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Predicting vortex merging and ensuing turbulence characteristics in shear layers from initial conditions

Published online by Cambridge University Press:  17 September 2019

Anirban Guha Open the ORCID record for Anirban Guha [Opens in a new window]  and
Mona Rahmani Open the ORCID record for Mona Rahmani [Opens in a new window]
Anirban Guha*
Affiliation:
Institute of Coastal Research, Helmholtz-Zentrum Geesthacht, Geesthacht 21502, Germany School of Science and Engineering, University of Dundee, Dundee DD1 4HN, UK
Mona Rahmani
Affiliation:
Department of Mathematics, The University of British Columbia, 1984 Mathematics Road, Vancouver, British Columbia V6T 1Z2, Canada
*
†Email address for correspondence: [email protected]
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Abstract

Unstable shear layers in environmental and industrial flows roll up into a series of vortices, which often form complex nonlinear merging patterns such as pairs and triplets. These patterns crucially determine the subsequent turbulence, mixing and scalar transport. We show that the late-time, highly nonlinear merging patterns are predictable from the linearized initial state. The initial asymmetry between consecutive wavelengths of the vertical velocity field provides an effective measure of the strength and pattern of vortex merging. The predictions of this measure are substantiated using direct numerical simulations. We also show that this measure has significant implications in determining the route to turbulence and the ensuing turbulence characteristics.

JFM classification

Instability: Transition to turbulence Turbulent Flows: Shear layer turbulence Vortex Flows: Vortex interactions
Type
JFM Rapids
Information
Journal of Fluid Mechanics , Volume 878 , 10 November 2019 , R4
Copyright
© 2019 Cambridge University Press 

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