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Taming Real World Flow Control Experiments with MLC

  • Thomas Duriez
  • Steven L. Brunton
  • Bernd R. Noack
Chapter
Part of the Fluid Mechanics and Its Applications book series (FMIA, volume 116)

Abstract

In this chapter, we present applications of machine learning control (MLC) to flow control experiments. Examples range from mixing enhancement of laminar flow to separation mitigation of a turbulent boundary layer. The discussion highlights the physical actuation mechanisms, challenges of alternative model-based control and enabling implementations of MLC in the data aquisition system.

Keywords

Particle Image Velocimetry Wind Tunnel Shear Layer Flow Control Turbulent Boundary Layer 
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.

Copyright information

© Springer International Publishing Switzerland 2017

Authors and Affiliations

  • Thomas Duriez
    • 1
  • Steven L. Brunton
    • 2
  • Bernd R. Noack
    • 3
    • 4
  1. 1.Laboratorio de Fluido DinámicaCONICET - Universidad de Buenos AiresBuenos AiresArgentina
  2. 2.Mechanical Engineering DepartmentUniversity of WashingtonSeattleUSA
  3. 3.Département Mécanique-EnergétiqueLIMSI-CNRS, UPR 3251OrsayFrance
  4. 4.Institut für StrömungsmechanikTechnische Universität BraunschweigBraunschweigGermany

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