Influence of large-scale motions on effectiveness of active drag-reduction control in turbulent channel flow at Reτ = 1000

Bing Qing Deng, Wei Xi Huang, Chun Xiao Xu, Gui Xiang Cui

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Direct numerical simulations are performed in turbulent channel flows with opposition control at Reτ =180 and 1000. The reason for the reduction of control effectiveness at higher Reynolds number is investigated. In the outer layer, the control imposed on the wall can reduce the Reynolds stresses at the same rate as the drag reduction, while the distribution of the energy at different scales is little different from the uncontrolled case. In the near-wall region at Reτ = 1000, suppression of the near-wall structures under the large-scale high-speed streaks by the control are much weaker than those under the region of the large-scale low-speed streaks, which leads to the falloff of the effectiveness of the control in suppressing the near-wall turbulence at high Reynolds numbers. By further analyzing the drag reduction rates, it is found that the effectiveness of the control is mainly determined by the suppression degree of the near-wall motions which is influenced by the large-scale motions.

Original languageEnglish (US)
Title of host publication9th International Symposium on Turbulence and Shear Flow Phenomena, TSFP 2015
PublisherTSFP-9
ISBN (Electronic)9780000000002
StatePublished - 2015
Event9th International Symposium on Turbulence and Shear Flow Phenomena, TSFP 2015 - Melbourne, Australia
Duration: Jun 30 2015Jul 3 2015

Publication series

Name9th International Symposium on Turbulence and Shear Flow Phenomena, TSFP 2015
Volume3

Other

Other9th International Symposium on Turbulence and Shear Flow Phenomena, TSFP 2015
Country/TerritoryAustralia
CityMelbourne
Period6/30/157/3/15

Bibliographical note

Funding Information:
Acknowledgments The work is supported by National Natural Science Foundation of China (Project No. 11490551, 11472154, 11322221, 11132005).

Copyright:
Copyright 2017 Elsevier B.V., All rights reserved.

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