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Direct numerical simulations of Taylor–Couette turbulence: the effects of sand grain roughness

Published online by Cambridge University Press:  24 June 2019

Pieter Berghout*
Affiliation:
Physics of Fluids Group and Max Planck Center Twente, MESA+ Institute and J. M. Burgers Centre for Fluid Dynamics, University of Twente, P.O. Box 217, 7500AE Enschede, The Netherlands
Xiaojue Zhu
Affiliation:
Physics of Fluids Group and Max Planck Center Twente, MESA+ Institute and J. M. Burgers Centre for Fluid Dynamics, University of Twente, P.O. Box 217, 7500AE Enschede, The Netherlands Center of Mathematical Sciences and Applications, and School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA
Daniel Chung
Affiliation:
Department of Mechanical Engineering, University of Melbourne, Victoria 3010, Australia
Roberto Verzicco
Affiliation:
Physics of Fluids Group and Max Planck Center Twente, MESA+ Institute and J. M. Burgers Centre for Fluid Dynamics, University of Twente, P.O. Box 217, 7500AE Enschede, The Netherlands Dipartimento di Ingegneria Industriale, University of Rome ‘Tor Vergata’, Via del Politecnico 1, Roma 00133, Italy Gran Sasso Science Institute – Viale F. Crispi, 7 67100 L’Aquila, Italy
Richard J. A. M. Stevens
Affiliation:
Physics of Fluids Group and Max Planck Center Twente, MESA+ Institute and J. M. Burgers Centre for Fluid Dynamics, University of Twente, P.O. Box 217, 7500AE Enschede, The Netherlands
Detlef Lohse
Affiliation:
Physics of Fluids Group and Max Planck Center Twente, MESA+ Institute and J. M. Burgers Centre for Fluid Dynamics, University of Twente, P.O. Box 217, 7500AE Enschede, The Netherlands Max Planck Institute for Dynamics and Self-Organisation, Am Fassberg 17, 37077 Göttingen, Germany
*
Email address for correspondence: p.berghout@utwente.nl

Abstract

Progress in roughness research, mapping any given roughness geometry to its fluid dynamic behaviour, has been hampered by the lack of accurate and direct measurements of skin-friction drag, especially in open systems. The Taylor–Couette (TC) system has the benefit of being a closed system, but its potential for characterizing irregular, realistic, three-dimensional (3-D) roughness has not been previously considered in depth. Here, we present direct numerical simulations (DNSs) of TC turbulence with sand grain roughness mounted on the inner cylinder. The model proposed by Scotti (Phys. Fluids, vol. 18, 031701, 2006) has been modified to simulate a random rough surface of monodisperse sand grains. Taylor numbers range from $Ta=1.0\times 10^{7}$(corresponding to $Re_{\unicode[STIX]{x1D70F}}=82$) to $Ta=1.0\times 10^{9}$ ($Re_{\unicode[STIX]{x1D70F}}=635$). We focus on the influence of the roughness height $k_{s}^{+}$ in the transitionally rough regime, through simulations of TC with rough surfaces, ranging from $k_{s}^{+}=5$ up to $k_{s}^{+}=92$. We analyse the global response of the system, expressed both by the dimensionless angular velocity transport $Nu_{\unicode[STIX]{x1D714}}$ and by the friction factor $C_{f}$. An increase in friction with increasing roughness height is accompanied with enhanced plume ejection from the inner cylinder. Subsequently, we investigate the local response of the fluid flow over the rough surface. The equivalent sand grain roughness $k_{s}^{+}$ is calculated to be $1.33k$, where $k$ is the size of the sand grains. We find that the downwards shift of the logarithmic layer, due to transitionally rough sand grains exhibits remarkably similar behaviour to that of the Nikuradse (VDI-Forsch., vol. 361, 1933) data of sand grain roughness in pipe flow,regardless of the Taylor number dependent constants of the logarithmic layer. Furthermore, we find that the dynamical effects of the sand grains are contained to the roughness sublayer $h_{r}$ with $h_{r}=2.78k_{s}$.

Information

Type
JFM Papers
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
© The Author(s) 2019
Figure 0

Figure 1. Illustration of the Taylor–Couette (TC) set-up. (a) TC set-up with inner cylinder sand grain roughness: $\unicode[STIX]{x1D714}_{i}$ is the inner cylinder angular velocity, $r_{i}$ is the inner cylinder radius, $r_{o}$ is the outer cylinder radius and $d=r_{o}-r_{i}$ the gap width. (b) A zoom of the sand grain roughness that is modelled. The outer cylinder is stationary and smooth.

