Export citation

Export citation

Choose format for download:

Download Citation
  • Access by Xinjiang University

Hierarchical random additive model for the spanwise and wall-normal velocities in wall-bounded flows at high Reynolds numbers

X. I. A. Yang1, R. Baidya2, Yu Lv3, and I. Marusic2

  • 1Mechanical and Nuclear Engineering, Penn State University, Pennsylvania 16801, USA
  • 2Department of Mechanical Engineering, University of Melbourne, Melbourne, Victoria 3010, Australia
  • 3Department of Aerospace Engineering, Mississippi State University, Mississippi 39759, USA

Phys. Rev. Fluids 3, 124606 – Published 17 December, 2018

DOI: https://doi.org/10.1103/PhysRevFluids.3.124606

Abstract

At high Reynolds numbers, the logarithmic range in wall-bounded flows spans many scales. An important conceptual modeling framework of the logarithmic range is Townsend's attached eddy hypothesis [The Structure of Turbulent Shear Flow (Cambridge University Press, Cambridge, 1976)], where high Reynolds number wall-bounded flows are modeled as assemblies of space-filling, self-similar, and wall-attached eddies. Recently, Yang et al. [Phys. Rev. Fluids 1, 024402 (2016)] reinterpreted this hypothesis and developed the “hierarchical random additive process” model (HRAP), which provides further insights into the scaling implications of the attached eddies. For example, in a recent study [Yang et al., Phys. Rev. Fluids 2, 064602 (2017)], the HRAP model was used for making scaling predictions of the second-order structure function [ui(x)ui(x)][uj(x)uj(x)] in the logarithmic range, where ui's are the velocity fluctuations in the ith Cartesian direction. Here, we provide empirical support for this HRAP model using high-fidelity experimental data of all three components of velocity in a high Reynolds number boundary layer flow. We show that the spanwise velocity fluctuation can be modeled as a random additive process, and that the wall-normal velocity fluctuation is dominated by the closest neighboring wall-attached eddy. By accounting for all the three velocities in all the three Cartesian directions, the HRAP model is formally a well rounded model for the momentum-carrying scales in wall-bounded flows at high Reynolds numbers.

Physics Subject Headings (PhySH)

Article Text

References (41)

