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At least 145 records · Page 8

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NASA NTRS2010

Low field SQUID MRI devices, components and methods

Low field SQUID MRI devices, components and methods are disclosed. They include a portable low field (SQUID)-based MRI instrument and a portable low field SQUID-based MRI system to be operated under a bed where a subject is adapted to be located. Also disclosed is a method of distributing wires on an image encoding coil system adapted to be used with an NMR or MRI device for analyzing a sample or subject and a second order superconducting gradiometer adapted to be used with a low field SQUID-based MRI device as a sensing component for an MRI signal related to a subject or sample.

Penanen, Konstantin I.↗

NASA NTRS2011

Low field SQUID MRI devices, components and methods

Penanen, Konstantin I.↗

NASA NTRS2013

Low Field Squid MRI Devices, Components and Methods

Penanen, Konstantin I.↗

NASA NTRS2014

Low Field Squid MRI Devices, Components and Methods

Penanen, Konstantin I.↗

NASA NTRS1991

A solution-adaptive mesh algorithm for dynamic/static refinement of two and three dimensional grids

An adaptive grid algorithm has been developed in two and three dimensions that can be used dynamically with a solver or as part of a grid refinement process. The algorithm employs a transformation from the Cartesian coordinate system to a general coordinate space, which is defined as a parallelepiped in three dimensions. A weighting function, independent for each coordinate direction, is developed that will provide the desired refinement criteria in regions of high solution gradient. The adaptation is performed in the general coordinate space and the new grid locations are returned to the Cartesian space via a simple, one-step inverse mapping. The algorithm for relocation of the mesh points in the parametric space is based on the center of mass for distributed weights. Dynamic solution-adaptive results are presented for laminar flows in two and three dimensions.

Benson, Rusty A.↗

NASA NTRS1990

Quantitative characterization of spatial distribution of particles in materials: Application to materials processing

Most engineering materials contain second phase particles or fibers which serve to reinforce the matrix phase. The effect of reinforcements on material properties is usually analyzed in terms of the average volume fraction and spacing of reinforcements, quantities which are global microstructural characteristics. However, material properties can also depend on local microstructural characteristics; for example, on how uniformly the reinforcing phase is distributed in the material. The analysis method will then be applied to a materials processing problem to discover how processing parameters can be selected to maximize redistribution of the reinforcing phase during processing. Several mathematical analysis methods could be adapted to the problem of characterizing the distribution of particles in materials. A tessellation-based method was selected. In the first phase of the investigation, a software package was written to automate the analysis. Typical results are shown. The analysis technique allows the degree to which particles are clustered together, the size and spacing of particle clusters, and the particle density in clusters to be found. The analysis methods were applied to computer-generated distributions and to a few real particle-containing materials. Methods for analyzing a nonuniform particle distribution in a material can be applied to two broad classes of materials science problems: understanding how the resulting particle distribution affects properties. The analysis method described is applied to a materials processing problem: how to select extrusion conditions to maximize the redistribution of reinforcing particles that are initially nonuniformly distributed. In addition, the tessellation-based method to analyze star distributions in spiral galaxies was adapted, illustrating the diverse types of problems to which the analysis method can be applied.

Parse, J. B.↗

NASA NTRS1993

Adaptive-mesh algorithms for computational fluid dynamics

The basic goal of adaptive-mesh algorithms is to distribute computational resources wisely by increasing the resolution of 'important' regions of the flow and decreasing the resolution of regions that are less important. While this goal is one that is worthwhile, implementing schemes that have this degree of sophistication remains more of an art than a science. In this paper, the basic pieces of adaptive-mesh algorithms are described and some of the possible ways to implement them are discussed and compared. These basic pieces are the data structure to be used, the generation of an initial mesh, the criterion to be used to adapt the mesh to the solution, and the flow-solver algorithm on the resulting mesh. Each of these is discussed, with particular emphasis on methods suitable for the computation of compressible flows.

Powell, Kenneth G.↗

NASA NTRS1999

Automatic Data Distribution for CFD Applications on Structured Grids

Data distribution is an important step in implementation of any parallel algorithm. The data distribution determines data traffic, utilization of the interconnection network and affects the overall code efficiency. In recent years a number data distribution methods have been developed and used in real programs for improving data traffic. We use some of the methods for translating data dependence and affinity relations into data distribution directives. We describe an automatic data alignment and placement tool (ADAPT) which implements these methods and show it results for some CFD codes (NPB and ARC3D). Algorithms for program analysis and derivation of data distribution implemented in ADAPT are efficient three pass algorithms. Most algorithms have linear complexity with the exception of some graph algorithms having complexity O(n(sup 4)) in the worst case.

