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., λ2​) and then separates those
vortices with the help of progressive extraction of (λ2​) 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.Comment: Accepted for presentation at IEEE VIS 2023. The paper will appear in
IEEE Transactions on Visualization and Computer Graphic