Article

Lagrangian-Eulerian advection for unsteady flow visualization

Authors:

Bruno Jobard,

Gordon Erlebacher,

M. Yousuff HussainiAuthors Info & Claims

VIS '01: Proceedings of the conference on Visualization '01

Pages 53 - 60

Published: 21 October 2001 Publication History

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Abstract

In this paper, we propose a new technique to visualize dense representations of time-dependent vector fields based on a Lagrangian-Eulerian Advection (LEA) scheme. The algorithm produces animations with high spatio-temporal correlation at interactive rates. With this technique, every still frame depicts the instantaneous structure of the flow, whereas an animated sequence of frames reveals the motion a dense collection of particles would take when released into the flow. The simplicity of both the resulting data structures and the implementation suggest that LEA could become a useful component of any scientific visualization toolkit concerned with the display of unsteady flows.

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Kim MKlasky SPugmire DHentschel BChilds HCucchietti F(2018)Dense texture flow visualization using data-parallel primitivesProceedings of the Symposium on Parallel Graphics and Visualization10.5555/3293524.3293529(57-61)Online publication date: 4-Jun-2018
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Pereira ECardoso JMorla R(2016)Long-range trajectories from global and local motion representationsJournal of Visual Communication and Image Representation10.1016/j.jvcir.2016.06.02040:PA(265-287)Online publication date: 1-Oct-2016
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Lagrangian-Eulerian advection for unsteady flow visualization

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Information

Published In

VIS '01: Proceedings of the conference on Visualization '01

October 2001

607 pages

ISBN:078037200X

Conference Chairs:
Mike Bailey
San Diego Supercomputer Center
,
Charles Hansen
University of Utah
,
Program Chairs:
Hanspeter Pfister
Mitsubishi Electric Research Laboratories
,
Edward Swan
The Naval Research Laboratory

Publisher

IEEE Computer Society

United States

Publication History

Published: 21 October 2001

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VIS01: IEEE Visualization 2001

October 21 - 26, 2001

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Kim MKlasky SPugmire DHentschel BChilds HCucchietti F(2018)Dense texture flow visualization using data-parallel primitivesProceedings of the Symposium on Parallel Graphics and Visualization10.5555/3293524.3293529(57-61)Online publication date: 4-Jun-2018
https://dl.acm.org/doi/10.5555/3293524.3293529
Pereira ECardoso JMorla R(2016)Long-range trajectories from global and local motion representationsJournal of Visual Communication and Image Representation10.1016/j.jvcir.2016.06.02040:PA(265-287)Online publication date: 1-Oct-2016
https://dl.acm.org/doi/10.1016/j.jvcir.2016.06.020
Rodr�guez-Cerro AGarc�a-Fern�ndez IMart�nez-Dur� RPla-Castells M(2015)Texture advection on discontinuous flowsThe Visual Computer: International Journal of Computer Graphics10.1007/s00371-015-1118-731:6-8(1033-1043)Online publication date: 1-Jun-2015
https://dl.acm.org/doi/10.1007/s00371-015-1118-7
Edmunds MLaramee RChen GMax NZhang EWare C(2012)Technical SectionComputers and Graphics10.1016/j.cag.2012.07.00636:8(974-990)Online publication date: 1-Dec-2012
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Li GTricoche XHansen C(2008)Physically-based dye advection for flow visualizationProceedings of the 10th Joint Eurographics / IEEE - VGTC conference on Visualization10.1111/j.1467-8659.2008.01201.x(727-734)Online publication date: 26-May-2008
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