Advected Tangent Curves: A General Scheme for Characteristic Curves of Flow Fields

Weinkauf, Tino; Hege, Hans-Christian; Theisel, Holger

doi:10.1111/j.1467-8659.2012.03063.x

Cited by 17 publications

(14 citation statements)

References 16 publications

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“…The automatic selection of time‐dependent streak and time surfaces is an unsolved problem of major importance and a fruitful direction for future research. As the recent differential descriptions for streak and time lines [WT10, WHT12] allow for their fast computation, related approaches to the one described in this paper may become feasible for streak and time surfaces, too.…”

Section: Discussionmentioning

confidence: 99%

Sets of Globally Optimal Stream Surfaces for Flow Visualization

Schulze

Esturo²,

Günther

et al. 2014

Computer Graphics Forum

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Stream surfaces are a well‐studied and widely used tool for the visualization of 3D flow fields. Usually, stream surface seeding is carried out manually in time‐consuming trial and error procedures. Only recently automatic selection methods were proposed. Local methods support the selection of a set of stream surfaces, but, contrary to global selection methods, they evaluate only the quality of the seeding lines but not the quality of the whole stream surfaces. Global methods, on the other hand, only support the selection of a single optimal stream surface until now. However, for certain flow fields a single stream surface is not sufficient to represent all flow features. In our work, we overcome this limitation by introducing a global selection technique for a set of stream surfaces. All selected surfaces optimize global stream surface quality measures and are guaranteed to be mutually distant, such that they can convey different flow features. Our approach is an efficient extension of the most recent global selection method for single stream surfaces. We illustrate its effectiveness on a number of analytical and simulated flow fields and analyze the quality of the results in a user study.

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Section: Discussionmentioning

confidence: 99%

Sets of Globally Optimal Stream Surfaces for Flow Visualization

Schulze

Esturo²,

Günther

et al. 2014

Computer Graphics Forum

Self Cite

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“…Thanks to parallel computation on the GPU, the construction of these type of surfaces can be performed in real-time as well [13]. Recently, Weinkauf et al [43] describe a conceptual framework for treating any kind of integral structure in a unified way.…”

Section: Flow Visualization and Integral Structuresmentioning

confidence: 99%

Comparative visualization of multiple time surfaces by planar surface reformation

Brambilla

Angelelli

Andreassen

et al. 2016

2016 IEEE Pacific Visualization Symposium (PacificVis)

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Comparing time surfaces at different integration time points, or from different seeding areas, can provide valuable insight into transport phenomena of fluid flows. Such a comparative study is challenging due to the often convoluted shapes of these surfaces. We propose a new approach for comparative flow visualization based on time surfaces, which exploits the idea of embedding the surfaces in a carefully designed, reformed 2D visualization space. Such an embedding enables new opportunities for comparative flow visualization. We present three different strategies for comparative flow visualization that take advantage of the reformation. By reforming the time surfaces, we not only mitigate occlusion issues, but we can devote also the third dimension of the visualization space to the comparative aspects of the visualization. Our approach is effective in a variety of flow study cases. The direct comparison of individual time surfaces reveals small scale differences and fine details about the fluid's motion. The concurrent study of multiple surface families enables the identification and the comparison of the most prominent motion patterns. This work was developed in close collaboration with an expert in fluid dynamics, who assessed the potential usefulness of this approach in his field.

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“…Instead of applying a pattern from one time step to another, we apply a pattern from a different data set to the square cylinder flow [4,34].…”

Section: Borromean Magnetic Flux Vector Fieldmentioning

confidence: 99%

Multi-field Pattern Matching based on Sparse Feature Sampling

Wang

Seidel

Weinkauf

2016

IEEE Trans. Visual. Comput. Graphics

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We present an approach to pattern matching in 3D multi-field scalar data. Existing pattern matching algorithms work on single scalar or vector fields only, yet many numerical simulations output multi-field data where only a joint analysis of multiple fields describes the underlying phenomenon fully. Our method takes this into account by bundling information from multiple fields into the description of a pattern. First, we extract a sparse set of features for each 3D scalar field using the 3D SIFT algorithm (Scale-Invariant Feature Transform). This allows for a memory-saving description of prominent features in the data with invariance to translation, rotation, and scaling. Second, the user defines a pattern as a set of SIFT features in multiple fields by e.g. brushing a region of interest. Third, we locate and rank matching patterns in the entire data set. Experiments show that our algorithm is efficient in terms of required memory and computational efforts.

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Advected Tangent Curves: A General Scheme for Characteristic Curves of Flow Fields

Cited by 17 publications

References 16 publications

Sets of Globally Optimal Stream Surfaces for Flow Visualization

Sets of Globally Optimal Stream Surfaces for Flow Visualization

Comparative visualization of multiple time surfaces by planar surface reformation

Multi-field Pattern Matching based on Sparse Feature Sampling

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