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From zonal flow to convection rolls in Rayleigh–Bénard convection with free-slip plates

Published online by Cambridge University Press:  28 October 2020

Qi Wang
Affiliation:
Physics of Fluids Group and Max Planck Center Twente for Complex Fluid Dynamics, MESA+ Institute and J. M. Burgers Centre for Fluid Dynamics, University of Twente, Enschede, The Netherlands Department of Modern Mechanics, University of Science and Technology of China, Hefei 230027, PR China
Kai Leong Chong
Affiliation:
Physics of Fluids Group and Max Planck Center Twente for Complex Fluid Dynamics, MESA+ Institute and J. M. Burgers Centre for Fluid Dynamics, University of Twente, Enschede, The Netherlands
Richard J. A. M. Stevens
Affiliation:
Physics of Fluids Group and Max Planck Center Twente for Complex Fluid Dynamics, MESA+ Institute and J. M. Burgers Centre for Fluid Dynamics, University of Twente, Enschede, The Netherlands
Roberto Verzicco
Affiliation:
Physics of Fluids Group and Max Planck Center Twente for Complex Fluid Dynamics, MESA+ Institute and J. M. Burgers Centre for Fluid Dynamics, University of Twente, 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, 767100 L'Aquila, Italy
Detlef Lohse*
Affiliation:
Physics of Fluids Group and Max Planck Center Twente for Complex Fluid Dynamics, MESA+ Institute and J. M. Burgers Centre for Fluid Dynamics, University of Twente, Enschede, The Netherlands Max Planck Institute for Dynamics and Self-Organization, 37077 Göttingen, Germany
*
†Email address for correspondence: d.lohse@utwente.nl

Abstract

Rayleigh–Bénard (RB) convection with free-slip plates and horizontally periodic boundary conditions is investigated using direct numerical simulations. Two configurations are considered, one is two-dimensional (2-D) RB convection and the other one three-dimensional (3-D) RB convection with a rotating axis parallel to the plate, which for strong rotation mimics 2-D RB convection. For the 2-D simulations, we explore the parameter range of Rayleigh numbers $Ra$ from $10^{7}$ to $10^{9}$ and Prandtl numbers $Pr$ from $1$ to $100$. The effect of the width-to-height aspect ratio $\varGamma$ is investigated for $1\leqslant \varGamma \leqslant 128$. We show that zonal flow, which was observed, for example, by Goluskin et al. (J. Fluid. Mech., vol. 759, 2014, pp. 360–385) for $\varGamma =2$, is only stable when $\varGamma$ is smaller than a critical value, which depends on $Ra$ and $Pr$. The regime in which only zonal flow can exist is called the first regime in this study. With increasing $\varGamma$, we find a second regime in which both zonal flow and different convection roll states can be statistically stable. For even larger $\varGamma$, in a third regime, only convection roll states are statistically stable and zonal flow is not sustained. How many convection rolls form (or in other words, what the mean aspect ratio of an individual roll is), depends on the initial conditions and on $Ra$ and $Pr$. For instance, for $Ra=10^{8}$ and $Pr=10$, the aspect ratio $\varGamma _r$ of an individual, statistically stable convection roll can vary in a large range between $16/11$ and $64$. A convection roll with a large aspect ratio of $\varGamma _r = 64$, or more generally already with $\varGamma _r \gg 10$, can be seen as ‘localized’ zonal flow, and indeed carries over various properties of the global zonal flow. For the 3-D simulations, we fix $Ra=10^{7}$ and $Pr=0.71$, and compare the flow for $\varGamma =8$ and $\varGamma = 16$. We first show that with increasing rotation rate both the flow structures and global quantities like the Nusselt number $Nu$ and the Reynolds number $Re$ increasingly behave like in the 2-D case. We then demonstrate that with increasing aspect ratio $\varGamma$, zonal flow, which was observed for small $\varGamma =2{\rm \pi}$ by von Hardenberg et al. (Phys. Rev. Lett., vol. 15, 2015, 134501), completely disappears for $\varGamma =16$. For such large $\varGamma$, only convection roll states are statistically stable. In-between, here for medium aspect ratio $\varGamma = 8$, the convection roll state and the zonal flow state are both statistically stable. What state is taken depends on the initial conditions, similarly as we found for the 2-D case.

