Fluid Flow Visualization

Flow visualization has been a very attractive component of scientific visualization research for a long time.Usually very large multivariate datasets require processing. These datasets often consist of a large number of sample locations and several time steps. The steadily increasing performance of computers has recently become a driving factor for a reemergence in flow visualization research, especially in texture-based techniques. In this paper, dense, texture-based flow visualization techniques are discussed. This class of techniques attempts to provide a complete, dense representation of the flow field with high spatio-temporal coherency. An attempt of categorizing closely related solutions is incorporated and presented. Fundamentals are shortly addressed as well as advantages and disadvantages of the methods.

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“…This process is iterated until the target cell is found. More details can be found in text books about flow visualization fundamentals [53,68].…”

Section: Gridsmentioning

confidence: 99%

The State of the Art in Flow Visualization: Dense and Texture‐Based Techniques

Laramee

Hauser

Doleisch

et al. 2004

Computer Graphics Forum

Self Cite

296

152

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“…It was present at the birth of many important fields, most notably the theory of elasticity, the calculus of variations, and the theory of elliptic integrals. The path traced by this curve illuminates a wide range of mathematical style, from the mechanics-based intuition of the early work, through a period of technical virtuosity in mathematical technique, to the present day where computational techniques dominate [16][17][18][19][20].…”

Section: Introductionmentioning

confidence: 99%

On new characterization of inextensible flows of space-like curves in de Sitter space

Yeneroğlu

2016

Open Mathematics

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“…The starting points of streamlets can be thought of as nozzles which periodically introduce dye into the flow. This is an Eulerian approach [12] as opposed to using moving particles, which would be a Lagrangian approach. Moving particles have the disadvantage that depending on the flow field an uneven particle distribution may evolve quite rapidly.…”

Section: Animation Of Frolicmentioning

confidence: 99%

Fast oriented line integral convolution for vector field visualization via the Internet

Wegenkittl¹,

Groller²

Proceedings. Visualization '97 (Cat. No. 97CB36155)

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Oriented Line Integral Convolution (OLIC) illustrates flow fields by convolving a sparse texture with an anisotropic convolution kernel. The kernel is aligned to the underlying flow of the vector field. OLIC does not only show the direction of the flow but also its orientation. This paper presents Fast Rendering of Oriented Line Integral Convolution (FROLIC), which is approximately two orders of magnitude faster than OLIC. Costly convolution operations as done in OLIC are replaced in FROLIC by approximating a streamlet through a set of disks with varying intensity. The issue of overlapping streamlets is discussed. Two efficient animation techniques for animating FROLIC images are described. FROLIC has been implemented as a Java applet. This allows researchers from various disciplines (typically with inhomogenous hardware environments) to conveniently explore and investigate analytically defined 2D vector fields.

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Fluid Flow Visualization

Cited by 42 publications

References 32 publications

The State of the Art in Flow Visualization: Dense and Texture‐Based Techniques

The State of the Art in Flow Visualization: Dense and Texture‐Based Techniques

On new characterization of inextensible flows of space-like curves in de Sitter space

Fast oriented line integral convolution for vector field visualization via the Internet

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