Techniques for Visualizing Multi-Valued Flow Data

Abstract

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.