Figure 1

Figure 2. (a) Visual comparison between a surface with translational degrees of freedom as employed presently and (b) the original model by Scotti (2006) without translational degrees of freedom. (c) Probability density function (p.d.f.) of the surface height $h(\unicode[STIX]{x1D703},z)/k$ distribution of a rough surface with 952 roughness elements (B2). For the statistics of all rough surfaces used in this study, we refer the reader to the Appendix, table 2. (d) Schematic of an ellipsoidal building block of the rough surface. Every rectangular tile of size $2k\times 2k$ contains exactly one ellipsoid; $M$ indicates the centre of the tile. The radii $l_{1}=2.0k,l_{2}=1.4k,l_{3}=1.0k$ are kept constant for each ellipsoid to maintain a monodisperse rough surface. Randomness is ensured by giving the ellipsoid five degrees of freedom; two translational shifts of the centre of the ellipsoid from the centre of the tile $M$, ($\unicode[STIX]{x0394}z$ and $r_{i}\unicode[STIX]{x0394}\unicode[STIX]{x1D703}$) and three rotational degrees of freedom ($\unicode[STIX]{x1D6FC}_{1},\unicode[STIX]{x1D6FC}_{2},\unicode[STIX]{x1D6FC}_{3}$) from ($r,\unicode[STIX]{x1D703},z$) to ($l_{1},l_{2},l_{3}$). We also employ a constant translation of the centre of the ellipsoid in the radial direction, with $\unicode[STIX]{x0394}r=-0.5k$ from $r=r_{i}$.

Figure 2

Table 1. Input parameters, numerical resolution and global response of the simulations. We run four sets of simulations, which are separated by an empty horizontal line. Within every set we keep $Ta$ constant. $n_{\unicode[STIX]{x1D703}}\times n_{z}$ gives the number of ellipsoids in the streamwise ($\unicode[STIX]{x1D703}$) and spanwise ($z$) directions, respectively. $N_{ell}$ expresses the resolution ($N_{\unicode[STIX]{x1D703}}\times N_{z}$) per elementary building block of size $2k\times 2k$. $N_{\unicode[STIX]{x1D703}}\times N_{z}\times N_{r}$ presents the total resolution of the computational domain. $C_{f}$ is the friction factor. $Nu_{\unicode[STIX]{x1D714}}$ is the dimensionless torque. $k_{s}^{+}=1.33k^{+}$ is the equivalent sand grain roughness height in viscous units, where $k^{+}$ is the size of the sand grains (ellipsoids with axes $2k\times 1.4k\times k$, see figure 2), also in viscous units. $Re_{\unicode[STIX]{x1D70F}}$ is the friction Reynolds number, $Re_{\unicode[STIX]{x1D70F}}=(d/2)u_{\unicode[STIX]{x1D70F},i}/\unicode[STIX]{x1D708}$. $r_{i}^{+}\unicode[STIX]{x0394}\unicode[STIX]{x1D703}=\unicode[STIX]{x0394}z^{+}$ the grid spacing in the streamwise and spanwise directions in viscous units and $\unicode[STIX]{x0394}r^{+}$ is the minimal grid spacing, at the maximum roughness height, in the wall-normal direction in viscous units. Normalization in viscous units is done with respect to the inner cylinder, i.e. $u_{\unicode[STIX]{x1D70F}}=u_{\unicode[STIX]{x1D70F},i}$.

Figure 3

Figure 3. (a,c,e,g) Profiles of the streamwise – azimuthal – velocity $u^{+}$ (solid) and the angular velocity $\unicode[STIX]{x1D714}^{+}$ (dashed) versus the wall-normal distance $y^{+}$. Black solid lines indicate the viscous sublayer profile $u^{+}=y^{+}$ and the logarithmic law $u^{+}=\unicode[STIX]{x1D705}^{-1}\log y^{+}+B$, with $\unicode[STIX]{x1D705}=0.4$ and $B=5.0$. (b,d,f,h) Profiles of the streamwise velocity shift $\unicode[STIX]{x0394}u^{+}$ (solid) and the angular velocity shift $\unicode[STIX]{x0394}\unicode[STIX]{x1D714}^{+}$ (dashed). Every row corresponds to a constant Taylor number, (a,b) $Ta=1.0\times 10^{7}$, (c,d) $Ta=5.0\times 10^{7}$, (e,f) $Ta=5.0\times 10^{8}$ and (g,h) $Ta=1.0\times 10^{9}$, see table 1. The grey lines in (g) are logarithmic fits to the smooth profiles for $y^{+}=[150,500]$.

