Extracting feature lines from 3D unstructured grids
VIS '97 Proceedings of the 8th conference on Visualization '97
Tracking scalar features in unstructured datasets
Proceedings of the conference on Visualization '98
A higher-order method for finding vortex core lines
Proceedings of the conference on Visualization '98
The “parallel vectors” operator: a vector field visualization primitive
VIS '99 Proceedings of the conference on Visualization '99: celebrating ten years
`` Direct Search'' Solution of Numerical and Statistical Problems
Journal of the ACM (JACM)
A novel approach to vortex core region detection
VISSYM '02 Proceedings of the symposium on Data Visualisation 2002
Vortex tracking in scale-space
VISSYM '02 Proceedings of the symposium on Data Visualisation 2002
Geometric verification of swirling features in flow fields
Proceedings of the conference on Visualization '02
A Predictor-Corrector Technique for Visualizing Unsteady Flow
IEEE Transactions on Visualization and Computer Graphics
Feature Extraction and Iconic Visualization
IEEE Transactions on Visualization and Computer Graphics
An Efficient k-Means Clustering Algorithm: Analysis and Implementation
IEEE Transactions on Pattern Analysis and Machine Intelligence
A feature-based approach to visualizing and mining simulation data
A feature-based approach to visualizing and mining simulation data
Surface techniques for vortex visualization
VISSYM'04 Proceedings of the Sixth Joint Eurographics - IEEE TCVG conference on Visualization
Probabilistic Local Features in Uncertain Vector Fields with Spatial Correlation
Computer Graphics Forum
Hierarchical vortex regions in swirling flow
EuroVis'09 Proceedings of the 11th Eurographics / IEEE - VGTC conference on Visualization
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In order to understand complex vortical flows in large data sets, we must be able to detect and visualize vortices in an automated fashion. In this paper, we present a feature-based vortex detection and visualization technique that is appropriate for large computational fluid dynamics data sets computed on unstructured meshes. In particular, we focus on the application of this technique to visualization of the flow over a serrated wing and the flow field around a spinning missile with dithering canards. We have developed a core line extraction technique based on the observation that vortex cores coincide with local extrema in certain scalar fields. We also have developed a novel technique to handle complex vortex topology that is based on k-means clustering. These techniques facilitate visualization of vortices in simulation data that may not be optimally resolved or sampled. Results are included that highlight the strengths and weaknesses of our approach. We conclude by describing how our approach can be improved to enhance robustness and expand its range of applicability.