Using Maxima Score for the Extraction and Visualization of Fluid Flow Structures

The extraction of important flow features can facilitate easier cognition of fluid flows, enabling users to improve object/fluid interactions. This paper presents an approach to extract flow features, which can be applied to data of any domain. Our approach uses a normalized "maxima score" for predictable output across datasets. This score is calculated based on a given point's scalar intensity relative to its neighbors. This score can be used to reveal areas of interest within the flow field. We present two techniques for visualization of the maxima score, one based on isosurfaces and one based on edge tracing from image processing. We have successfully applied the maxima score approach to synthetic, computational, and empirical datasets.

[1]  Frits H. Post,et al.  Detection, quantification, and tracking of vortices using streamline geometry , 2000, Comput. Graph..

[2]  Seiichiro Izawa,et al.  Extraction of coherent vortices from homogeneous turbulence using curvelets and total variation filtering methods , 2012 .

[3]  Lijie Xu,et al.  An Information-Theoretic Framework for Flow Visualization , 2010, IEEE Transactions on Visualization and Computer Graphics.

[4]  V. Arnold,et al.  Sur la topologie des écoulements stationnaires des fluides parfaits , 1965 .

[5]  T. Colonius,et al.  Effect of Tip Vortices in Low-Reynolds-Number Poststall Flow Control , 2009 .

[6]  John F. Canny,et al.  A Computational Approach to Edge Detection , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[7]  Roger C. Strawn,et al.  Computer Visualization Of Vortex Wake Systems , 1998 .

[8]  David H. Eberly,et al.  Ridges for image analysis , 1994, Journal of Mathematical Imaging and Vision.

[9]  Robert Michael Kirby,et al.  Comparing 2D vector field visualization methods: a user study , 2005, IEEE Transactions on Visualization and Computer Graphics.

[10]  Konrad Polthier,et al.  Identifying Vector Field Singularities Using a Discrete Hodge Decomposition , 2002, VisMath.

[11]  Gerik Scheuermann,et al.  Measuring Complexity in Lagrangian and Eulerian Flow Descriptions , 2010, Comput. Graph. Forum.

[12]  Jinhee Jeong,et al.  On the identification of a vortex , 1995, Journal of Fluid Mechanics.

[13]  Jun Ma,et al.  A Unified Approach to Streamline Selection and Viewpoint Selection for 3D Flow Visualization , 2013, IEEE Transactions on Visualization and Computer Graphics.

[14]  Gerik Scheuermann,et al.  Multifield visualization using local statistical complexity , 2007, IEEE Transactions on Visualization and Computer Graphics.

[15]  Alain Farcy,et al.  Correlation between vortex structures and unsteady loads for flapping motion in hover , 2009 .

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

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

[18]  Xin,et al.  A quick and feature based visualization algorithm for large-scale flow data , 2009, 2009 IEEE International Geoscience and Remote Sensing Symposium.