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), 2020. Published by Cambridge University Press
Figure 0

Figure 1. Sketch of (a) 2-D RB convection and (b) 3-D RB convection with spanwise rotation for free-slip plates and horizontally periodical conditions.

Figure 1

Table 1. Overview of the 2-D run simulations. The first three columns indicate the $Ra$, $Pr$ and $\varGamma$ range of the simulations. $N_z^{r}$ and $N_z^{z}$ indicate the number of grid points in the vertical direction for the simulations with initial conditions of roll states and shear flow, respectively. Here, $N_{BL}^{r}$ and $N_{BL}^{z}$ indicate the minimum number of grid points in the thermal boundary layer for convection roll states and zonal flow states, respectively. We note that the number of grid points in the boundary layer is always higher than that given by the recommendation of Shishkina et al. (2010) for the no-slip case, which is approximately $5$ to $9$ for this $Ra$ range, to ensure that the boundary layers are resolved. The number of grid points in the horizontal direction is generally equal to or larger than $N_x=N_z\times \varGamma$. For $Ra=10^{8}$ and $3\times 10^{8}$, $N_z^{z}=256$ is used only for the large $\varGamma$ cases (for example, $Ra=3\times 10^{8},\varGamma =32$ and 64) where very long simulations are performed, in order to test whether the zonal flow state can stably exist.

Figure 2

Figure 2. (a) Time evolution of $Nu$ for the zonal flow state for $Ra=10^{8}$ and $Pr=10$ with $\varGamma =4$ (black line) and $\varGamma =12$ (red line). (b) Temperature snapshot for the zonal flow state for $Ra=10^{8}$, $Pr=10$, $\varGamma =12$. (c) Time evolution of $Nu$ for $Ra=10^{8}$, $Pr=10$, $\varGamma =64$. The three curves correspond to three separate simulations with random perturbations added to the initial temperature field. In all the cases, the flow undergoes a transition from zonal flow to convection roll states, for which $Nu$ is larger. (d) Temperature snapshots at different times denoted by the red dashed lines for the simulation indicated by the red curve in panel (c). At $t=2000$, there is zonal flow, whereas later it features an increasing number of turbulent convection rolls. (e) The final two-roll state for $Ra=10^{8}$, $Pr=10$, $\varGamma =128$, and the zoom in of the two plume-ejecting regions. For all these simulations the initial velocity had a linear shear flow profile $u(z)=2z-1, w=0$, in order to trigger a zonal flow state.

Figure 3

Figure 3. Temperature snapshots of different roll states for $Ra=10^{8}$ and $Pr=10$ in a $\varGamma =12$ periodic cell. (a) Two-roll state; (b) four-roll state; (c) six-roll state; (d) eight-roll state. The different roll states are from initial conditions with different numbers of initial rolls.

Figure 4

Figure 4. Phase diagram in the (a) $Ra-\varGamma$ parameter space for $Pr=10$ and in the (b) $Pr-\varGamma$ parameter space for $Ra=10^{8}$. Black circles ($\bullet$) correspond to only zonal flow, red squares (${_\square}$) denote coexistence of zonal flow and convection rolls, and blue diamonds (${_\lozenge}$) indicate that only convection roll states are stable. The black hollow circles mark the cases shown in figure 2. Note that we also performed simulations for $Ra=10^{9}$, $Pr=10$ for convection roll states with $\varGamma =16$ and zonal flow state for $\varGamma =2$, to obtain $Nu\sim Ra^{\alpha }$ and $Re\sim Ra^{\beta }$ effective scaling relations for $Nu$ and $Re$.

Figure 5

Figure 5. Temperature snapshots of different roll states for $Ra=10^{8}$ and $Pr=10$ in a $\varGamma =16$ periodic cell. The dimensionless mean horizontal size of the convection roll $\varGamma _r$ (i.e. the mean aspect ratio of one individual roll) and the Nusselt number $Nu$ for each state are indicated. The different roll states are from initial conditions with different numbers of initial rolls. All these states can stably exist for a long time (see table 3 in appendix A) without undergoing a transition to other states.