Frumkin, Michael↗

NASA NTRS1992

Sensor fusion V; Proceedings of the Meeting, Boston, MA, Nov. 15-17, 1992

Topics addressed include 3D object perception, human-machine interface in multisensor systems, sensor fusion architecture, fusion of multiple and distributed sensors, interface and decision models for sensor fusion, computational networks, simple sensing for complex action, multisensor-based control, and metrology and calibration of multisensor systems. Particular attention is given to controlling 3D objects by sketching 2D views, the graphical simulation and animation environment for flexible structure robots, designing robotic systems from sensorimotor modules, cylindrical object reconstruction from a sequence of images, an accurate estimation of surface properties by integrating information using Bayesian networks, an adaptive fusion model for a distributed detection system, multiple concurrent object descriptions in support of autonomous navigation, robot control with multiple sensors and heuristic knowledge, and optical array detectors for image sensors calibration. (No individual items are abstracted in this volume)

Schenker, Paul S.↗

NASA NTRS1981

Contextual classification of multispectral image data - An unbiased estimator for the context distribution

Recent investigations have demonstrated the effectiveness of a contextual classifier that combines spatial and spectral information employing a general statistical approach. This statistical classification algorithm exploits the tendency of certain ground-cover classes to occur more frequently in some spatial contexts than in others. Indeed, a key input to this algorithm is a statistical characterization of the context: the context distribution. Here a discussion is given of an unbiased estimator of the context distribution which, besides having the advantage of statistical unbiasedness, has the additional advantage over other estimation techniques of being amenable to an adaptive implementation in which the context distribution estimate varies according to local contextual information. Results from applying the unbiased estimator to the contextual classification of three real Landsat data sets are presented and contrasted with results from noncontextual classifications and from contextual classifications utilizing other context distribution estimation techniques.

Tilton, J. C.↗

NASA NTRS2015

"Intelligent Ensemble" Projections of Precipitation and Surface Radiation in Support of Agricultural Climate Change Adaptation

Earth's climate is changing and will continue to change into the foreseeable future. Expected changes in the climatological distribution of precipitation, surface temperature, and surface solar radiation will significantly impact agriculture. Adaptation strategies are, therefore, required to reduce the agricultural impacts of climate change. Climate change projections of precipitation, surface temperature, and surface solar radiation distributions are necessary input for adaption planning studies. These projections are conventionally constructed from an ensemble of climate model simulations (e.g., the Coupled Model Intercomparison Project 5 (CMIP5)) as an equal weighted average, one model one vote. Each climate model, however, represents the array of climate-relevant physical processes with varying degrees of fidelity influencing the projection of individual climate variables differently. Presented here is a new approach, termed the "Intelligent Ensemble, that constructs climate variable projections by weighting each model according to its ability to represent key physical processes, e.g., precipitation probability distribution. This approach provides added value over the equal weighted average method. Physical process metrics applied in the "Intelligent Ensemble" method are created using a combination of NASA and NOAA satellite and surface-based cloud, radiation, temperature, and precipitation data sets. The "Intelligent Ensemble" method is applied to the RCP4.5 and RCP8.5 anthropogenic climate forcing simulations within the CMIP5 archive to develop a set of climate change scenarios for precipitation, temperature, and surface solar radiation in each USDA Farm Resource Region for use in climate change adaptation studies.

Taylor, Patrick C.↗

NASA NTRS1996

A Structured Grid Based Solution-Adaptive Technique for Complex Separated Flows

The objective of this work was to enhance the predictive capability of widely used computational fluid dynamic (CFD) codes through the use of solution adaptive gridding. Most problems of engineering interest involve multi-block grids and widely disparate length scales. Hence, it is desirable that the adaptive grid feature detection algorithm be developed to recognize flow structures of different type as well as differing intensity, and adequately address scaling and normalization across blocks. In order to study the accuracy and efficiency improvements due to the grid adaptation, it is necessary to quantify grid size and distribution requirements as well as computational times of non-adapted solutions. Flow fields about launch vehicles of practical interest often involve supersonic freestream conditions at angle of attack exhibiting large scale separate vortical flow, vortex-vortex and vortex-surface interactions, separated shear layers and multiple shocks of different intensity. In this work, a weight function and an associated mesh redistribution procedure is presented which detects and resolves these features without user intervention. Particular emphasis has been placed upon accurate resolution of expansion regions and boundary layers. Flow past a wedge at Mach=2.0 is used to illustrate the enhanced detection capabilities of this newly developed weight function.

Thornburg, Hugh↗

NASA NTRS1981

Contextual classification of multispectral image data: An unbiased estimator for the context distribution

A key input to a statistical classification algorithm, which exploits the tendency of certain ground cover classes to occur more frequently in some spatial context than in others, is a statistical characterization of the context: the context distribution. An unbiased estimator of the context distribution is discussed which, besides having the advantage of statistical unbiasedness, has the additional advantage over other estimation techniques of being amenable to an adaptive implementation in which the context distribution estimate varies according to local contextual information. Results from applying the unbiased estimator to the contextual classification of three real LANDSAT data sets are presented and contrasted with results from non-contextual classifications and from contextual classifications utilizing other context distribution estimation techniques.

