Resolvent-analysis-based design of airfoil separation control

By C. Yeh, Kunihiko Taira. Journal of Fluid Mechanics, 2018

182 citations recorded by the source corpus.

We use resolvent analysis to design active control techniques for separated flows over a NACA 0012 airfoil. Spanwise-periodic flows over the airfoil at a chord-based Reynolds number of $23\,000$ and a free-stream Mach number of $0.3$ are considered at two post-stall angles of attack of $6^{\circ }$ and $9^{\circ }$ . Near the leading edge, localized unsteady thermal actuation is introduced in an open-loop manner with two tunable parameters of actuation frequency and spanwise wavelength. To provide physics-based guidance for the effective choice of these control input parameters, we conduct global resolvent analysis on the baseline turbulent mean flows to identify the actuation frequency and wavenumber that provide large perturbation energy amplification. The present analysis also considers the use of a temporal filter to limit the time horizon for assessing the energy amplification to extend resolvent analysis to unstable base flows. We incorporate the amplification and response mode from resolvent analysis to provide a metric that quantifies momentum mixing associated with the modal structure. This metric is compared to the results from a large number of three-dimensional large-eddy simulations of open-loop controlled flows. With the agreement between the resolvent-based metric and the enhancement of aerodynamic performance found through large-eddy simulations, we demonstrate that resolvent analysis can predict the effective range of actuation frequency as well as the global response to the actuation input. We believe that the present resolvent-based approach provides a promising path towards mean flow modification by capitalizing on the dominant modal mixing.

Subfields: Aerospace Engineering, Computational Mechanics

View Paper: https://www.semanticscholar.org/paper/40d6fa8c3d6261096e523b1d7a1be91e74ddb9f2

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In Aerospace Engineering

  1. Shervin Bagheri
  2. Scott T. M. Dawson
  3. Karthik Duraisamy
  4. Kunihiko Taira
  5. Steven L. Brunton
  6. J. Nathan Kutz

In Computational Mechanics

  1. Steven L. Brunton
  2. Scott T. M. Dawson
  3. Maziar S. Hemati
  4. J. Nathan Kutz
  5. Kunihiko Taira
  6. Shervin Bagheri
  7. Yiyang Sun
  8. Karthik Duraisamy

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