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Reynolds-number measurements for low-Prandtl-number turbulent convection of large-aspect-ratio samples

Published online by Cambridge University Press:  22 May 2013

James Hogg  and
Guenter Ahlers
James Hogg
Affiliation:
Department of Physics and ITST, University of California, Santa Barbara, CA 93106, USA
Guenter Ahlers*
Affiliation:
Department of Physics and ITST, University of California, Santa Barbara, CA 93106, USA
*
†Email address for correspondence: guenter@physics.ucsb.edu
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Abstract

We present experimental results for the Reynolds number ${\mathit{Re}}_{U} $ based on the horizontal mean-flow velocity $U$ and for ${\mathit{Re}}_{V} $ based on the root-mean-square horizontal fluctuation velocity $V$ for turbulent Rayleigh–Bénard convection in a cylindrical sample of aspect ratio $\Gamma = 10. 9$ over the Prandtl number range $0. 18\leq \mathit{Pr}\leq 0. 88$. The results were derived from space–time cross-correlation functions of shadowgraph images, using the elliptic approximation of He & Zhang (Phys. Rev. E, vol. 73, 2006, 055303). The data cover the Rayleigh number range from $3\times 1{0}^{5} $ to $2\times 1{0}^{7} $. We find that ${\mathit{Re}}_{U} $ is nearly two orders of magnitude smaller than the values given by the Grossmann–Lohse (GL) model (Grossmann & Lohse, Phys. Rev. E, vol. 66, 2002, 016305) for $\Gamma = 1. 00$ and attribute this difference to averaging caused by lateral random diffusion of the large-scale circulation cells in large-$\Gamma $ samples. For the fluctuations we found ${\mathit{Re}}_{V} = {\tilde {R} }_{0} {\mathit{Pr}}^{\alpha } {\mathit{Ra}}^{\eta } $, with ${\tilde {R} }_{0} = 0. 31$, $\alpha = - 0. 53\pm 0. 11$ and $\eta = 0. 45\pm 0. 03$. That result agrees well with the GL model. The close agreement of the coefficient ${\tilde {R} }_{0} $ must be regarded as a coincidence because the GL model was for $\Gamma = 1. 00$ and for a mean-flow velocity $U$.

JFM classification

Convection: Convection Turbulent Flows: Turbulent Flows
Type
Papers
Information
Journal of Fluid Mechanics , Volume 725 , 25 June 2013 , pp. 664 - 680
Copyright
©2013 Cambridge University Press 

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Hogg Supplementary Material

Movie 1 corresponding to Fig. 1a of the main document, running at approximately half of real-time speed. 11 mm square in the center of the cell, with Pr = 0.18, Ra = 1x10^{6}, 11 pixels/mm

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Video 1.2 MB

Hogg Supplementary Material

Movie 2 corresponding to Fig. 1b of the main document, running at approximately real-time speed. 94 mm square, with Pr=0.88, Ra=2x10^{7}, 5 pixels/mm.

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Video 5.1 MB

Hogg Supplementary Material

Movie 3 corresponding to Fig. 7a of the main document, running at approximately real-time speed. It shows processed shadowgraph images corresponding to Fig. 1b for Pr = 0.88 and Ra = 2x10^{7}. Only the dark (relatively warm) structures near the bottom of the sample remain. A 94 mm square was used with a resolution of 5 pixels/mm.

Download Hogg Supplementary Material(Video)
Video 5.2 MB

Hogg Supplementary Material

Movie 4 corresponding to Fig. 7b of the main document, running at approximately real-time speed. It shows processed shadowgraph images corresponding to Fig. 1b for Pr = 0.88 and Ra = 2x10^{7}. Only the light (relatively cold) structures near the top of the sample remain. A 94 mm square was used with a resolution of 5 pixels/mm.

Download Hogg Supplementary Material(Video)
Video 5 MB