Figure 4

Figure 4. (a) Azimuthal velocity shift (Hama roughness function) $\unicode[STIX]{x0394}u^{+}$ versus the equivalent sand grain roughness height $k_{s}^{+}$, where $k_{s}^{+}=1.33k^{+}$. (b) Angular velocity shift $\unicode[STIX]{x1D714}^{+}$ versus $k_{s}^{+}$. Close overlap with the Nikuradse curve is observed in the transitionally rough regime. The overlap is slightly better for the angular velocity shift, for which we also obtain $k_{s}^{+}=1.33k^{+}$. The solid blue line represents the fully rough asymptote; $\unicode[STIX]{x0394}u^{+}=2.44\log (k_{s}^{+})+5.2-8.5$. The green lines represent the fully rough asymptotes obtained from the simulations, with $\unicode[STIX]{x1D705}_{u},\unicode[STIX]{x1D705}_{\unicode[STIX]{x1D714}},A_{u}$ and $A_{\unicode[STIX]{x1D714}}$ extracted from figure 3(g). The spread between statistically similar surfaces, with similar mean and maximum heights, is indicated by the vertical bar. $k_{s}$ is determinded by a best fit between the two data points in the fully rough regime (i.e. cases D4 and D5, see table 1) and the Nikuradse fully rough asymptote.

Figure 5

Figure 5. (a) Azimuthal velocity $u^{+}$ (solid) and the angular velocity $\unicode[STIX]{x1D714}^{+}$ (dashed) versus the wall-normal distance $y/k_{s}$, where $y=(r-h_{m})$ and $h_{m}$ is the mean roughness height. The three simulations with the highest roughness are plotted (D3, D4 and D5 respectively, see table 1) to convey collapse of the profiles for the fully rough cases. (b) The Nikuradse constant $\tilde{B}$ versus the equivalent sand grain roughness height $k_{s}^{+}$ for both the azimuthal velocity (squares) and the angular velocity (diamonds). Horizontal black line at $\tilde{B}=6.0$ gives the asymptotic value that is observed for fully rough behaviour.

Figure 6

Figure 6. Profiles of (a) the friction factor $C_{f}$, and (b) the Nusselt number $Nu_{\unicode[STIX]{x1D714}}$ versus the roughness height. $k/d$ is the roughness height $k$ relative to the gap width $d$. (c) Normalized friction coefficient $C_{f}(k_{s}^{+})/C_{f}(k_{s}^{+}=0)$ versus the equivalent sand grain roughness height $k_{s}^{+}$. (d) Normalized Nusselt number $Nu_{\unicode[STIX]{x1D714}}(k_{s}^{+})/Nu_{\unicode[STIX]{x1D714}}(k_{s}^{+}=0)$ versus the equivalent sand grain roughness height $k_{s}^{+}$.

Figure 7

Figure 7. (a) Moody representation, showing the friction factor $C_{f}$ as a function of the inner cylinder Reynolds number $Re_{i}$ for varying roughness height $k/d$. The solid line is the fit of the Prandtl friction law to the smooth-wall simulation data. (b) Compensated plot of the Nusselt number versus the Taylor number for constant $k/d$. In this regime, $Nu\propto Ta^{0.33}$. The solid black line indicates the asymptotic scaling of $Nu\propto Ta^{0.50}$.

Figure 8

Figure 8. (ac) Classical turbulent state: contour fields of the instantaneous azimuthal velocity $u(r,\unicode[STIX]{x1D703},z,t)$ for $Ta=5.0\times 10^{7}$ in the meridional plane. (a) Smooth-wall simulation (BS) in which we observe one ejecting plume and one impacting plume. (b) Rough inner cylinder $k/d=0.039$ (B2), with the roughness indicated in grey, exhibiting more plumes ejecting from the inner cylinder radially outwards. (c) Rough inner cylinder $k/d=0.073$, with the roughness indicated in grey, (B4) leading to a more chaotic flow field, with enhanced mixing and enhanced radial transport of the conserved angular velocity flux. (df) Ultimate turbulent state: contour fields of the instantaneous azimuthal velocity $u(r,\unicode[STIX]{x1D703},z,t)$ for $Ta=1.0\times 10^{9}$ in the meridional plane. (d) Smooth inner cylinder (DS) with many plumes ejecting, considerably more chaotic than in (a). (e) Inner cylinder wall roughness (indicated in grey) $k/d=0.035$ (D2) and (f) inner wall roughness $k/d=0.055$ (D5). For the rough cases, we observe more plumes ejecting and more mixing in the bulk, leading to enhanced radial transport of the angular velocity $J^{\unicode[STIX]{x1D714}}$, expressed in a higher $Nu_{\unicode[STIX]{x1D714}}$.

