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Dependence of small-scale energetics on large scales in turbulent flows

Published online by Cambridge University Press:  10 August 2018

M. F. Howland*
Affiliation:
Center for Turbulence Research, Stanford University, Stanford, CA 94305, USA Department of Mechanical Engineering, Stanford University, Stanford, CA 94305, USA
X. I. A. Yang
Affiliation:
Center for Turbulence Research, Stanford University, Stanford, CA 94305, USA Mechanical and Nuclear Engineering, Pennsylvania State University, State College, PA 16802, USA
*
Email address for correspondence: [email protected]

Abstract

In a turbulent flow, small- and large-scale fluid motions are coupled. In this work, we investigate the small-scale response to large-scale fluctuations in turbulent flows and discuss the implications on large eddy simulation (LES) wall modelling. The interscale interaction in wall-bounded flows was previously parameterized in the predictive inner–outer (PIO) model, where the amplitude of the small scales responds linearly to the large-scale fluctuations. While this assumed linearity is valid in the viscous sublayer, it is an insufficient approximation of the true interscale interaction in wall-normal distances within the buffer layer and above. Within these regions, a piecewise linear response function (piecewise with respect to large-scale fluctuations being positive or negative) appears to be more appropriate. In addition to proposing a new response function, we relate the amplitude modulation process to the Townsend attached eddy hypothesis. This connection allows us to make theoretical predictions on the model parameters within the PIO model. We use these parameters to apply the PIO model to wall-modelled LES. Further, we present empirical evidence of amplitude modulation in isotropic turbulence. The evidence suggests that the existence of nonlinear interscale interactions in the form of amplitude modulation does not rely on the presence of a non-penetrating boundary, but on the presence of a range of viscosity-dominated scales and a range of inertial-dominated scales.

