Skip to main content
banner image
No data available.
Please log in to see this content.
You have no subscription access to this content.
No metrics data to plot.
The attempt to load metrics for this article has failed.
The attempt to plot a graph for these metrics has failed.
The full text of this article is not currently available.
/content/aip/journal/pof2/26/5/10.1063/1.4876195
1.
1. A. J. Smits, B. J. McKeon, and I. Marusic, “High-Reynolds number wall turbulence,” Annu. Rev. Fluid Mech. 43, 353375 (2011).
http://dx.doi.org/10.1146/annurev-fluid-122109-160753
2.
2. G. Berkooz, P. Holmes, and J. L. Lumley, “The proper orthogonal decomposition in the analysis of turbulent flows,” Annu. Rev. Fluid Mech. 25, 539575 (1993).
http://dx.doi.org/10.1146/annurev.fl.25.010193.002543
3.
3. C. W. Rowley, “Model reduction for fluids using balanced proper orthogonal decomposition,” Int. J. Bifurcation Chaos 15(3), 9971013 (2005).
http://dx.doi.org/10.1142/S0218127405012429
4.
4. P. J. Schmid, “Dynamic mode decomposition of numerical and experimental data,” J. Fluid Mech. 656, 528 (2010).
http://dx.doi.org/10.1017/S0022112010001217
5.
5. A. Tumin, “The biorthogonal eigenfunction system of linear stability equations: a survey of applications to receptivity problems and to analysis of experimental and computational results,” AIAA Paper 2011-3244, 2011.
6.
6. I. Mezić, “Analysis of fluid flows via spectral properties of the Koopman operator,” Annu. Rev. Fluid Mech. 45, 357378 (2013).
http://dx.doi.org/10.1146/annurev-fluid-011212-140652
7.
7. B. J. McKeon and A. S. Sharma, “A critical-layer framework for turbulent pipe flow,” J. Fluid Mech. 658, 336382 (2010).
http://dx.doi.org/10.1017/S002211201000176X
8.
8. B. J. McKeon, A. S. Sharma, and I. Jacobi, “Experimental manipulation of wall turbulence: A systems approach,” Phys. Fluids 25, 031301 (2013).
http://dx.doi.org/10.1063/1.4793444
9.
9. A. S. Sharma and B. J. McKeon, “On coherent structure in wall turbulence,” J. Fluid Mech. 728, 196238 (2013).
http://dx.doi.org/10.1017/jfm.2013.286
10.
10. R. Moarref, A. S. Sharma, J. A. Tropp, and B. J. McKeon, “Model-based scaling of the streamwise energy density in high-Reynolds number turbulent channels,” J. Fluid Mech. 734, 275316 (2013).
http://dx.doi.org/10.1017/jfm.2013.457
11.
11. S. Hoyas and J. Jiménez, “Scaling of the velocity fluctuations in turbulent channels up to Reτ = 2003,” Phys. Fluids 18(1), 011702 (2006).
http://dx.doi.org/10.1063/1.2162185
12.
12. D. E. Coles, “The law of the wake in the turbulent boundary layer,” J. Fluid Mech. 1, 191226 (1956).
http://dx.doi.org/10.1017/S0022112056000135
13.
13. J. LeHew, M. Guala, and B. J. McKeon, “A study of the three-dimensional spectral energy distribution in a zero pressure gradient turbulent boundary layer,” Exp. Fluids 51, 9971012 (2011).
http://dx.doi.org/10.1007/s00348-011-1117-z
14.
14. R. Moarref, A. S. Sharma, J. A. Tropp, and B. J. McKeon, “On effectiveness of a rank-1 model of turbulent channels for representing the velocity spectra,” AIAA Paper 2013-2480, 2013.
15.
15. Y. Huang and D. P. Palomar, “Rank-constrained separable semidefinite programming with applications to optimal beamforming,” IEEE Trans. Signal Proces. 58(2), 664678 (2010).
http://dx.doi.org/10.1109/TSP.2009.2031732
16.
16. CVX Research, Inc., “CVX: Matlab Software for Disciplined Convex Programming, version 2.0 beta,” see http://cvxr.com/cvx, September 2012.
http://aip.metastore.ingenta.com/content/aip/journal/pof2/26/5/10.1063/1.4876195
Loading
/content/aip/journal/pof2/26/5/10.1063/1.4876195
Loading

Data & Media loading...

Loading

Article metrics loading...

/content/aip/journal/pof2/26/5/10.1063/1.4876195
2014-05-13
2016-09-27

Abstract

We combine resolvent-mode decomposition with techniques from convex optimization to optimally approximate velocity spectra in a turbulent channel. The velocity is expressed as a weighted sum of resolvent modes that are dynamically significant, non-empirical, and scalable with Reynolds number. To optimally represent direct numerical simulations (DNS) data at friction Reynolds number 2003, we determine the weights of resolvent modes as the solution of a convex optimization problem. Using only 12 modes per wall-parallel wavenumber pair and temporal frequency, we obtain close agreement with DNS-spectra, reducing the wall-normal and temporal resolutions used in the simulation by three orders of magnitude.

Loading

Full text loading...

/deliver/fulltext/aip/journal/pof2/26/5/1.4876195.html;jsessionid=pu3OezG51uTn-O2B_zo6b2Bd.x-aip-live-03?itemId=/content/aip/journal/pof2/26/5/10.1063/1.4876195&mimeType=html&fmt=ahah&containerItemId=content/aip/journal/pof2
true
true

Access Key

  • FFree Content
  • OAOpen Access Content
  • SSubscribed Content
  • TFree Trial Content
752b84549af89a08dbdd7fdb8b9568b5 journal.articlezxybnytfddd
/content/realmedia?fmt=ahah&adPositionList=
&advertTargetUrl=//oascentral.aip.org/RealMedia/ads/&sitePageValue=pof.aip.org/26/5/10.1063/1.4876195&pageURL=http://scitation.aip.org/content/aip/journal/pof2/26/5/10.1063/1.4876195'
Right1,Right2,Right3,