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Stabilizing/destabilizing the large-scale circulation in turbulent Rayleigh–Bénard convection with sidewall temperature control

Published online by Cambridge University Press:  09 March 2021

Shengqi Zhang
Affiliation:
State Key Laboratory for Turbulence and Complex Systems, Peking University, Beijing 100871, PR China
Xin Chen
Affiliation:
Institute of Extreme Mechanics and School of Aeronautics, Northwestern Polytechnical University, Xi'an 710072, PR China
Zhenhua Xia*
Affiliation:
Department of Engineering Mechanics, Zhejiang University, Hangzhou 310027, PR China
Heng-Dong Xi
Affiliation:
Institute of Extreme Mechanics and School of Aeronautics, Northwestern Polytechnical University, Xi'an 710072, PR China
Quan Zhou
Affiliation:
Shanghai Key Laboratory of Mechanics in Energy Engineering, Shanghai Institute of Applied Mathematics and Mechanics, School of Mechanics and Engineering Science, Shanghai University, Shanghai 200072, PR China
Shiyi Chen*
Affiliation:
State Key Laboratory for Turbulence and Complex Systems, Peking University, Beijing 100871, PR China Department of Mechanics and Aerospace Engineering, Southern University of Science and Technology, Shenzhen 518055, PR China
*
†Email addresses for correspondence: xiazh@zju.edu.cn, chensy@sustech.edu.cn
†Email addresses for correspondence: xiazh@zju.edu.cn, chensy@sustech.edu.cn

Abstract

In this paper, we designed two different configurations with locally isothermal sidewalls, where the temperature is set to be the bulk temperature, to control the large-scale circulation in turbulent Rayleigh–Bénard convection, namely two-point control and four-point control. At fixed Rayleigh number $Ra=10^8$ and Prandtl number $Pr=2$, a series of direct numerical simulations are performed on both two-dimensional (2-D) and quasi-two-dimensional (quasi-2-D) cavities with both types of control, where the width of the control area is fixed at $\delta _c=0.05$ and the vertical distance from the cavity centre $h_c$ varies from 0 to 0.45 with an interval of 0.05. Our results show that the control effect depends on $h_c$, the control configurations as well as the flow dimensions. For 2-D cavities, both two-point control and four-point control suppress the flow reversal when $h_c \geq 0.05$, accompanied by the enhancement of vertical heat transfer and the strength of the large-scale circulation. For quasi-2-D cavities, the suppression of the flow reversals is obvious with two-point control and $h_c\geq 0.05$, while the effect is rather limited with four-point control. Further experiments with $Pr=5.7$ and $Ra$ up to $7.36\times10^8$ show that two-point control with $h_c=0.15$ can effectively suppress the flow reversal, while two-point control with $h_c=0$ can suppress the reversals at low $Ra=1.93\times 10^8$ and activate them at higher $Ra=7.36\times 10^8$, which agrees well with our numerical simulations.

Information

Type
JFM Papers
Copyright
© The Author(s), 2021. Published by Cambridge University Press
Figure 0

Figure 1. Sketches of sidewall controlled 2-D RBC with $h_c>0$: (a) two-point control and (b) four-point control. In quasi-2-D RBC, the $z$ direction points out from the paper and adiabatic conditions are applied on both sidewalls in the $z$ direction.

Figure 1

Figure 2. Plot of $\langle Nu\rangle _t$ in a cubic RBC cell at $Ra=1\times 10^8$ and $Pr=1$ obtained using the present code with different numbers of grid points. The results reported in Kooij et al. (2018) from the validated code GOLDFISH are also shown for comparison.

Figure 2

Table 1. Parameters of the 2-D and quasi-2-D simulations with $Ra=10^8$ and $Pr=2$.

Figure 3

Table 2. Parameters of simulations and experiments with $Ra>10^8$ and $Pr=5.7$. The $t_E$ value is estimated differently in simulations and experiments.

Figure 4

Figure 3. Time series $L(t)$ of 2-D simulations at $Ra=10^8$ and $Pr=2$: (a) no control; (b) two-point control with $h_c=0$; (c) two-point control with $h_c=0.45$; (d) four-point control with $h_c=0.05$; (e) four-point control with $h_c=0.25$; and (f) four-point control with $h_c=0.45$. The origins of time are chosen differently for each case (arb. orig.). Green and red circles represent reversal starts and ends, respectively.

Figure 5

Figure 4. Time series $L(t)$ of quasi-2-D simulations at $Ra=10^8$ and $Pr=2$: (a) no control; (b) two-point control with $h_c=0$; (c) two-point control with $h_c=0.3$; (d) four-point control with $h_c=0.05$; (e) four-point control with $h_c=0.3$; and (f) four-point control with $h_c=0.45$. The origins of time are chosen differently for each case (arb. orig.). Green and red circles represent reversal starts and ends, respectively.