Type
JFM Papers
Copyright
© 2018 Cambridge University Press 

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References

Agostini, L. & Leschziner, M. A. 2014 On the influence of outer large-scale structures on near-wall turbulence in channel flow. Phys. Fluids 26 (7), 075107.Google Scholar
Agostini, L. & Leschziner, M. 2016a On the validity of the quasi-steady-turbulence hypothesis in representing the effects of large scales on small scales in boundary layers. Phys. Fluids 28 (4), 045102.Google Scholar
Agostini, L. & Leschziner, M. 2016b Predicting the response of small-scale near-wall turbulence to large-scale outer motions. Phys. Fluids 28 (1), 015107.Google Scholar
Agostini, L., Leschziner, M. & Gaitonde, D. 2016 Skewness-induced asymmetric modulation of small-scale turbulence by large-scale structures. Phys. Fluids 28 (1), 015110.Google Scholar
Anderson, W. & Meneveau, C. 2011 Dynamic roughness model for large-eddy simulation of turbulent flow over multiscale, fractal-like rough surfaces. J. Fluid Mech. 679, 288314.Google Scholar
Awasthi, A. & Anderson, W. 2018 Numerical study of turbulent channel flow perturbed by spanwise topographic heterogeneity: amplitude and frequency modulation within low- and high-momentum pathways. Phys. Rev. Fluids 3 (4), 044602.Google Scholar
Baars, W. J., Hutchins, N. & Marusic, I. 2016 Spectral stochastic estimation of high-Reynolds-number wall-bounded turbulence for a refined inner–outer interaction model. Phys. Rev. Fluids 1 (5), 054406.Google Scholar
Baars, W. J., Hutchins, N. & Marusic, I. 2017 Reynolds number trend of hierarchies and scale interactions in turbulent boundary layers. Phil. Trans. R. Soc. Lond. A 375 (2089), 20160077.Google Scholar
Baars, W. J., Talluru, K. M., Hutchins, N. & Marusic, I. 2015 Wavelet analysis of wall turbulence to study large-scale modulation of small scales. Exp. Fluids 56 (10), 188.Google Scholar
Bae, H. J., Lozano-Duran, A., Bose, S. & Moin, P. 2018 Turbulence intensities in large-eddy simulation of wall-bounded flows. Phys. Rev. Fluids 3 (1), 014610.Google Scholar
Bandyopadhyay, P. R. & Hussain, A. 1984 The coupling between scales in shear flows. Phys. Fluids 27 (9), 22212228.Google Scholar
Bose, S. & Moin, P. 2014 A dynamic slip boundary condition for wall-modeled large-eddy simulation. Phys. Fluids 26 (1), 015104.Google Scholar
Bose, S. T. & Park, G. I. 2017 Wall-modeled LES for complex turbulent flows. Annu. Rev. Fluid Mech. 50 (1), 535561.Google Scholar
Bou-Zeid, E., Meneveau, C. & Parlange, M. 2005 A scale-dependent lagrangian dynamic model for large eddy simulation of complex turbulent flows. Phys. Fluids 17 (2), 025105.Google Scholar
Buxton, O. & Ganapathisubramani, B. 2014 Concurrent scale interactions in the far-field of a turbulent mixing layer. Phys. Fluids 26 (12), 125106.Google Scholar
Chernyshenko, S. I., Marusic, I. & Mathis, R.2012 Quasi-steady description of modulation effects in wall turbulence. arXiv:1203.3714v1.Google Scholar
Choi, H. & Moin, P. 2012 Grid-point requirements for large eddy simulation: Chapman’s estimates revisited. Phys. Fluids 24 (1), 011702.Google Scholar
Chung, D. & McKeon, B. J. 2010 Large-eddy simulation of large-scale structures in long channel flow. J. Fluid Mech. 661, 341364.Google Scholar
Fiscaletti, D., Ganapathisubramani, B. & Elsinga, G. E. 2015 Amplitude and frequency modulation of the small scales in a jet. J. Fluid Mech. 772, 756783.Google Scholar
Ganapathisubramani, B., Hutchins, N., Monty, J. P., Chung, D. & Marusic, I. 2012 Amplitude and frequency modulation in wall turbulence. J. Fluid Mech. 712, 6191.Google Scholar
Howland, M. F. & Yang, X. I. A. 2017 Dependence of small-scale energetics on large scales in wall-bounded flows. In CTR Annual Research Briefs, pp. 215228. Stanford University, Center Turbulence Research.Google Scholar
Hoyas, S. & Jiménez, J. 2006 Scaling of the velocity fluctuations in turbulent channels up to Re 𝜏 = 2003. Phys. Fluids 18 (1), 011702.Google Scholar
Hutchins, N., Chauhan, K., Marusic, I., Monty, J. & Klewicki, J. 2012 Towards reconciling the large-scale structure of turbulent boundary layers in the atmosphere and laboratory. Boundary-Layer Meteorol. 145 (2), 273306.Google Scholar
Hutchins, N. & Marusic, I. 2007 Large-scale influences in near-wall turbulence. Phil. Trans. R. Soc. Lond. A 365 (1852), 647664.Google Scholar
Hutchins, N., Nickels, T. B., Marusic, I. & Chong, M. 2009 Hot-wire spatial resolution issues in wall-bounded turbulence. J. Fluid Mech. 635, 103136.Google Scholar
Hwang, J., Lee, J., Sung, H. J. & Zaki, T. A. 2016 Inner–outer interactions of large-scale structures in turbulent channel flow. J. Fluid Mech. 790, 128157.Google Scholar
