool in several sub-fields of physics, biology, and finance. Analytic understanding of the long term behavior of such processes is only tractable for very simple types of stochastic processes such as Markovian processes. However, in real world applications more complex stochastic processes often arise. In physics, the complicating factor might be nonlinearities; in biology it might be memory effects; and in finance is might be the non-random intentional behavior of participants in a market. In the absence of analytic insight, one is forced to understand these more complex stochastic processes via numerical simulation techniques. In this paper we present a quantum algorithm for performing such simulations. In particular, we show how a quantum algorithm can predict arbitrary descriptive statistics (moments) of N-step stochastic processes in just O(square root of N) time. That is, the quantum complexity is the square root of the classical complexity for performing such simulations. This is a significant speedup in comparison to the current state of the art.

Williams Colin P.↗

The Investigation of the Effects of Gravity on Single Bubble Sonoluminescence

In single bubble following it's rapid collapse each cycle of oscillation of an ultrasonic field. Since widely varying length and time scales affect the bubble dynamics and optical emission processes, it is difficult to anticipate the importance of the effects of gravity present for observations on earth. Our bubble is driven in an acoustically resonating cavity at it's first harmonic mode. The acoustical radiation pressure (Bjerknes force) will then keep it suspended in the center near the pressure antinode. When driven in a region where the diffusive processes balance the bubble it acts in a nonlinear but regular way, emitting a short (approx. 200ps) burst of light each acoustic cycle. Balancing the Bjerknes force with buoyancy, as in, we can see that the bubble should be displaced from the velocity node approximately 20m at normal gravity. Therefore, water flows past the bubble at the time of collapse. Gravitation also changes the ambient pressure at the bubble's location, as Delta.P = rho.g.h this gives a change of approximately -0.5% in our experiment when going from 1.8g to 0g. Studies of ambient pressure changes were also done in order to assess these effects. Inside a pressure sealed chamber a spherical glass cell is filled with distilled water which has been degassed to 120mmHg. A bubble is then trapped in the center and driven by a piezoelectric transducer at 32.2kHz attached to the side of the cell. An optical system is then set up to take strobbed video images along and light emission data simultaneously. Temperature, pressure, drive voltage, and listener voltage are also monitored. PMT output in Volts The radii of the bubbles for both experiment s are fit using the Rayleigh-Plesset equation and the acoustic drive amplitude and the ambient bubble radius are found. There is little change in the acoustic drive amplitude as we expect, since we are not varying the drive voltage. However. the ambient bubble radius goes up considerably. These changes (increased light output, increased maximum bubble radius, and increased ambient bubble radius) are also observed when the ambient pressure is varied in the laboratory by an amount similar to that due to gravitation. The changes in the ambient bubble radius and light output with a change in ambient pressure are predicted by the "dissociation hypothesis" and have been observed by other groups in the laboratory. It seems clear that buoyancy's effect on light output and bubble radius, are at best on the same order as the effects of ambient pressure.

Dzikowicz, Ben↗

Detection in fixed and random noise in foveal and parafoveal vision explained by template learning

Foveal and parafoveal contrast detection thresholds for Gabor and checkerboard targets were measured in white noise by means of a two-interval forced-choice paradigm. Two white-noise conditions were used: fixed and twin. In the fixed noise condition a single noise sample was presented in both intervals of all the trials. In the twin noise condition the same noise sample was used in the two intervals of a trial, but a new sample was generated for each trial. Fixed noise conditions usually resulted in lower thresholds than twin noise. Template learning models are presented that attribute this advantage of fixed over twin noise either to fixed memory templates' reducing uncertainty by incorporation of the noise or to the introduction, by the learning process itself, of more variability in the twin noise condition. Quantitative predictions of the template learning process show that it contributes to the accelerating nonlinear increase in performance with signal amplitude at low signal-to-noise ratios.

NASA Center ARC↗

A Fundamental Mathematical Model of a Microbial Predenitrification System

Space flight beyond Low Earth Orbit requires sophisticated systems to support all aspects of the mission (life support, real-time communications, etc.). A common concern that cuts across all these systems is the selection of information technology (IT) methodology, software and hardware architectures to provide robust monitoring, diagnosis, and control support. Another dimension of the problem space is that different systems must be integrated seamlessly so that communication speed and data handling appear as a continuum (un-interrupted). One such team investigating this problem is the Advanced Integration Matrix (AIM) team whose role is to define the critical requirements expected of software and hardware to support an integrated approach to the command and control of Advanced Life Support (ALS) for future long-duration human space missions, including permanent human presence on the Moon and Mars. A goal of the AIM team is to set the foundation for testing criteria that will assist in specifying tasks, control schemes and test scenarios to validate and verify systems capabilities. This project is to contribute to the goals of the AIM team by assisting with controls planning for ALS. Control for ALS is an enormous problem it involves air revitalization, water recovery, food production, solids processing and crew. In more general terms, these systems can be characterized as involving both continuous and discrete processes, dynamic interactions among the sub-systems, nonlinear behavior due to the complex operations, and a large number of multivariable interactions due to the dimension of the state space. It is imperative that a baseline approach from which to measure performance is established especially when the expectation for the control system is complete autonomous control.

Hoo, Karlene A.↗