199 resultados para vorticity contour visualization


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Visualization of fluids has wide applications in science, engineering and entertainment. Various methodologies Of visualizing fluids have evolved which emphasize on capturing different aspects of the fluids accurately. In this survey the existing methods for realistic visualization of fluids are reviewed. The approaches are classified based on the key concept they rely on for fluid modeling. This classification allows for easy selection of the method to be adopted for visualization given an application. It also enables identification of alternative techniques for fluid modeling.

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Study of symmetric or repeating patterns in scalar fields is important in scientific data analysis because it gives deep insights into the properties of the underlying phenomenon. Though geometric symmetry has been well studied within areas like shape processing, identifying symmetry in scalar fields has remained largely unexplored due to the high computational cost of the associated algorithms. We propose a computationally efficient algorithm for detecting symmetric patterns in a scalar field distribution by analysing the topology of level sets of the scalar field. Our algorithm computes the contour tree of a given scalar field and identifies subtrees that are similar. We define a robust similarity measure for comparing subtrees of the contour tree and use it to group similar subtrees together. Regions of the domain corresponding to subtrees that belong to a common group are extracted and reported to be symmetric. Identifying symmetry in scalar fields finds applications in visualization, data exploration, and feature detection. We describe two applications in detail: symmetry-aware transfer function design and symmetry-aware isosurface extraction.

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In this paper, we explore a novel idea of using high dynamic range (HDR) technology for uncertainty visualization. We focus on scalar volumetric data sets where every data point is associated with scalar uncertainty. We design a transfer function that maps each data point to a color in HDR space. The luminance component of the color is exploited to capture uncertainty. We modify existing tone mapping techniques and suitably integrate them with volume ray casting to obtain a low dynamic range (LDR) image. The resulting image is displayed on a conventional 8-bits-per-channel display device. The usage of HDR mapping reveals fine details in uncertainty distribution and enables the users to interactively study the data in the context of corresponding uncertainty information. We demonstrate the utility of our method and evaluate the results using data sets from ocean modeling.

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The present paper discusses the flow visualization for turbulent free convection in a tank of water with the bottom surface being a smooth or a grooved surface and the top of the water surface exposed to ambient. The grooved surface is of parallel 90 degrees V-grooves with groove height of 10 mm and groove width of 20 mm. The experiment is carried out with aspect ratio (AR) of 2.9 and Rayleigh number (Ra) in the range, 1.3 x 10(7) - 4 x 10(7). Here AR is the aspect ratio (= width of fluid layer/height of fluid layer). Heat flux at the bottom surface is from electrical heating. From the pH-dye visualization, interesting flow structures are observed and these structures are analyzed with the help of plumes dynamics and temperature variations with time. (C) 2011 Elsevier Ltd. All rights reserved.

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Critical applications like cyclone tracking and earthquake modeling require simultaneous high-performance simulations and online visualization for timely analysis. Faster simulations and simultaneous visualization enable scientists provide real-time guidance to decision makers. In this work, we have developed an integrated user-driven and automated steering framework that simultaneously performs numerical simulations and efficient online remote visualization of critical weather applications in resource-constrained environments. It considers application dynamics like the criticality of the application and resource dynamics like the storage space, network bandwidth and available number of processors to adapt various application and resource parameters like simulation resolution, simulation rate and the frequency of visualization. We formulate the problem of finding an optimal set of simulation parameters as a linear programming problem. This leads to 30% higher simulation rate and 25-50% lesser storage consumption than a naive greedy approach. The framework also provides the user control over various application parameters like region of interest and simulation resolution. We have also devised an adaptive algorithm to reduce the lag between the simulation and visualization times. Using experiments with different network bandwidths, we find that our adaptive algorithm is able to reduce lag as well as visualize the most representative frames.

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Western Blot analysis is an analytical technique used in Molecular Biology, Biochemistry, Immunogenetics and other Molecular Biology studies to separate proteins by electrophoresis. The procedure results in images containing nearly rectangular-shaped blots. In this paper, we address the problem of quantitation of the blots using automated image processing techniques. We formulate a special active contour (or snake) called Oblong, which locks on to rectangular shaped objects. Oblongs depend on five free parameters, which is also the minimum number of parameters required for a unique characterization. Unlike many snake formulations, Oblongs do not require explicit gradient computations and therefore the optimization is carried out fast. The performance of Oblongs is assessed on synthesized data and Western Blot Analysis images.

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Adaptive Mesh Refinement is a method which dynamically varies the spatio-temporal resolution of localized mesh regions in numerical simulations, based on the strength of the solution features. In-situ visualization plays an important role for analyzing the time evolving characteristics of the domain structures. Continuous visualization of the output data for various timesteps results in a better study of the underlying domain and the model used for simulating the domain. In this paper, we develop strategies for continuous online visualization of time evolving data for AMR applications executed on GPUs. We reorder the meshes for computations on the GPU based on the users input related to the subdomain that he wants to visualize. This makes the data available for visualization at a faster rate. We then perform asynchronous executions of the visualization steps and fix-up operations on the CPUs while the GPU advances the solution. By performing experiments on Tesla S1070 and Fermi C2070 clusters, we found that our strategies result in 60% improvement in response time and 16% improvement in the rate of visualization of frames over the existing strategy of performing fix-ups and visualization at the end of the timesteps.

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Identifying symmetry in scalar fields is a recent area of research in scientific visualization and computer graphics communities. Symmetry detection techniques based on abstract representations of the scalar field use only limited geometric information in their analysis. Hence they may not be suited for applications that study the geometric properties of the regions in the domain. On the other hand, methods that accumulate local evidence of symmetry through a voting procedure have been successfully used for detecting geometric symmetry in shapes. We extend such a technique to scalar fields and use it to detect geometrically symmetric regions in synthetic as well as real-world datasets. Identifying symmetry in the scalar field can significantly improve visualization and interactive exploration of the data. We demonstrate different applications of the symmetry detection method to scientific visualization: query-based exploration of scalar fields, linked selection in symmetric regions for interactive visualization, and classification of geometrically symmetric regions and its application to anomaly detection.

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In this paper, we present the molecular density distribution measurement in turbulent nitrogen jet (Re approximate to 3 x 10(3)), using acetone as molecular tracer. The tracer was seeded in the nitrogen jet by purging through the liquid acetone at ambient temperature. Planar laser sheet of 266 nm wavelength from frequency quadrupled, Q-switched, Nd:YAG laser was used as an excitation source. Emitted fluorescence images of jet flow field were recorded on CMOS camera. The dependence of planar laser induced fluorescence (PLIF) intensity on acetone vapor density was used to convert PLIF image of nitrogen jet into the density image on pixel-by-pixel basis. Instantaneous quantitative density image of nitrogen jet, seeded with acetone, was obtained. The arrowhead-shaped coherent turbulent structures were observed in the present work. It was found that coherent structures were non-overlapping with separate boundaries. Breaking of coherent structures into turbulence was clearly observed above four times jet width.