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Static Visualization of Unsteady Flows by Flow Steadification

Authors: Steve Wolligandt; Thomas Wilde; Christian Rössl; Holger Theisel;

Static Visualization of Unsteady Flows by Flow Steadification

Abstract

Finding static visual representations of time-varying phenomena is a standard problem in visualization. We are interested in unsteady flow data, i.e., we want to find a static visualization - one single still image - that shows as much of the global behavior of particle trajectories (path lines) as possible. We propose a new approach, which we call steadification: given a time-dependent flow field v, we construct a new steady vector field w such that the stream lines of w correspond to the path lines of v. With this, the temporal behavior of v can be visualized by using standard methods for steady vector field visualization. We present a formal description as a constraint optimization that can be mapped to finding a set cover, a NP-hard problem that is solved approximately and fairly efficiently by a greedy algorithm. As an application, we introduce the first 2D image-based flow visualization technique that shows the behavior of path lines in a static visualization, even if the path lines have a significantly different behavior than stream lines.

Steve Wolligandt, Thomas Wilde, Christian Rössl, and Holger Theisel

Vision, Modeling, and Visualization

Flow Visualization

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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