Using potential theory and dense texture-based visualization for external motion applications

We propose a novel methodology that uses potential theory and a texture-based algorithm to produce dense smooth visualization of steady and unsteady flow fields. Given a chosen pattern, the flow field expression $potentially varying over time - determines how it has to be adapted and controlled locally to generate a dense visualization. We use this methodology for the visualization of external motion, and give a practical solution for special application cases. External motion is intended to describe the motion of a fluid around an object, or, similarly, the motion of an object immersed in a still fluid. This approach is general and produces flow visualization in an intuitive and straightforward way. User intervention and degrees of freedom are offered as well. Significant applications can be found in many scientific areas, including engineering in general, physics, magnetisms, aero- and fluid dynamics, medical visualization and meteorology. Relevant examples are the study of wind interaction against buildings, air about airfoils, water around bridge piers