DocumentCode :
36562
Title :
Exploring Flow Fields Using Space-Filling Analysis of Streamlines
Author :
Chaudhuri, Arindam ; Teng-Yok Lee ; Han-Wei Shen ; Wenger, Rephael
Author_Institution :
Dept. of Comput. Sci. & Eng., Ohio State Univ., Columbus, OH, USA
Volume :
20
Issue :
10
fYear :
2014
fDate :
Oct. 2014
Firstpage :
1392
Lastpage :
1404
Abstract :
Large scale scientific simulations frequently use streamline based techniques to visualize flow fields. As the shape of a streamline is often related to some underlying property of the field, it is important to identify streamlines (or their parts) with unique geometric features. In this paper, we introduce a metric, called the box counting ratio, which measures the geometric complexity of streamlines by measuring their space-filling capacity at different scales. We propose a novel interactive visualization framework which utilizes this metric to extract, organize and visualize features of varying density and complexity hidden in large numbers of streamlines. The proposed framework extracts complex regions of varying density from the streamlines, and organizes and presents them on an interactive 2D information space, allowing user selection and visualization of streamlines. We also extend this framework to support exploration using an ensemble of measures including box counting ratio. Our framework allows the user to easily visualize and interact with features otherwise hidden in large vector field data. We strengthen our claims with case studies using combustion and climate simulation data sets.
Keywords :
computational fluid dynamics; computational geometry; data visualisation; flow visualisation; fractals; box counting ratio; climate simulation data sets; combustion; flow field visualization; interactive 2D information space; interactive visualization framework; space-filling streamline analysis; streamline geometric complexity measurement; streamline selection; streamline visualization; Complexity theory; Feature extraction; Fractals; Measurement; Spirals; Vectors; Flow visualization; box counting ratio; fractal dimension; multi-scale feature detection; streamlines;
fLanguage :
English
Journal_Title :
Visualization and Computer Graphics, IEEE Transactions on
Publisher :
ieee
ISSN :
1077-2626
Type :
jour
DOI :
10.1109/TVCG.2014.2312009
Filename :
6767149
Link To Document :
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