Inoue, M., Mathis, R., Marusic, I. & Pullin, D. I. 2012 Inner-layer intensities for the flat-plate turbulent boundary layer combining a predictive wall-model with large-eddy simulations. Phys. Fluids 24 (7), 075102.Google Scholar
Jacobi, I. & McKeon, B. J. 2013 Phase relationships between large and small scales in the turbulent boundary layer. Exp. Fluids 54 (3), 1481.Google Scholar
Johnson, P. L. & Meneveau, C. 2017 Turbulence intermittency in a multiple-time-scale Navier–Stokes-based reduced model. Phys. Rev. Fluids 2 (7), 072601.Google Scholar
Lee, M. & Moser, R. D. 2015 Direct numerical simulation of turbulent channel flow up to Re 𝜏 ≈ 5200. J. Fluid Mech. 774, 395415.Google Scholar
Li, Y., Perlman, E., Wan, M., Yang, Y., Meneveau, C., Burns, R., Chen, S., Szalay, A. & Eyink, G. 2008 A public turbulence database cluster and applications to study lagrangian evolution of velocity increments in turbulence. J. Turbul. 9, N31.Google Scholar
Lozano-Durán, A., Bae, H., Bose, S. & Moin, P. 2017 Dynamic wall models for the slip boundary condition. Annual Research Briefs 2017. Stanford University, Center Turbulence Research.Google Scholar
Lozano-Durán, A. & Jiménez, J. 2014 Effect of the computational domain on direct simulations of turbulent channels up to Re 𝜏 = 4200. Phys. Fluids 26 (1), 011702.Google Scholar
Marusic, I., Mathis, R. & Hutchins, N. 2010 Predictive model for wall-bounded turbulent flow. Science 329 (5988), 193196.Google Scholar
Mathis, R., Hutchins, N. & Marusic, I. 2009a Large-scale amplitude modulation of the small-scale structures in turbulent boundary layers. J. Fluid Mech. 628, 311337.Google Scholar
Mathis, R., Hutchins, N. & Marusic, I. 2011 A predictive inner–outer model for streamwise turbulence statistics in wall-bounded flows. J. Fluid Mech. 681, 537566.Google Scholar
Mathis, R., Marusic, I., Chernyshenko, S. I. & Hutchins, N. 2013 Estimating wall-shear-stress fluctuations given an outer region input. J. Fluid Mech. 715, 163.Google Scholar
Mathis, R., Monty, J. P., Hutchins, N. & Marusic, I. 2009b Comparison of large-scale amplitude modulation in turbulent boundary layers, pipes, and channel flows. Phys. Fluids 21 (11), 111703.Google Scholar
Meneveau, C. & Katz, J. 2000 Scale-invariance and turbulence models for large-eddy simulation. Annu. Rev. Fluid Mech. 32 (1), 132.Google Scholar
Park, G., Howland, M. F., Lozano-Duran, A. & Moin, P. 2016 Prediction of wall shear-stress fluctuations in wall-modeled large-eddy simulation. In APS Meeting Abstracts.Google Scholar
Park, G. I. & Moin, P. 2016 Space-time characteristics of wall-pressure and wall shear-stress fluctuations in wall-modeled large eddy simulation. Phys. Rev. Fluids 1 (2), 024404.Google Scholar
Piomelli, U. & Balaras, E. 2002 Wall-layer models for large-eddy simulations. Annu. Rev. Fluid Mech. 34 (1), 349374.Google Scholar
Sidebottom, W., Cabrit, O., Marusic, I., Meneveau, C., Ooi, A. & Jones, D. 2014 Modelling of wall shear-stress fluctuations for large-eddy simulation. In Proc. 19th Australasian Fluid Mech. Conf., Melbourne, Australia.Google Scholar
Talluru, K. M., Baidya, R., Hutchins, N. & Marusic, I. 2014 Amplitude modulation of all three velocity components in turbulent boundary layers. J. Fluid Mech. 746, R1.Google Scholar
Tang, Z. & Jiang, N. 2018 Scale interaction and arrangement in a turbulent boundary layer perturbed by a wall-mounted cylindrical element. Phys. Fluids 30 (5), 055103.Google Scholar
Townsend, A. A. 1976 The Structure of Turbulent Shear Flow. Cambridge University Press.Google Scholar
Yang, X. I. A., Baidya, R., Johnson, P., Marusic, I. & Meneveau, C. 2017 Structure function tensor scaling in the logarithmic region derived from the attached eddy model of wall-bounded turbulent flows. Phys. Rev. Fluids 2 (6), 064602.Google Scholar
Yang, X. I. A. & Howland, M. F. 2018 Implication of Taylor’s hypothesis on measuring flow modulation. J. Fluid Mech. 836, 222237.Google Scholar
Yang, X. I. A. & Lozano-Durán, A. 2017 A multifractal model for the momentum transfer process in wall-bounded flows. J. Fluid Mech. 824, R2.Google Scholar
Yang, X. I. A., Marusic, I. & Meneveau, C. 2016a Hierarchical random additive process and logarithmic scaling of generalized high order, two-point correlations in turbulent boundary layer flow. Phys. Rev. Fluids 1 (2), 024402.Google Scholar
Yang, X. I. A., Marusic, I. & Meneveau, C. 2016b Moment generating functions and scaling laws in the inertial layer of turbulent wall-bounded flows. J. Fluid Mech. 791, R2.Google Scholar
Yang, X. I. A., Meneveau, C., Marusic, I. & Biferale, L. 2016c Extended self-similarity in moment-generating-functions in wall-bounded turbulence at high Reynolds number. Phys. Rev. Fluids 1 (4), 044405.Google Scholar
Zhang, C. & Chernyshenko, S. I. 2016 Quasisteady quasihomogeneous description of the scale interactions in near-wall turbulence. Phys. Rev. Fluids 1 (1), 014401.Google Scholar