DocumentCode
964567
Title
Efficient Visualization of Lagrangian Coherent Structures by Filtered AMR Ridge Extraction
Author
Sadlo, F. ; Peikert, R.
Author_Institution
ETH Zurich, Zurich
Volume
13
Issue
6
fYear
2007
Firstpage
1456
Lastpage
1463
Abstract
This paper presents a method for filtered ridge extraction based on adaptive mesh refinement. It is applicable in situations where the underlying scalar field can be refined during ridge extraction. This requirement is met by the concept of Lagrangian coherent structures which is based on trajectories started at arbitrary sampling grids that are independent of the underlying vector field. The Lagrangian coherent structures are extracted as ridges in finite Lyapunov exponent fields computed from these grids of trajectories. The method is applied to several variants of finite Lyapunov exponents, one of which is newly introduced. High computation time due to the high number of required trajectories is a main drawback when computing Lyapunov exponents of 3-dimensional vector fields. The presented method allows a substantial speed-up by avoiding the seeding of trajectories in regions where no ridges are present or do not satisfy the prescribed filter criteria such as a minimum finite Lyapunov exponent.
Keywords
Lyapunov methods; computational fluid dynamics; feature extraction; filtering theory; flow visualisation; mesh generation; Lagrangian coherent structure visualization; adaptive mesh refinement; arbitrary sampling grids; filtered AMR ridge extraction; finite Lyapunov exponent fields; vector fields; Adaptive filters; Adaptive mesh refinement; Computational efficiency; Fluid dynamics; Grid computing; Isosurfaces; Lagrangian functions; Sampling methods; Topology; Visualization; coherent structures; flow visualization; ridge extraction; unsteady vector fields; vector field topology;
fLanguage
English
Journal_Title
Visualization and Computer Graphics, IEEE Transactions on
Publisher
ieee
ISSN
1077-2626
Type
jour
DOI
10.1109/TVCG.2007.70554
Filename
4376174
Link To Document