title: Parallel vectors criteria for unsteady flow vortices.
abstract: Feature-based flow visualization is naturally dependent on feature extraction. To extract flow features, often higher-order properties of the flow data are used such as the Jacobian or curvature properties, implicitly describing the flow features in terms of their inherent flow characteristics (e.g., collinear flow and vorticity vectors). In this paper we present recent research which leads to the (not really surprising) conclusion that feature extraction algorithms need to be extended to a time-dependent analysis framework (in terms of time derivatives) when dealing with unsteady flow data. Accordingly, we present two extensions of the parallel vectors based vortex extraction criteria to the time-dependent domain and show the improvements of feature-based flow visualization in comparison to the steady versions of this extraction algorithm both in the context of a high-resolution dataset, i.e., a simulation specifically designed to evaluate our new approach, as well as for a real-world dataset from a concrete application.
authors: Institute of Computer Graphics and Algorithms, Vienna University of Technology, Wien, Austria. raphael@cg.tuwien.ac.at
authors: Raphael
authors: R
authors: Fuchs
authors: Ronald
authors: R
authors: Peikert
authors: Helwig
authors: H
authors: Hauser
authors: Filip
authors: F
authors: Sadlo
authors: Philipp
authors: P
authors: Muigg
mesh_terms: D000465:Algorithms; D003196:Computer Graphics; D003198:Computer Simulation; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008962:Models, Theoretical; D010363:Pattern Recognition, Automated / Q000379:methods*; D012212:Rheology / Q000379:methods*