Delocalized Unsteady Vortex Region Detectors

In this paper we discuss generalizations of instantaneous, local vortex criteria. We incorporate information on spatial context and temporal development into the detection process. The presented method is generic in so far that it can extend any given Eulerian criterion to take the Lagrangian approach into account. Furthermore, we present a visual aid to understand and steer the feature extraction process. We show that the delocalized detectors are able to distinguish between connected vortices and help understanding regions of multiple interacting vortex structures. The delocalized detectors extract smoother structures and reduce noise in the vortex detection result.

[1]  Helwig Hauser,et al.  Integrating Local Feature Detectors in the Interactive Visual Analysis of Flow Simulation Data , 2007, EuroVis.

[2]  Hans-Peter Seidel,et al.  Finite-Time Transport Structures of Flow Fields , 2008, 2008 IEEE Pacific Visualization Symposium.

[3]  F. A. Seiler,et al.  Numerical Recipes in C: The Art of Scientific Computing , 1989 .

[4]  Joerg Meyer,et al.  Pathline predicates and unsteady flow structures , 2008, The Visual Computer.

[5]  Rüdiger Westermann,et al.  A particle system for interactive visualization of 3D flows , 2005, IEEE Transactions on Visualization and Computer Graphics.

[6]  Melissa A. Green,et al.  Detection of Lagrangian coherent structures in three-dimensional turbulence , 2007, Journal of Fluid Mechanics.

[7]  R. Cucitore,et al.  On the effectiveness and limitations of local criteria for the identification of a vortex , 1999 .

[8]  Helwig Hauser,et al.  Parallel Vectors Criteria for Unsteady Flow Vortices , 2008, IEEE Transactions on Visualization and Computer Graphics.

[9]  H. Lugt Wirbelströmung in Natur und Technik , 1979 .

[10]  Brian Cabral,et al.  Imaging vector fields using line integral convolution , 1993, SIGGRAPH.

[11]  Filip Sadlo,et al.  Visualizing Lagrangian Coherent Structures and Comparison to Vector Field Topology , 2009, Topology-Based Methods in Visualization II.

[12]  Robert S. Laramee,et al.  The State of the Art in Flow Visualisation: Feature Extraction and Tracking , 2003, Comput. Graph. Forum.

[13]  Frits H. Post,et al.  Geometric Methods for Vortex Extraction , 1999 .

[14]  D. Sujudi,et al.  Identification of Swirling Flow in 3-D Vector Fields , 1995 .

[15]  G. Haller An objective definition of a vortex , 2004, Journal of Fluid Mechanics.

[16]  Hans Hagen,et al.  Efficient Computation and Visualization of Coherent Structures in Fluid Flow Applications , 2007, IEEE Transactions on Visualization and Computer Graphics.

[17]  David L. Kao,et al.  UFLIC: a line integral convolution algorithm for visualizing unsteady flows , 1997 .

[18]  Hans Hagen,et al.  Visualization of Coherent Structures in Transient 2D Flows , 2009, Topology-Based Methods in Visualization II.

[19]  G. Batchelor,et al.  An Introduction to Fluid Dynamics , 1968 .

[20]  Hans-Peter Seidel,et al.  Path Line Attributes - an Information Visualization Approach to Analyzing the Dynamic Behavior of 3D Time-Dependent Flow Fields , 2009, Topology-Based Methods in Visualization II.

[21]  William H. Press,et al.  Numerical recipes in C. The art of scientific computing , 1987 .

[22]  Hans-Christian Hege,et al.  Vortex and Strain Skeletons in Eulerian and Lagrangian Frames , 2007, IEEE Transactions on Visualization and Computer Graphics.

[23]  Filip Sadlo,et al.  Efficient Visualization of Lagrangian Coherent Structures by Filtered AMR Ridge Extraction , 2007, IEEE Transactions on Visualization and Computer Graphics.

[24]  Raghu Machiraju,et al.  Geometric verification of swirling features in flow fields , 2002, IEEE Visualization, 2002. VIS 2002..