Tilton, J. C.↗

NASA NTRS1991

From biological neural networks to thinking machines: Transitioning biological organizational principles to computer technology

The three-dimensional organization of the vestibular macula is under study by computer assisted reconstruction and simulation methods as a model for more complex neural systems. One goal of this research is to transition knowledge of biological neural network architecture and functioning to computer technology, to contribute to the development of thinking computers. Maculas are organized as weighted neural networks for parallel distributed processing of information. The network is characterized by non-linearity of its terminal/receptive fields. Wiring appears to develop through constrained randomness. A further property is the presence of two main circuits, highly channeled and distributed modifying, that are connected through feedforward-feedback collaterals and biasing subcircuit. Computer simulations demonstrate that differences in geometry of the feedback (afferent) collaterals affects the timing and the magnitude of voltage changes delivered to the spike initiation zone. Feedforward (efferent) collaterals act as voltage followers and likely inhibit neurons of the distributed modifying circuit. These results illustrate the importance of feedforward-feedback loops, of timing, and of inhibition in refining neural network output. They also suggest that it is the distributed modifying network that is most involved in adaptation, memory, and learning. Tests of macular adaptation, through hyper- and microgravitational studies, support this hypothesis since synapses in the distributed modifying circuit, but not the channeled circuit, are altered. Transitioning knowledge of biological systems to computer technology, however, remains problematical.

Ross, Muriel D.↗

NASA NTRS1994

Low-Flow-Rate Dry-Powder Feeder

Apparatus feeds small, precise flow of dry powder through laser beam of optical analyzer measuring patterns of light created by forward scattering (Fraunhofer diffraction) of laser beam from powder particles. From this optical measurement, statistical distribution of sizes of powder particles computed. Rates of flow optimized for measurement of particle-size distributions. Developed for analyzing particle-size distributions of solid-propellant powders. Also adapted to pharmaceutical industry, in manufacture of metal powder, and in other applications where particle-size distributions of materials used to control rates of chemical reactions and/or physical characteristics of processes.

Ramsey, Keith E.↗

NASA NTRS1989

Application of a self-adaptive grid method to complex flows

A directional-split, modular, user-friendly grid point distribution code is applied to several test problems. The code is self-adaptive in the sense that grid point spacing is determined by user-specified constants denoting maximum and minimum grid spacings and constants relating the relative influence of smoothness and orthogonality. Estimates of truncation error, in terms of flow-field gradients and/or geometric features, are used to determine the point distribution. Points are redistributed along grid lines in a specified direction in an elliptic manner over a user-specified subdomain, while orthogonality and smoothness are controlled in a parabolic (marching) manner in the remaining directions. Multidirectional adaption is achieved by sequential application of the method in each coordinate direction. The flow-field solution is redistributed onto the newly distributed grid points after each unidirectional adaption by a simple one-dimensional interpolation scheme. For time-accurate schemes such interpolation is not necessary and time-dependent metrics are carried in the fluid dynamic equations to account for grid movement.

Deiwert, G. S.↗

NASA NTRS1974

Energy transfer in volume-reflecting heat shields

An approximate analysis of radiative transfer in highly scattering materials was developed based on the Kubelka-Munk differential equations--a set of two differential equations representing the spatial rate of change of radiative half-fluxes within the scattering media. These approximate solutions of the Kubelka-Munk equations together with analytic solutions for the steady state temperature distribution for two types of boundary conditions are given. These solutions show the influence of back surface reflectance, scattering power, incident radiative flux parameter and boundary conductive flux parameter on overall reflectance and temperature distributions. This radiation field analysis, adapted to spherical geometry, was applied to the evaluation of the thermal performance of teflon and fritted quartz as heat protection materials for entry into the atmosphere of Jupiter.

Weston, K. C.↗

NASA NTRS1989

Design of a structural and functional hierarchy for planning and control of telerobotic systems

Hierarchical structures offer numerous advantages over conventional structures for the control of telerobotic systems. A hierarchically organized system can be controlled via undetailed task assignments and can easily adapt to changing circumstances. The distributed and modular structure of these systems also enables fast response needed in most telerobotic applications. On the other hand, most of the hierarchical structures proposed in the literature are based on functional properties of a system. These structures work best for a few given functions of a large class of systems. In telerobotic applications, all functions of a single system needed to be explored. This approach requires a hierarchical organization based on physical properties of a system and such a hierarchical organization is introduced. The decomposition, organization, and control of the hierarchical structure are considered, and a system with two robot arms and a camera is presented.

Acar, Levent↗