Stochastic Lagrangian Dynamics of Vorticity. II. Channel-Flow Turbulence
Gregory L. Eyink, Akshat Gupta, and Tamer Zaki

TL;DR
This paper develops a rigorous stochastic Lagrangian framework for vorticity dynamics in turbulent flows, applying it to channel flow data to analyze vortex origins and reconnection processes, revealing distributed vortex lifting and unifying classical and quantum fluid behaviors.
Contribution
It introduces a stochastic Lagrangian theory for vorticity, providing exact expressions and applying them to turbulent channel flow to challenge existing vortex lifting notions.
Findings
Vortex lifting is a distributed process over large space-time regions.
Lagrangian chaos can be explained by virtual reconnection with vorticity cancellation.
The theory unifies classical fluid and superfluid vortex dynamics.
Abstract
We here exploit a rigorous mathematical theory of vorticity dynamics for Navier-Stokes solutions in terms of stochastic Lagrangian flows and their stochastic Cauchy invariants, that are conserved on average backward in time. This theory yields exact expressions for the vorticity inside the flow domain in terms of the vorticity at the wall, as it is transported by viscous diffusion and by nonlinear advection, stretching and rotation. As a concrete application, we exploit an online database of a turbulent channel-flow simulation at (Graham et al. 2016) to determine the origin of the vorticity in the near-wall buffer layer. Following an experimental study of Sheng et al. (2009), we identify typical "ejection" and "sweep" events in the buffer layer by local minima/maxima of the wall-stress. In contrast to their conjecture, however, we find that vortex-lifting from the…
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Taxonomy
TopicsQuantum, superfluid, helium dynamics · Fluid Dynamics and Turbulent Flows · Meteorological Phenomena and Simulations