  1. J. Jiménez, Cascades in wall-bounded turbulence, Ann. Rev. Fluid Mech. 44, 27 (2011).
  2. I. Marusic, J. P. Monty, M. Hultmark, and A. J. Smits, On the logarithmic region in wall turbulence, J. Fluid Mech. 716, R3 (2013).
  3. A. Perry and M. Chong, On the mechanism of wall turbulence, J. Fluid Mech. 119, 173 (1982).
  4. J. Bretheim, C. Meneveau, and D. F. Gayme, Standard logarithmic mean velocity distribution in a band-limited restricted nonlinear model of turbulent flow in a half-channel, Phys. Fluids 27, 011702 (2015).
  5. J. Woodcock and I. Marusic, The statistical behavior of attached eddies, Phys. Fluids 27, 015104 (2015).
  6. X. I. A. Yang, I. Marusic, and C. Meneveau, Hierarchical random additive process and logarithmic scaling of generalized high order, two-point correlations in turbulent boundary layer flow, Phys. Rev. Fluids 1, 024402 (2016).
  7. A. Townsend, The Structure of Turbulent Shear Flow (Cambridge University Press, Cambridge, 1976).
  8. A. Perry, S. Henbest, and M. Chong, A theoretical and experimental study of wall turbulence, J. Fluid Mech. 165, 163 (1986).
  9. A. E. Perry and I. Marusic, A wall-wake model for the turbulence structure of boundary layers. Part 1. Extension of the attached eddy hypothesis, J. Fluid Mech. 298, 361 (1995).
  10. I. Marusic and A. E. Perry, A wall-wake model for the turbulence structure of boundary layers. Part 2. Further experimental support, J. Fluid Mech. 298, 389 (1995).
  11. C. M. de Silva, J. D. Woodcock, N. Hutchins, and I. Marusic, Influence of spatial exclusion on the statistical behavior of attached eddies, Phys. Rev. Fluids 1, 022401 (2016).
  12. I. Marusic and J. P. Monty, Attached eddy model of wall turbulence, Ann. Rev. Fluid Mech. (2019).
  13. C. Meneveau and I. Marusic, Generalized logarithmic law for high-order moments in turbulent boundary layers, J. Fluid Mech. 719, R1 (2013).
  14. C. M. de Silva, I. Marusic, J. D. Woodcock, and C. Meneveau, Scaling of second- and higher-order structure functions in turbulent boundary layers, J. Fluid Mech. 769, 654 (2015).
  15. U. Frisch, Fully developed turbulence and intermittency, Ann. N.Y. Acad. Sci. 357, 359 (1980).
  16. Z.-S. She and E. Leveque, Universal Scaling Laws in Fully Developed Turbulence, Phys. Rev. Lett. 72, 336 (1994).
  17. X. I. A. Yang, I. Marusic, and C. Meneveau, Moment generating functions and scaling laws in the inertial layer of turbulent wall-bounded flows, J. Fluid Mech. 791, R2 (2016).
  18. X. I. A. Yang, R. Baidya, P. Johnson, I. Marusic, and C. Meneveau, Structure function tensor scaling in the logarithmic region derived from the attached eddy model of wall-bounded turbulent flows, Phys. Rev. Fluids 2, 064602 (2017).
  19. X. I. A. Yang and A. Lozano-Durán, A multifractal model for the momentum transfer process in wall-bounded flows, J. Fluid Mech. 824, R2 (2017).
  20. J. C. Del Alamo, J. Jiménez, P. Zandonade, and R. D. Moser, Scaling of the energy spectra of turbulent channels, J. Fluid Mech. 500, 135 (2004).
  21. D. Krug, X. I. A. Yang, C. M. de Silva, R. Ostilla-Mónico, R. Verzicco, I. Marusic, and D. Lohse, Statistics of turbulence in the energy-containing range of Taylor–Couette compared to canonical wall-bounded flows, J. Fluid Mech. 830, 797 (2017).
  22. J. A. Sillero, J. Jiménez, and R. D. Moser, Two-point statistics for turbulent boundary layers and channels at Reynolds numbers up to δ+2000, Phys. Fluids 26, 105109 (2014).
  23. C. M. de Silva, K. Kevin, R. Baidya, N. Hutchins, and I. Marusic, Large coherence of spanwise velocity in turbulent boundary layers, J. Fluid Mech. 847, 161 (2018).
  24. R. Baidya, Multicomponent Velocity Measurements in Turbulent Boundary Layers, Ph.D. thesis, University of Melbourne (2016).
  25. J. Philip, R. Baidya, N. Hutchins, J. P. Monty, and I. Marusic, Spatial averaging of streamwise and spanwise velocity measurements in wall-bounded turbulence using V and ×-probes, Meas. Sci. Technol. 24, 115302 (2013).
  26. E. Hopf, Statistical hydromechanics and functional calculus, J. Ration. Mech. Anal. 1, 87 (1952).
  27. A. S. Monin and A. M. Yaglom, Statistical Fluid Mechanics, Vol. II: Mechanics of Turbulence (Courier Corporation, Chelmsford, MA, 2013).
  28. X. I. A. Yang, C. Meneveau, I. Marusic, and L. Biferale, Extended self-similarity in moment-generating-functions in wall-bounded turbulence at high reynolds number, Phys. Rev. Fluids 1, 044405 (2016).
  29. M. K. Simon, Probability Distributions Involving Gaussian Random Variables: A Handbook for Engineers and Scientists (Springer Science & Business Media, Berlin, 2007).
  30. K. M. Talluru, R. Baidya, N. Hutchins, and I. Marusic, Amplitude modulation of all three velocity components in turbulent boundary layers, J. Fluid Mech. 746, R1 (2014).
  31. M. Bernardini, S. Pirozzoli, and P. Orlandi, Velocity statistics in turbulent channel flow up to Reτ=4000, J. Fluid Mech. 742, 171 (2014).
  32. M. Lee and R. D. Moser, Direct numerical simulation of turbulent channel flow up to Reτ5200, J. Fluid Mech. 774, 395 (2015).
  33. U. Frisch, Turbulence: The Legacy of A. N. Kolmogorov (Cambridge University Press, Cambridge, 1995).
  34. M. Hultmark, M. Vallikivi, S. C. C. Bailey, and A. J. Smits, Turbulent Pipe Flow at Extreme Reynolds Numbers, Phys. Rev. Lett. 108, 094501 (2012).
  35. J. M. Wallace, Quadrant analysis in turbulence research: History and evolution, Ann. Rev. Fluid Mech. 48, 131 (2016).
  36. H. Fernholz, E. Krause, M. Nockemann, and M. Schober, Comparative measurements in the canonical boundary layer at Reδ26×104 on the wall of the German–Dutch windtunnel, Phys. Fluids 7, 1275 (1995).
  37. Z. J. Wang, K. Fidkowski, R. Abgrall, F. Bassi, D. Caraeni, A. Cary, H. Deconinck, R. Hartmann, K. Hillewaert, H. T. Huynh, N. Kroll, G. May, P.-O. Persson, B. van Leer, and M. Visbal, High-order CFD methods: Current status and perspective, Int. J. Numer. Methods Fluids 72, 811 (2013).
  38. K. Hillewaert, J. S. Cagnone, S. M. Murman, A. Garai, Y. Lv, and M. Ihme, Assessment of high-order DG methods for LES of compressible flows, in Proceedings of the Summer Program, Center for Turbulence Research, Stanford University (2016), p. 363.
  39. Y. Lv, P. C. Ma, and M. Ihme, On underresolved simulations of compressible turbulence using an entropy-bounded DG method: Solution stabilization, scheme optimization, and benchmark against a finite-volume solver, Computers & Fluids 161, 89 (2018).
  40. N. Hutchins, T. B. Nickels, I. Marusic, and M. Chong, Hot-wire spatial resolution issues in wall-bounded turbulence, J. Fluid Mech. 635, 103 (2009).
  41. P. Ligrani and P. Bradshaw, Spatial resolution and measurement of turbulence in the viscous sublayer using subminiature hot-wire probes, Exp. Fluids 5, 407 (1987).

Outline

Information

Sign In to Your Journals Account

Filter

Filter

Article Lookup

Enter a citation