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Interaction of noise disturbances and streamwise streaks

  • Philipp SchlatterEmail author
  • Luca Brandt
  • Rick de Lange
Conference paper
Part of the Springer Proceedings in Physics book series (SPPHY, volume 132)

Abstract

Disturbance evolution in a boundary layer with streamwise streaks and random two-and three-dimensional noise of various amplitudes is studied via numerical simulations. The aim of the present work is to determine the impact of the interaction on the arising flow structures and, eventually, on the location and details of the breakdown to turbulence. It is shown that largescale 2D noise can be controlled via streaks, whereas the more general 3D noise configuration is prone to premature transition due to increased instability of the introduced streaks. It is interesting to note that the latter transition scenario closely resembles the flow structures found in bypass transition. A recent theoretical and numerical study by Cossu and Brandt [2] has shown that a substantial stabilisation of a boundary layer subject to essentially two-dimensional disturbances (i.e. Tollmien-Schlichting (TS) waves) can be achieved by a spanwise modulation of the mean flow, i.e. via superimposed streamwise streaks on the laminar Blasius flow. In particular, it has been shown both experimentally via finite-amplitude roughness [3] and later via large-eddy simulation (LES, [5]) that transition to turbulence can effectively by moved to a more downstream position via this essentially passive control mechanism. However, the disturbances considered in the mentioned studies have all had their maximum energy in two-dimensional (spanwise invariant) modes. It is therefore interesting to examine the interaction of streamwise streaks with disturbences of a more general nature, i.e. 2D and 3D random noise at various frequencies and (spanwise) wavenumbers.

Keywords

Turbulent Spot Bypass Transition Transition Delay Transition Scenario Parabolised Stability Equation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Philipp Schlatter
    • 1
    Email author
  • Luca Brandt
    • 1
  • Rick de Lange
    • 2
  1. 1.Linné Flow Centre, KTH MechanicsStockholmSweden
  2. 2.TUe Mechanical EngineeringEindhovenThe Netherlands

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