Figure 9

Figure 9. Contour field of the mean azimuthal velocity $\langle u\rangle _{\unicode[STIX]{x1D703},t}$ in the meridional plane for $Ta=1.0\times 10^{9}$. (a) Smooth inner cylinder (DS) (b). Inner cylinder wall roughness $k/d=0.0517$ (D2) and (c) inner wall roughness $k/d=0.0818$ (D5). The solid vertical lines indicate the height of the roughness sublayer $h_{r}$, calculated over the entire cylinder height.  plume ejection regions,  sheared regions,  plume impacting regions.

Figure 10

Figure 10. Contour of the time-averaged azimuthal velocity $\langle u\rangle _{t}^{+}$, zoomed in on only a few roughness elements, indicated in grey, for $Ta=1.0\times 10^{9}$ (D2). Flow is from left to right. Isolines of $\langle u\rangle _{t}^{+}$ overlay the contour. On the vertical axis, we display the wall-normal coordinate normalized by the gap width $d$ (left) and in viscous units (right). On the horizontal axis, we display the azimuthal coordinate, normalized by the gap width $d$ (below) and in viscous units (above).

Figure 11

Figure 11. (a) Profiles of the root mean square of the form-induced azimuthal velocity fluctuations $\tilde{u} ^{+}=(\langle u\rangle _{t}-\langle u\rangle _{\unicode[STIX]{x1D703},t})/u_{\unicode[STIX]{x1D70F}}$ at incremental heights above the roughness for identical location and conditions as in figure 9. The radial coordinate $r^{+}$ is made dimensionless by the roughness height $k^{+}$. The horizontal axis represents the azimuthal coordinate in viscous units. (b) Root mean squares of the azimuthally averaged form-induced velocity fluctuations. The profiles are obtained at three heights, namely where the Taylor roll impacts, ejects and in the centre (sheared region) – the extent of the regions are estimated from time-averaged velocity fields. The cyan line gives the mean over the entire height of the cylinder. The solid black lines indicate the maximum roughness height $k_{max}^{+}$ and the height of the roughness sublayer $h_{r}^{+}$.

Figure 12

Figure 12. Profiles of the mean streamwise velocity $\langle u\rangle _{\unicode[STIX]{x1D703},z,t}$ versus the radial coordinate $(r-r_{i})/d$, where $r_{i}$ is the radius of the inner cylinder and $d$ is the gap width. (a) Constant Taylor number $Ta=5.0\times 10^{8}$ and increasing roughness heights. The profiles exhibit clear ‘slaving’, i.e. the bulk velocity moves towards the velocity of the roughened cylinder. (b) Constant roughness height $k/d=0.060\pm 0.002$ for increasing Taylor number. Increased slaving of the bulk velocity is observed for increasing viscous scaled roughness height $k_{s}^{+}$, respectively: (blue) $k_{s}^{+}=9$, (green) $k_{s}^{+}=24$, (red) $k_{s}^{+}=47$ and (cyan) $k_{s}^{+}=65$.

