Development of a Virtual Scientific Visualization Environment for the Analysis of Complex Flows

This project offers a multidisciplinary approach towards the acquisition, analysis and visualization of experimental data that pertain to cardiovascular applications. First and foremost, the capabilities of our Time-Resolved Digital Particle Image Velocimetry (TRDPIV) system were improved, allowing near-wall wall TRDPIV on compliant, dynamically moving boundaries. As a result, false flow-field vectors due to reflections from the boundary walls were eliminated, and allowing measurement of wall shear stress, wall shear rate, and oscillating shear index within as little as fifty microns of the boundary. Similar in-vitro measurements have not been reported to date by any other group. Second, an immersive, virtual environment (VE) was developed for the investigation and analysis of vortical, spatio-temporally developing flows with complex fluid-structure interactions. This VE was used to study flows in the cardiovascular system, particularly for flow through mechanical heart valves and inside the heart left ventricle (LV). The simulation provides three-dimensional (3-D) visualization of in-vitro heart flow mechanics, allowing global, volumetric flow analysis, and a useful environment for comparison with in-vivo MRI velocimetry data. 3-D glyphs (symbols representing informational parameters) are used to visually represent the flow parameters in the form of an ellipse attached to a cone, where the ellipse represents a second-order Reynolds stress tensor, and the cone represents the velocity magnitude and direction at a particular point in space, and the color corresponds to an out-of-plane vorticity. This new system has a major advantage over conventional 2-D systems in that it successfully doubles the number of visualized parameters, and allows for visualization of a time-dependent series of flow data in the Virginia Tech CAVETM immersive VE. The user controls his/her viewpoint, and can thus navigate through the simulation and view the flow field from any perspective in the immersive VE.

Finally, an edge detection algorithm was developed to determine the inner and outer myocardial boundaries, and from this information calculate the local thickness distribution of the myocardium and a myocardial area approximation. This information is important in validating our in-vitro system, and is integral to the evaluation and diagnosis of congestive heart disease and its progression.