Figure 6

Figure 6. Time evolution of (a) $Re$ and (b) $Nu$ for $Ra=10^{8}$, $Pr=10$, $\varGamma =16$ with an initial sixteen-roll state. Here, $Re_x=\sqrt {(Ra/Pr)}\sqrt {(\langle u^{2}\rangle _V)}$ is the horizontal Reynolds number and $Re_z=\sqrt {(Ra/Pr)}\sqrt {(\langle w^{2}\rangle _V)}$ the vertical one. (c) Temperature snapshots at different times. The roll merging can be seen, namely the flow undergoes a transition from the initial sixteen-roll state (I), to a fourteen-roll state (II), to a twelve-roll state (III) and then to the final ten-roll state (IV). The figure has the same colour scale as figure 5. (d) Time evolution of $Re$ for much longer time (on a log-scale) to show that the final ten-roll state is stable without undergoing a transition to another roll state.

Figure 7

Figure 7. Phase diagram for different roll states for (a) $Pr=10$, $\varGamma =16$ and (b) $Ra=10^{8}, \varGamma =16$. Circles denote that the corresponding roll state with the mean aspect ratio $\varGamma _r$ of an individual roll is stable, while crosses denote that the roll state is not stable. The solid line in panel (b) connects the minimal mean aspect ratio $\varGamma _{r,\rm {min}}$ of an individual convection roll for different $Pr$ for $\varGamma =16$, while the dashed line connects $\varGamma _{r,min}$ for different $Pr$ for $\varGamma =32$.

Figure 8

Figure 8. The (a) $Nu$ and (b) $Re$ as functions of $Ra$ for different convection roll states (see legend in panel (d)) for $Pr=10$, $\varGamma =16$ and the zonal flow state (see orange stars on solid orange line) for $Pr=10$, $\varGamma =2$. The (c) $Nu$ and (d) $Re$ as functions of $Pr$ for different roll states for $Ra=10^{8}$, $\varGamma =16$ and for the zonal flow state, for which we put $\varGamma =2$. Again, see the legend in panel (d). The inset in panel (c) shows $Nu$ as a function of $\varGamma _r$ for $Ra=10^{8}$ and different $Pr$ obtained for $\varGamma =16$ (hollow symbols) and $\varGamma =32$ (solid symbols). The solid symbols often overshadow the hollow ones as the symbol sizes are the same.

Figure 9

Table 2. The effective scaling exponents for fitted effective scaling relations $Nu \sim Ra^{\gamma _{Nu}}$, $Re \sim Ra^{\gamma _{Re}}$ and $Re \sim Pr^{\alpha _{Re}}$ for different roll states for $Pr=10$ obtained in an aspect ratio $\varGamma =16$ domain. The zonal flow data is for $\varGamma =2$.

Figure 10

Figure 9. (a) Time-averaged temperature fields for the $\varGamma _r=16$ roll state for different $Pr$ at $Ra=10^{8}$ obtained in a $\varGamma =32$ domain. (b) Instantaneous temperature field for $Pr=100$ for the $\varGamma _r=16$ state with $Ra=10^{8},\varGamma =32$. (c) Zoom-in for the time-averaged temperature fields in panel (a) for $Pr=1$ and 10. (d) Temperature profiles for the different $Pr$ at the centre point of plume-ejecting regions ($x/H\approx 16$) where the local $Nu$ is smallest. Panels (e) and (f) show the spatial dependence of $Nu(x)$ at the hot plate at $z=0$ (solid lines) and the cold plate at $z=1$ (dashed lines) for different $Pr$ for the (e) $\varGamma _r=16$ and the (f) $\varGamma _r=4$ roll states. Note that all curves are shifted such that the minimum local $Nu$ at the hot plate is located at $x/H=16$.

