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Influence of the Reynolds number on the vortical structures in the logarithmic region of turbulent boundary layers

Published online by Cambridge University Press:  25 January 2013

Sophie Herpin
Affiliation:
Laboratoire de Mécanique de Lille (LML), Ecole Centrale de Lille, Bd Paul Langevin, Cite Scientifique, 59655 Villeneuve d’Ascq CEDEX, France
Michel Stanislas*
Affiliation:
Laboratoire de Mécanique de Lille (LML), Ecole Centrale de Lille, Bd Paul Langevin, Cite Scientifique, 59655 Villeneuve d’Ascq CEDEX, France
Jean Marc Foucaut
Affiliation:
Laboratoire de Mécanique de Lille (LML), Ecole Centrale de Lille, Bd Paul Langevin, Cite Scientifique, 59655 Villeneuve d’Ascq CEDEX, France
Sebastien Coudert
Affiliation:
Laboratoire de Mécanique de Lille (LML), Ecole Centrale de Lille, Bd Paul Langevin, Cite Scientifique, 59655 Villeneuve d’Ascq CEDEX, France
*
Email address for correspondence: [email protected]

Abstract

Near-wall turbulence is a subject of prime importance for turbulence modelling. Coherent structures were hypothesized early by Theodorsen in this flow region and have been the subject of intensive research ever since. The overall organization of these coherent structures has now been well assessed. Vortical structures appear to play a key role in this organization. Their characteristics and scaling have been studied by many authors as listed in the Introduction. The present contribution to the subject relies on high-resolution stereo particle image velocimetry (PIV) to study these structures. High-quality measurements are performed in a thick turbulent boundary layer at different values of the Reynolds number. The data quality is first assessed by comparing the statistics to those of hot-wire anemometry and direct numerical simulation data. The agreement between the two appears satisfactory. The PIV data are then processed in order to extract the vortex characteristics in a streamwise plane and in a spanwise plane. The statistical characteristics of these vortices are analysed in detail as a function of wall distance. The scaling of the data appears to be universal when the Kolmogorov scales are used. These results are analysed and discussed in terms of their probability density functions. This leads to a question regarding the Kolmogorov cascade in this region of the flow.

Type
Papers
Copyright
©2013 Cambridge University Press

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Footnotes

Present address: Oxylane Research, 4 Bv de Mons, 59665 Villeneuve d’Ascq, France.

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