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Experimental control of natural perturbations in channel flow

Published online by Cambridge University Press:  04 July 2014

Fabien Juillet
Affiliation:
Laboratoire d’Hydrodynamique (LadHyX), CNRS-Ecole Polytechnique, 91128 Palaiseau, France
B. J. McKeon
Affiliation:
Graduate Aerospace Laboratories (GALCIT), California Institute of Technology, Pasadena, CA 91125, USA
Peter J. Schmid*
Affiliation:
Department of Mathematics, Imperial College London, London SW7 2AZ, UK
*
Email address for correspondence: [email protected]

Abstract

A combined approach using system identification and feed-forward control design has been applied to experimental laminar channel flow in an effort to reduce the naturally occurring disturbance level. A simple blowing/suction strategy was capable of reducing the standard deviation of the measured sensor signal by 45 %, which markedly exceeds previously obtained results under comparable conditions. A comparable reduction could be verified over a significant streamwise extent, implying an improvement over previous, more localized disturbance control. The technique is effective, flexible, and robust, and the obtained results encourage further explorations of experimental control of convection-dominated flows.

Type
Papers
Copyright
© 2014 Cambridge University Press 

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References

Belson, B. A., Hanson, R. E., Palmeiro, D., Lavoie, P., Meidell, K. & Rowley, C. W.2012 Comparison of plasma actuators in simulations and experiments for control of bypass transition. AIAA Paper 2012-1141.Google Scholar
Bewley, T. R. 2001 Flow control: new challenges for a new renaissance. Prog. Aerosp. Sci. 37 (1), 2158.Google Scholar
Burl, J. 1998 Linear Optimal Control. Prentice Hall.Google Scholar
Cattafesta, L. N., Garg, S., Choudhari, M. & Li, F.1997 Active control of flow-induced cavity resonance. AIAA.Google Scholar
Cattafesta, L. N. & Sheplak, M. 2011 Actuators for active flow control. Annu. Rev. Fluid Mech. 43, 247272.CrossRefGoogle Scholar
Cattafesta, L. N., Song, Q., Williams, D. R., Rowley, C. W. & Alvi, F. S. 2008 Active control of flow-induced cavity oscillations. Prog. Aerosp. Sci. 44, 479502.Google Scholar
Cattafesta, L. N., Williams, D., Rowley, C. W. & Alvi, F.2003 Review of active control of flow-induced cavity resonance. AIAA Paper 2003-3567.CrossRefGoogle Scholar
Dearing, S., Lambert, S. & Morrison, J. 2007 Flow control with active dimples. Aeronaut. J. 705714.Google Scholar
Dovetta, N., Juillet, F. & Schmid, P. J. 2014 Data-based model-predictive control design for convectively unstable flows. Phys. Fluids (submitted).Google Scholar
Gad-el-Hak, M. 1996 Modern developments in flow control. Appl. Mech. Rev. 49 (7), 365379.CrossRefGoogle Scholar
Glezer, A. & Amitay, M. 2002 Synthetic jets. Annu. Rev. Fluid Mech. 34, 503529.Google Scholar
Hervé, A., Sipp, D., Schmid, P. J. & Samuelides, M. 2012 A physics-based approach to flow control using system identification. J. Fluid Mech. 702, 2658.Google Scholar
Ilak, M. & Rowley, C. W.2006 Reduced-order modeling of channel flow using traveling POD and balanced POD. AIAA Paper 2006-3194.CrossRefGoogle Scholar
Illingworth, S. J., Morgans, A. S. & Rowley, C. W. 2012 Feedback control of cavity flow oscillations using simple linear models. J. Fluid Mech. 709, 223248.Google Scholar
Jacobi, I. & McKeon, B. J. 2011 Dynamic roughness perturbation of a turbulent boundary layer. J. Fluid Mech. 688, 258296.Google Scholar
Jacobson, S. A. & Reynolds, W. C. 1998 Active control of streamwise vortices and streaks in boundary layers. J. Fluid Mech. 360, 179211.Google Scholar
Jahanmiri, M.2010 Active flow control: a review. Tech Rep. 2010:12. Chalmers University of Technology.Google Scholar
Juillet, F.2013 Control of amplifier flows using subspace identification techniques. PhD thesis, Ecole Polytechnique.Google Scholar
Juillet, F., Schmid, P. J. & Huerre, P. 2013 Control of amplifier flows using subspace identification techniques. J. Fluid Mech. 725, 522565.CrossRefGoogle Scholar
Kegerise, M., Cabell, O. H. & Cattafesta, L. N.2004 Real-time adaptive control of flow-induced cavity tones. AIAA Paper 2004-0572.Google Scholar
Kim, J. & Bewley, T. R. 2007 A linear systems approach to flow control. Annu. Rev. Fluid Mech. 39 (1), 383417.Google Scholar
Ljung, L. 1999 System Identification, Theory for the User, 2nd edn. Prentice Hall PTR.Google Scholar
Luchtenburg, D. M., Tadmor, G., Lehmann, O., Noack, B. R., King, R. & Morzyński, M.2006 Tuned POD Galerkin models for transient feedback regulation of the cylinder wake. AIAA-Paper 2006-1407.CrossRefGoogle Scholar
Lundell, F. 2007 Reactive control of transition induced by free-stream turbulence: an experimental demonstration. J. Fluid Mech. 585, 4171.Google Scholar
Moarref, R. & Jovanovic, M. R. 2012 Model-based design of transverse wall oscillations for turbulent drag reduction. J. Fluid Mech. 707, 205240.CrossRefGoogle Scholar
Penrose, R. 1955 A generalized inverse for matrices. Proc. Camb. Phil. Soc. 51, 406413.Google Scholar
Quadrio, M. & Ricco, P. 2004 Critical assessment of turbulent drag reduction through spanwise wall oscillations. J. Fluid Mech. 521, 251271.Google Scholar
Rathnasingham, R. & Breuer, K. S. 1997 System identification and control of turbulent flows. Phys. Fluids 9, 18671869.Google Scholar
Rathnasingham, R. & Breuer, K. S. 2003 Active control of turbulent boundary layers. J. Fluid Mech. 495, 209233.Google Scholar
Rebbeck, H. & Choi, K. S. 2006 A wind-tunnel experiment on real-time opposition control of turbulence. Phys. Fluids 18, 035103.Google Scholar
Rowley, C. W. 2005 Model reduction for fluids using balanced proper orthogonal decomposition. Intl J. Bifurcation Chaos 15 (3), 9971013.Google Scholar
DRowley, C. W., Colonius, T. & Murray, R. M. 2004 Model reduction for compressible flows using POD and Galerkin projection. Physica 189, 115129.Google Scholar
Tikhonov, A. N. 1963 Solution of incorrectly formulated problems and the regularization method. Dokl. Akad. Nauk USSR 151, 501504.Google Scholar
Willcox, K. & Peraire, J. 2002 Balanced model reduction via the proper othogonal decomposition. AIAA J. 40 (11), 23232330.Google Scholar
Woodcock, J. D., Sader, J. E. & Marusic, I. 2012 Induced flow due to blowing and suction flow control: an analysis of transpiration. J. Fluid Mech. 690, 366398.Google Scholar