Figure 11

Figure 10. The 3-D RB convection with spanwise rotation: (a) $Nu$ and (b) $Re$ as functions of $1/Ro$ for $Ra=10^{7},Pr=0.71,\varGamma =16$ (black circles). For orientation with respect to the Nusselt number, the data for non-rotation ($1/Ro=0$, red diamond) and the 2-D cases with the same control parameters ($Ra=10^{7}$, $Pr=0.71$, $\varGamma =16$) for different roll aspect ratios $\varGamma _r$ (blue squares) are also shown; for these data points the value at the $1/Ro$ axis has no meaning. The Reynolds number, $Re$, for the $\varGamma _r=8/3$ (7702.85) and $\varGamma _r=2$ (7726.20) states are close to each other and cannot be differentiated in the figure.

Figure 12

Figure 11. The 3-D RB convection with spanwise rotation (the rotating axis is parallel to $y$ axis): top view snapshots of temperature fields at midheight ($z=H/2$, top row) and thermal boundary layer height ($z= z_{bl} = H/ (2 Nu$), bottom row) for $Ra=10^{7},Pr=0.71,\varGamma =16$ with different rotation rates. (a) $1/Ro=0$; (b) $1/Ro=1$; (c) $1/Ro=3.75$; (d) $1/Ro=10$; (e) $1/Ro=50$.

Figure 13

Figure 12. The 3-D RB convection with spanwise rotation (the rotating axis is parallel to $y$ axis): time evolution of $Nu$ for $Ra=10^{7}, Pr=0.71, 1/Ro=3.75$ with three different initial conditions for (a) $\varGamma =8$ and (b) $\varGamma =16$. Here, ${{IC}}_{0}$ means the initial condition with zero velocity and ${{IC}}_c/ {{IC}}_{a}$ denote cyclonic/anticyclonic shear flow as the initial condition. (c–h) Side-view temperature snapshots at midspanwise length ($y/H=\varGamma /2$) at different times denoted by the dashed lines in panel (a,b).

Figure 14

Table 3. Simulation details for all cases shown in figure 7(a). The columns from left to right indicate $Ra$, $Pr$, $\varGamma$, grid resolutions $N_x\times N_z$, the number of initial rolls $n^{(i)}$, the number of final convection rolls $n$, the mean aspect ratio of the convection rolls $\varGamma _r=\varGamma /n$, the Nusselt number $Nu$, the Reynolds number $Re$ based on root mean square of the global velocity, the horizontal Reynolds number $Re_x$ based on root mean square of the horizontal velocity, the vertical Reynolds number $Re_z$, the total simulation time $t_{tot}$, and the time $t_{avg}$ used to average $Nu$ and $Re$.

Figure 15

Table 4. Simulation details for the main cases in figure 7(b) for $\varGamma =16$ and 32. The table head is the same as table 3. Here, ‘s’ denotes that the final flow state is steady, which means that both Nu and Re are independent of time once the final state is achieved.

Figure 16

Figure 13. (a) Reynolds number ratio $Re_z/Re_x$ as a function of $\varGamma$ for the zonal flow state and (b) Reynolds number ratio $Re_z/Re_x$ as a function of $\varGamma _r$ for the convection roll state for $Ra=10^{8}$ with different $Pr$. Solid symbols in panel (b) for $\varGamma =16$ and hollow symbols for $\varGamma =32$. The solid symbols can hardly be seen as they are mostly hidden by the hollow symbols. The data in panel (b) can be well described by the effective scaling relation $Re_z/Re_x=0.86\varGamma _r^{-0.68}$.

Figure 17

Table 5. Simulations details for 3-D RB convection with spanwise rotation. The corresponding 2-D simulations are also included for comparison. The table head is similar to that of tables 3 and 4, apart from the inverse Rossby number $1/Ro$ for the 3-D cases. Here, ${IC_0}$ means initial conditions with zero velocity and conductive temperature profile with random perturbations and ${IC_c}$ means initial conditions with cyclonic shear flow $u(z)=2z-1$, $v=0$, $w=0$ and conductive temperature profile with random perturbations.

Wang et al. Supplementary Material

Temperature field showing transition from the zonal flow to the convection roll state

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