Figure 6

Figure 5. Plots of $\langle \tau _-\rangle /\langle \tau \rangle _0$ and $\langle \tau _+\rangle /\langle \tau \rangle _0$ for the two-point control and $\langle \tau \rangle /\langle \tau \rangle _0$ for the four-point control from the (a) 2-D and (b) quasi-2-D simulations at $Ra=10^8$ and $Pr=2$ with $0\leq h_c\leq 0.45$. Here $\langle \tau \rangle _0$ is the mean time interval between successive reversals from the no-control case. Dotted lines represent the error bars of $\langle \tau \rangle _0$. Symbols $\triangle$ and $\triangledown$ denote $\langle \tau _-\rangle$ and $\langle \tau _+\rangle$ in the two-point control configuration, respectively. If the reversals are fully eliminated at certain $h_c$, there will be no symbol shown.

Figure 7

Figure 6. Temperature contours (colour), in-plane velocity vectors (black) and in-plane $\boldsymbol {F}^b$ vectors (white) of instantaneous fields in the $z=0$ plane. The lengths of the vectors are proportional to their magnitudes. The control parameters are $Ra=10^8$ and $Pr=2$. Panels: (a1,a2,a3) 2-D and two-point control, $h_c=0.25,\ t_E=2.5\times 10^3$; (b1,b2,b3) 2-D and four-point control, $h_c=0.25,\ t_E=3.5\times 10^3$; (c1,c2,c3) quasi-2-D and two-point control, $h_c=0.3,\ t_E=3.5\times 10^3$; (d1,d2,d3) quasi-2-D and four-point control, $h_c=0.3,\ t_E=0.7\times 10^3$. Panels (a1,b1,c1,d1) show the temperature contours and in-plane velocity vectors in the whole domain; (a2,b2,c2,d2) show the zoomed-in temperature contours, in-plane velocity vectors (black) and in-plane $\boldsymbol {F}^b$ vectors (white) near the upper-right control region (if it exists); (a3,b3,c3,d3) show the zoomed-in temperature contours, in-plane velocity vectors (black) and in-plane $\boldsymbol {F}^b$ vectors (white) near the lower-right control region.

Figure 8

Figure 7. Conceptual energy curves of dynamical picture demonstrating reversal suppression/activation effect: (a) $\mathcal {S}_x$, $\mathcal {S}_y$ and $\mathcal {R}_{\rm \pi}$ symmetry, corresponding to the ‘no-control’ case; (b) $\mathcal {R}_{\rm \pi}$ symmetry, corresponding to the present two-point control cases with $h_c\geq 0.05$; (c) $\mathcal {S}_x$, $\mathcal {S}_y$ and $\mathcal {R}_{\rm \pi}$ symmetry, corresponding to the reversal-enhancing cases with the two-point $h_c=0$ control and the four-point control; and (d) $\mathcal {S}_x$, $\mathcal {S}_y$ and $\mathcal {R}_{\rm \pi}$ symmetry, corresponding to the reversal-suppressing cases with the two-point $h_c=0$ control and the four-point control.

Figure 9

Figure 8. Relative time-averaged values of vertical and horizontal Nusselt numbers given by the 2-D and quasi-2-D simulations at $Ra=10^8$ and $Pr=2$. Here $\langle Nu_0\rangle _t$ denotes the vertical Nusselt number without sidewall control. (a) Relative time-averaged vertical Nusselt number difference $(\langle Nu \rangle _t-\langle Nu_0 \rangle _t)/\langle Nu_0 \rangle _t$. (b) Relative time-averaged horizontal Nusselt number $\langle Nu_h \rangle _t/\langle Nu_0 \rangle _t$.

Figure 10

Figure 9. Time-averaged kinetic energy and the corresponding contribution from $(1,1)$ and $(2,2)$ modes, in 2-D and quasi-2-D cases with $Ra=10^8$ and $Pr=2$: (a) 2-D cases and (b) quasi-2-D cases in the $z=0$ plane. The three dotted lines denote the corresponding time-averaged kinetic energy (black) and the contributions from the modes $(1,1)$ (red) and $(2,2)$ (blue) for the case without sidewall control.

Figure 11

Figure 10. Temperature contours and in-plane streamlines of fields in the $z=0$ plane and averaged during clockwise state between reversals in quasi-2-D cases with $Ra=10^8$ and $Pr=2$: (a) no control; (b) two-point control with $h_c=0.3$; and (c) four-point control with $h_c=0.3$.

Figure 12

Figure 11. Plots of $\hat {\delta }(t)$ of quasi-2-D experiments at $Ra\approx 1.93\times 10^8$ and $Pr=5.7$ with two-point control or without control: (a) no control; (b) two-point control with $h_c=0$; and (c) two-point control with $h_c=0.15$. Green and red circles represent reversal starts and ends respectively.

Figure 13

Figure 12. Mean reversal intervals from quasi-2-D experiments and simulations with two-point control configuration and without control at $Pr=5.7$. Experimental data of no-control cases are obtained from Chen et al. (2019).

Figure 14

Figure 13. Averaged temperature contours and in-plane streamlines of fields in the $z=0$ plane from the simulations of the no-control quasi-2-D cases with $Pr=5.7$: (a) $Ra=1.93\times 10^8$ and (b) $Ra=7.36\times 10^8$. The averaging is performed on the condition that the system is in the clockwise state.