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

Laramee, Robert S.; Hauser, Helwig; Doleisch, Helmut; Vrolijk, Benjamin; Post, Frits H.; Weiskopf, Daniel

doi:10.1111/j.1467-8659.2004.00753.x

Cited by 293 publications

(154 citation statements)

References 68 publications

(155 reference statements)

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“…These approaches are related to LagrangianEulerian Advection (LEA) [6]. We note that a full comparison of texture-based flow visualization techniques [8] is beyond the scope of this paper.…”

Section: Direct Geometric and Texture-based Flow Visualizationmentioning

confidence: 99%

Investigating swirl and tumble flow with a comparison of visualization techniques

Laramee

Weiskopf

Schneider³

et al.

IEEE Visualization 2004

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Figure 1: Visualization of swirl and tumble flow using a combination of direct color-mapping, streamlines, isosurfaces, texture-based flow visualization and slicing. (Left) visualizing swirl flow using 3D streamlines and texture-based flow visualization on an isosurface, (middle-left) a clipping plane is applied to reveal occluded flow structures, (middle-right) an isosurface and 3D streamlines visualize tumble motion, and (right) the addition of texture-based flow visualization on a color-mapped slice. ABSTRACTWe investigate two important, common fluid flow patterns from computational fluid dynamics (CFD) simulations, namely, swirl and tumble motion typical of automotive engines. We study and visualize swirl and tumble flow using three different flow visualization techniques: direct, geometric, and texture-based. When illustrating these methods side-by-side, we describe the relative strengths and weaknesses of each approach within a specific spatial dimension and across multiple spatial dimensions typical of an engineer's analysis. Our study is focused on steady-state flow. Based on this investigation we offer perspectives on where and when these techniques are best applied in order to visualize the behavior of swirl and tumble motion.

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Section: Direct Geometric and Texture-based Flow Visualizationmentioning

confidence: 99%

Investigating swirl and tumble flow with a comparison of visualization techniques

Laramee

Weiskopf

Schneider³

et al.

IEEE Visualization 2004

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“…There has been extensive work in vector field analysis and flow visualization [20], [21]. However, relatively little work has been done in the area of flow analysis by studying the structures in the gradient tensor, an asymmetric tensor field.…”

Section: Previous Workmentioning

confidence: 99%

Asymmetric Tensor Analysis for Flow Visualization

Zhang

Yeh

Lin

et al. 2009

IEEE Trans. Visual. Comput. Graphics

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Abstract-The gradient of a velocity vector field is an asymmetric tensor field which can provide critical insight that is difficult to infer from traditional trajectory-based vector field visualization techniques. We describe the structures in the eigenvalue and eigenvector fields of the gradient tensor and how these structures can be used to infer the behaviors of the velocity field that can represent either a 2D compressible flow or the projection of a 3D compressible or incompressible flow onto a 2D manifold. To illustrate the structures in asymmetric tensor fields, we introduce the notions of eigenvalue manifold and eigenvector manifold. These concepts afford a number of theoretical results that clarify the connections between symmetric and antisymmetric components in tensor fields. In addition, these manifolds naturally lead to partitions of tensor fields, which we use to design effective visualization strategies. Moreover, we extend eigenvectors continuously into the complex domains which we refer to as pseudoeigenvectors. We make use of evenly spaced tensor lines following pseudoeigenvectors to illustrate the local linearization of tensors everywhere inside complex domains simultaneously. Both eigenvalue manifold and eigenvector manifold are supported by a tensor reparameterization with physical meaning. This allows us to relate our tensor analysis to physical quantities such as rotation, angular deformation, and dilation, which provide a physical interpretation of our tensor-driven vector field analysis in the context of fluid mechanics. To demonstrate the utility of our approach, we have applied our visualization techniques and interpretation to the study of the Sullivan Vortex as well as computational fluid dynamics simulation data.

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“…where T stands for an input noise texture, k denotes the filter kernel, s is an arc length used to parameterize the streamline curve, and L represents the filter kernel length (Laramee et al, 2004a;Stalling and Hege, 1995). The result of this convolution is streaks in the texture in the direction of the local flow field.…”

Section: Background and Key Developmentsmentioning

confidence: 99%

Applications of Texture-Based Flow Visualization

Laramee

Erlebacher

Garth

et al. 2008

Engineering Applications of Computational Fluid Mechanics

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Flow visualization is a classic sub-field of scientific visualization. The task of flow visualization algorithms is to depict vector data, i.e., data with magnitude and direction. An important category of flow visualization techniques makes use of textures in order to convey the properties of a vector field. Recently, several research advances have been made in this special category, of dense, texture-based techniques. We present the application of the most recent texture-based techniques to real world data from oceanography and meteorology, computational fluid dynamics (CFD) in the automotive industry, and medicine. We describe the motivations for using texture-based algorithms as well as the important recent advancements required for their successful incorporation into industry grade software. Our goal is to appeal to practitioners in the field interested in learning how these recent techniques can help them gain insight into problems that engineers and other professionals may be faced with on a daily basis. Many of these applications have only recently become possible.

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

Cited by 293 publications

References 68 publications

Investigating swirl and tumble flow with a comparison of visualization techniques

Investigating swirl and tumble flow with a comparison of visualization techniques

Asymmetric Tensor Analysis for Flow Visualization

Applications of Texture-Based Flow Visualization

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