Figure 13

Figure 13. (a) Root mean square of the mean streamwise velocity $(u)_{rms}^{+}=\langle \langle u^{2}\rangle _{\unicode[STIX]{x1D703},z,t}-\langle u\rangle _{\unicode[STIX]{x1D703},z,t}^{2}\rangle ^{1/2}/u_{\unicode[STIX]{x1D70F}}$ versus the radius $(r-r_{i})/d$ for $Ta=1.0\times 10^{9}$. We observe an overall decrease of the viscous scaled turbulence intensity for increasing roughness height $k_{s}^{+}$. (b) The viscous ${\hat{J}}_{\unicode[STIX]{x1D708}}^{\unicode[STIX]{x1D714}}(y^{+})\equiv -r^{3}\unicode[STIX]{x1D708}\unicode[STIX]{x2202}_{r}\langle \unicode[STIX]{x1D714}\rangle _{\unicode[STIX]{x1D703},z,t}/J_{\unicode[STIX]{x1D708}}^{\unicode[STIX]{x1D714}}(r_{o})$ (solid line) and Reynolds stress ${\hat{J}}_{w\unicode[STIX]{x1D714}}^{\unicode[STIX]{x1D714}}(y^{+})\equiv r^{3}\langle w\unicode[STIX]{x1D714}\rangle _{\unicode[STIX]{x1D703},z,t}/J_{\unicode[STIX]{x1D708}}^{\unicode[STIX]{x1D714}}(r_{o})$ (dashed line) terms of the conserved angular velocity flux ${\hat{J}}^{\unicode[STIX]{x1D714}}$ versus the wall-normal distance $y^{+}$ for $Ta=1.0\times 10^{9}$. The sum of the individual terms represents the total conserved angular velocity flux radially outwards. The black horizontal line at ${\hat{J}}^{\unicode[STIX]{x1D714}}=1.0$ is the sum of the two blue lines for the smooth-wall case. It is observed that ${\hat{J}}^{\unicode[STIX]{x1D714}}$ is conserved above the maximum roughness height (indicated by cross markers).

Figure 14

Table 2. Parameters describing the surface geometry (including both blank patches and sand grains). From left to right: case number in accordance with table 1. The roughness height is measured with respect to the inner cylinder location $r=r_{0}$. $\bar{k}/k_{max}$ is the mean roughness height respective to the maximum roughness height. $\bar{k}$ is the first moment of the roughness height distribution, $1/S\int _{S}h(\unicode[STIX]{x1D703},z)\,\text{d}S$. $k_{std}$ is the standard deviation of the surface height distribution $(1/S\int _{S}(h(\unicode[STIX]{x1D703},z)-\bar{k})^{2}\,\text{d}S)^{1/2}$, $Sk$ is the skewness $1/k_{std}^{3}S\int _{S}(h(\unicode[STIX]{x1D703},z)-\bar{k})^{3}\,\text{d}S$ and $Ku$ the excess kurtosis, $1/k_{std}^{4}S\int _{S}(h(\unicode[STIX]{x1D703},z)-\bar{k})^{4}\,\text{d}S-3$. $k_{rms}$ is the root mean square of the mean height $(1/S\int _{S}(h(\unicode[STIX]{x1D703},z))^{2}\,\text{d}S)^{1/2}$. $k_{p}$ is the mean peak height. The peaks are obtained by a peak finding algorithm (‘find_peak_local’ in van der Walt et al. (2014)) with zero threshold and a minimum spacing of the peaks of four grid nodes. $ES$ is the effective slope, $ES=1/L_{\unicode[STIX]{x1D703}}L_{z}\int _{L_{\unicode[STIX]{x1D703}}}\int _{L_{z}}|\unicode[STIX]{x2202}h(\unicode[STIX]{x1D703},z)/\unicode[STIX]{x2202}(r_{i}\unicode[STIX]{x1D703})|\,\text{d}z\,\text{d}(r_{i}\unicode[STIX]{x1D703})$ as introduced by Napoli et al. (2008). It can be shown that the $ES$ parameter is twice the often used solidity parameter $\unicode[STIX]{x1D706}$ (Jiménez 2004). $\unicode[STIX]{x1D6FC}$ is the surface gradient in the streamwise direction, $\unicode[STIX]{x2202}h(\unicode[STIX]{x1D703},z)/\unicode[STIX]{x2202}r_{i}\unicode[STIX]{x1D703}$ and $\unicode[STIX]{x1D6FC}_{rms}$ is the root mean square of this distribution. $S_{f}$ is the total frontal projected area of the roughness (in the streamwise direction). $S_{s}$ is the total windward wetted area of the roughness. $\unicode[STIX]{x1D6EC}$ is the density parameter which relates the latter two parameters by $\unicode[STIX]{x1D6EC}=(S/S_{f})(S_{f}/S_{s})^{-1.6}$ where $S$ is the total area of the surface without roughness (Sigal & Danberg 1990). The fractal dimension of surface B2 is calculated from the slope of the power density spectrum versus the wavenumber, $C\propto q^{-4.65}$, for details we refer to Persson et al. (2005). Here we find a Hurst exponent $H$ of 1.32 and a fractal dimension $D$ of 1.68. As such we conclude that the surface can at no scale be considered fractal.