Turbulence profiles from a smooth flat-plate turbulent boundary layer at high Reynolds number

Winkel, Eric S.; Cutbirth, J. Michael; Ceccio, Steven L.; Perlin, Marc; Dowling, David R.

doi:10.1016/j.expthermflusci.2012.02.009

Cited by 28 publications

(23 citation statements)

References 21 publications

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“…For example, examinations of pipe flow have reported mean flow data at values of Re τ as high as 530 000 (Zagarola & Smits 1998;McKeon et al 2004), where Re τ is the friction Reynolds number, with turbulence data at values up to 98 000 Rosenberg et al 2013). For boundary layer flows under laboratory conditions, the corresponding values are 70 000 (Winter & Gaudet 1973) and 19 000 (Mathis, Hutchins & Marusic 2009), although some limited but valuable turbulence data were acquired at 69 000 in the LCC facility by Winkel et al (2012), and at 650 000 in the neutral atmospheric boundary layer by Hutchins et al (2012).…”

Section: Introductionmentioning

confidence: 97%

Turbulent boundary layer statistics at very high Reynolds number

2015

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Measurements are presented in zero-pressure-gradient, flat-plate, turbulent boundary layers for Reynolds numbers ranging from Re τ = 2600 to Re τ = 72 500 (Re θ = 8400-235 000). The wind tunnel facility uses pressurized air as the working fluid, and in combination with MEMS-based sensors to resolve the small scales of motion allows for a unique investigation of boundary layer flow at very high Reynolds numbers. The data include mean velocities, streamwise turbulence variances, and moments up to 10th order. The results are compared to previously reported high Reynolds number pipe flow data. For Re τ 20 000, both flows display a logarithmic region in the profiles of the mean velocity and all even moments, suggesting the emergence of a universal behaviour in the statistics at these high Reynolds numbers.

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Section: Introductionmentioning

confidence: 97%

Turbulent boundary layer statistics at very high Reynolds number

2015

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“…(2) across a wide range of bulk Reynold's number. 8,[16][17][18][19] The compass of this work is to provide a phenomenological explanation to Eq. (2) based on a spectral budget of the longitudinal velocity thereby offering another perspective on the origin of its logarithmic (or power-law) character.…”

Section: Introductionmentioning

confidence: 99%

Logarithmic scaling in the longitudinal velocity variance explained by a spectral budget

Banerjee

Katul

2013

Physics of Fluids

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A logarithmic scaling for the streamwise turbulent intensity \documentclass[12pt]{minimal}\begin{document}$\sigma _u^2/{{u_*}^2}=B_1-A_1\break\ln \left({z}/{\delta }\right)$\end{document}σu2/u*2=B1−A1lnz/δ was reported across several high Reynolds number laboratory experiments as predicted from Townsend's attached eddy hypothesis, where u* is the friction velocity and z is the height normalized by the boundary layer thickness δ. A phenomenological explanation for the origin of this log-law in the intermediate region is provided here based on a solution to a spectral budget where the production and energy transfer terms are modeled. The solution to this spectral budget predicts A1 = (18/55)Co/κ2/3 and B1 = (2.5)A1, where Co and κ are the Kolmogorov and von Kármán constants. These predictions hold when very large scale motions do not disturb the k−1 scaling existing across all wavenumbers 1/δ < k < 1/z in the streamwise turbulent velocity spectrum Eu(k). Deviations from a k−1 scaling along with their effects on A1 and B1 are discussed using published data and field experiments.

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“…34,35 Nevertheless, the existence of an outer peak remains an open question. Based on the diagnostic plot, 36 Alfredsson et al 15 suggested that an outer peak does exist at z + = 0.81Re 24 and at Re τ = 1.4 × 10 6 from SLTEST. The symbol "×" marks the location where the large-scale component is measured.…”

Section: A Turbulence Intensity and Spectramentioning

confidence: 99%

“…Case 7 and that at Re τ = 62 000 is from Winkel et al 24 The symbol "×" marks the location of where the large-scale component is measured. Profiles are displaced 5 units of u/u τ for clarity.…”

Section: -6mentioning

confidence: 99%

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Inner-layer intensities for the flat-plate turbulent boundary layer combining a predictive wall-model with large-eddy simulations

et al. 2012

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Symmetry analysis and self-similar forms of fluid flow and heat-mass transfer in turbulent boundary layer flow of a nanofluid Phys. Fluids 24, 092003 (2012) Detuned resonances of Tollmien-Schlichting waves in an airfoil boundary layer: Experiment, theory, and direct numerical simulation Phys. Fluids 24, 094103 (2012) Asymptotic expansion of the solution of the steady Stokes equation with variable viscosity in a two-dimensional tube structure J. Math. Phys. 53, 103702 (2012) Large-eddy simulation of turbulent channel flow using explicit filtering and dynamic mixed models Phys. Fluids 24, 085105 (2012) Additional information on Phys. Fluids (2010)] to calculate the statistics of the fluctuating streamwise velocity in the inner region. Results, including spectra and moments up to fourth order, are compared with equivalent predictions using experimental time series, as well as with direct experimental measurements at Reynolds numbers Re τ = 7300, 13 600, and 19 000. The LES combined with the wall model are then used to extend the inner-layer predictions to Reynolds numbers Re τ = 62 000, 100 000, and 200 000 that lie within a gap in log (Re τ ) space between laboratory measurements and surface-layer, atmospheric experiments. The present results support a loglike increase in the near-wall peak of the streamwise turbulence intensities with Re τ and also provide a means of extending LES results at large Reynolds numbers to the nearwall region of wall-bounded turbulent flows. C 2012 American Institute of Physics.

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Turbulence profiles from a smooth flat-plate turbulent boundary layer at high Reynolds number

Cited by 28 publications

References 21 publications

Turbulent boundary layer statistics at very high Reynolds number

Turbulent boundary layer statistics at very high Reynolds number

Logarithmic scaling in the longitudinal velocity variance explained by a spectral budget

Inner-layer intensities for the flat-plate turbulent boundary layer combining a predictive wall-model with large-eddy simulations

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