angenommen durch die Fakultät für Informatik

The analysis of flow datasets becomes more and more challenging due to the sheer data size produced by modern simulations and experimental measurements. Feature extrac-tion is necessary for a significant reduction of data fluid mechanicists are faced with. Among a variety of interesting flow features, vortex features are the most prominent. This thesis is devoted to the development of algorithms for vortex feature extraction in 3D and 3D time dependent flow fields. It contains advances in two categories: vortex features defined by swirling motion, and vortex features defined by extremal structures of scalar feature indicators. For the former, we present a novel extraction approach for swirling stream line motion cores in snapshots of the flow field and show how those structures can be tracked in time by appropriate feature flow fields. While this approach is based on stream lines, we extend this work to path lines to extract the center lines of swirling particle motion for the first time. For the latter, we define vortex core lines as ridge lines of certain scalar feature indicators. As this approach requires second derivatives of the scalar, we conclude that a reduction of the require