Extract and Characterize Hairpin Vortices in Turbulent Flows

August 08, 2023 Β· Declared Dead Β· πŸ› IEEE Transactions on Visualization and Computer Graphics

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Authors Adeel Zafar, Di Yang, Guoning Chen arXiv ID 2308.06283 Category cs.HC: Human-Computer Interaction Cross-listed cs.GR Citations 9 Venue IEEE Transactions on Visualization and Computer Graphics Last Checked 4 months ago
Abstract
Hairpin vortices are one of the most important vortical structures in turbulent flows. Extracting and characterizing hairpin vortices provides useful insight into many behaviors in turbulent flows. However, hairpin vortices have complex configurations and might be entangled with other vortices, making their extraction difficult. In this work, we introduce a framework to extract and separate hairpin vortices in shear driven turbulent flows for their study. Our method first extracts general vortical regions with a region-growing strategy based on certain vortex criteria (e.g., $Ξ»_2$) and then separates those vortices with the help of progressive extraction of ($Ξ»_2$) iso-surfaces in a top-down fashion. This leads to a hierarchical tree representing the spatial proximity and merging relation of vortices. After separating individual vortices, their shape and orientation information is extracted. Candidate hairpin vortices are identified based on their shape and orientation information as well as their physical characteristics. An interactive visualization system is developed to aid the exploration, classification, and analysis of hairpin vortices based on their geometric and physical attributes. We also present additional use cases of the proposed system for the analysis and study of general vortices in other types of flows.
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