he study of coherent structures in turbulent boundary layers is an active area of research. Driven by applications including the reduction of turbulent skin-friction drag over aircraft, researchers have long been interested in developing a deeper understanding of the key physical features within turbulent flows. One application of interest is the analysis of multiple scalar and vector distributions and how the interaction of variables contributes to theories of drag and the formation of vortex packets within a turbulent boundary layer. A second application involves examining the correlation between different layers within a numerical simulation of a turbulent channel flow. The analysis of these applications can be greatly facilitated by a better understanding of the complicated interactions that occur between the vortices that make up the motion. Important research conducted in the computational physics field focuses on modeling 3D magnetohydrodynamic light supersonic jets in the context of astrophysical jets in galaxy clusters. These high-speed jets propagate distances of over 650,000 light years from their sources, transporting energy and magnetic fields to their surrounding environments. The jet magnetic field is advected along with the flow and is expected to reflect properties of the evolving velocity field. Of particular interest is the extent to which the magnetic and velocity vector fields are spatially aligned and/or orthogonal to one another and the interplay between magnetic field strength and the corresponding velocity structures. Our research explores strategies for developing effective methods for the visual representation of multiple colocated vector and scalar fields to allow understanding and analyses of each field, both individually and in the context of the other. Mining the knowledge base of previous visualization research yields important findings and insights to assist the research of our specific applications. Using these insights, we can reconstruct, manipulate, and expand upon the existing state of the art to further the knowledge-discovery process related to specific tasks and conditions. Our present efforts focus primarily on the investigation of methods for effectively visualizing multiple fields defined over a 2D domain; the problem of effectively visualizing multiple fields defined over a 3D domain is even more challenging, and an important area for future work. The "Classifying and Combining Visualization Techniques" sidebar presents previous and related work. While it would be possible to compare the orientation between two vector fields by deriving a scalar field based on the dot product of corresponding vectors, it's also critical for our applications to understand the local magnitude, direction, and gradients of each vector field independent of the other. For this reason, we consider techniques for the multiple representation of 2D vector fields. Considering one sample from each of the three visually distinct methods for vector field visualization-texture, glyph, and line (discussed in the sidebar)-we explore the range of effects achievable using layered combinations of these approaches to visualize two colocated vector fields (see Figure 1 on page 76). For the texture-based sample, we use line integral convolution (LIC)-the most widely used texture-based approach. For the glyph-based sample, we create an image by repeatedly texture mapping a comet-like glyph along thick, equally spaced streamlines. This results in a glyph sequence that is continuous in the direction of the flow. We create the linebased sample using the source code supplied by the authors of an equally spaced streamline technique. One primary goal for each application is to depict the key physical structures of one vector field in the context of the key physical structures in another. Therefore, a highly desirable ability is to easily differentiate between the visual representations of each field and to identify each distribution. This process becomes more complicated when we apply the same representational technique (for example, texture, glyph, or line) to each field. While we could use a supplemental visual variable, such as color, to distinguish the two representations, we Strategies for effectively visualizing colocated 2D vector fields enable understanding of key physical structures of one vector field within the context of a related vector field. This article describes the range of effects possible by combining several existing flow visualization techniques for analyzing multiple vector fields.
Combined with overlaying approaches, they can be used to compare small numbers of flow and scalar fields REF .
Strategies for the visualization of multiple 2D vector fields
IEEE Computer Graphics and Applications
IEEE Computer Graphics and Applications
Computer Science Medicine