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Browsing by Author "Urness, Timothy Matthew"

Now showing 1 - 3 of 3
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    Flow Visualization Using Natural Textures
    (2005-04-15) Urness, Timothy Matthew; Interrante, Victoria; Longmire, Ellen; Marusic, Ivan
    The use of natural textures provides a richly diverse set of possibilities for the visualization of flow data. In this paper, we present methods that utilize the qualities and attributes of natural textures to visualize multiple scalar distributions and multiple vector fields obtained across a 2D domain in a turbulent boundary layer flow. First, we illustrate how different attributes of textures can represent scalar quantities along streamlines. We then present a technique that allows for the perception of two separate vector fields within the same image by utilizing different textures. Finally, we illustrate how textures have the ability to indicate specific regions of interest within flow images.
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    Strategies for the Visualization of Multiple Co-located Vector Fields
    (2005-09-22) Urness, Timothy Matthew; Interrante, Victoria; Longmire, Ellen; Marusic, Ivan; O'Neill, Sean; Jones, Thomas W.
    Fluids research often involves developing theories about the complex relationships between multiple scalar and vector quantities. We discuss strategies for effectively visualizing co-located vector fields, enabling the key physical structures of one vector field to be clearly understood within the context of a related vector field. We describe the range of effects that can be obtained by combining several existing flow visualization techniques for the purposes of analyzing multiple vector fields. Results are shown through two distinctly different scientific applications: the visualization of velocity and vorticity fields in experimentally acquired turbulent boundary layer flow data, and the visualization of velocity and magnetic fields in computational simulations of astrophysical jets.
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    Techniques for Visualizing Multi-Valued Flow Data
    (2003-06-06) Urness, Timothy Matthew
    We present several techniques to effectively visualize multi-valued flow data using contrast, color, 3D visualization, and texture. These methods were developed to facilitate the effective simultaneous visualization ofmultiple derived quantities in experimentally acquired, stereo PIV data of wall-bounded turbulent flow at moderately high Reynolds numbers. Our ultimate goal through this work is to enable researchers to obtain asuccinct, meaningful visual summary of the contents of a dataset through providing techniques that allow the creation of images in which the important features of multiple scalar distributions can be understood bothindependently and in the context of multiple other distributions.