Vortex Identification from Local Properties of the Vorticity Field
J.H. Elsas, L. Moriconi

TL;DR
This paper introduces a new vortex identification method based on local vorticity curvature, which outperforms traditional criteria in complex flow scenarios and aligns with turbulence theory.
Contribution
It proposes the $oldsymbol{ ext{vorticity curvature criterion}}$ ($oldsymbol{ ext{}}oldsymbol{\lambda_oldsymbol{ extomega}}oldsymbol{ ext{-criterion}}$), a novel vortex detection scheme based on local vorticity properties, improving accuracy over existing methods.
Findings
The $oldsymbol{ ext{ extlambda}_ ext{ extomega}}$-criterion effectively detects vortices in complex flows.
It handles strong shear effects with background velocity subtraction.
The method reveals small-scale turbulence in DNS of channel flow.
Abstract
It has been broadly acknowledged that vortex detection algorithms, usually based on linear-algebraic properties of the velocity gradient tensor, can be plagued with severe shortcomings and may become, in practical terms, dependent on the choice of subjective threshold parameters in their implementations. In two-dimensions, a large class of standard vortex identification prescriptions turn out to be equivalent to the "swirling strength criterion" (-criterion), which is critically revisited in this work. We classify the instances where the accuracy of the -criterion is affected by nonlinear superposition effects and propose an alternative vortex detection scheme based on the local curvature properties of the vorticity graph -- the "vorticity curvature criterion" (-criterion) -- which improves over the results obtained with the…
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