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Effect of radius ratio on the sheared annular centrifugal turbulent convection

Published online by Cambridge University Press:  13 September 2024

Jun Zhong
Affiliation:
New Cornerstone Science Laboratory, Center for Combustion Energy, Key Laboratory for Thermal Science and Power Engineering of Ministry of Education, Department of Energy and Power Engineering, Tsinghua University, 100084 Beijing, PR China
Junyi Li*
Affiliation:
New Cornerstone Science Laboratory, Center for Combustion Energy, Key Laboratory for Thermal Science and Power Engineering of Ministry of Education, Department of Energy and Power Engineering, Tsinghua University, 100084 Beijing, PR China
Chao Sun*
Affiliation:
New Cornerstone Science Laboratory, Center for Combustion Energy, Key Laboratory for Thermal Science and Power Engineering of Ministry of Education, Department of Energy and Power Engineering, Tsinghua University, 100084 Beijing, PR China Department of Engineering Mechanics, School of Aerospace Engineering, Tsinghua University, 100084 Beijing, PR China
*
†Email addresses for correspondence: junyili@mail.tsinghua.edu.cn, chaosun@tsinghua.edu.cn
†Email addresses for correspondence: junyili@mail.tsinghua.edu.cn, chaosun@tsinghua.edu.cn

Abstract

We perform linear stability analysis and direct numerical simulations to study the effect of the radius ratio on the instability and flow characteristics of the sheared annular centrifugal Rayleigh–Bénard convection, where the cold inner cylinder and the hot outer cylinder rotate with a small angular velocity difference. With the shear enhancement, the thermal convection is suppressed and finally becomes stable for different radius ratios $\{\eta \in \mathbb {R}|0.2\leqslant \eta \le 0.95\}$. Considering the inhomogeneous distribution of shear stresses in the base flow, a new global Richardson number $Ri_g$ is defined and the marginal-state curves for different radius ratios are successfully unified in the parameter domain of $Ri_g$ and the Rayleigh number $Ra$. The results are consistent with the marginal-state curve of the wall-sheared classical Rayleigh–Bénard convection in the streamwise direction, demonstrating that the basic stabilization mechanisms are identical. Moreover, systems with small radius ratios exhibit greater geometric asymmetry. On the one hand, this results in a smaller equivalent aspect ratio for the system, accommodating fewer convection roll pairs; fewer roll pairs are more likely to cause a transition in the flow structure during shear enhancement. On the other hand, the shear distribution is more inhomogeneous, allowing for an outward shift of the convection region and the elevation of bulk temperature under strong shear.

Information

Type
JFM Papers
Copyright
© The Author(s), 2024. Published by Cambridge University Press
Figure 0

Figure 1. Schematic diagram of the flow configuration in the sheared ACRBC system with (a) a small radius ratio $\eta =r^*_i/r^*_o=0.3$ and (b) a large radius ratio $\eta =0.8$ in the stationary reference frame. Here, $r^*_{i,o}, \varOmega ^*_{i,o}$ and $\theta ^*_{i,o}$ are the radius, angular speed and temperature of the inner and outer cylinders, respectively, and $L^*$ is the gap between two cylinders.

Figure 1

Figure 2. The critical Rayleigh number $Ra_c$ vs non-dimensional rotating speed difference $\varOmega$ at $\eta =0.2,0.3,0.5,0.7,0.9,0.95$. Each curve indicates the marginal states at one radius ratio $\eta$, namely the flow is unstable on the left side of the curve and stable on the right side. The horizontal dashed line represents the critical Rayleigh number $Ra_c=1708$ of RBC.

Figure 2

Figure 3. The local Richardson number $Ri_b$ defined by the base flow varies with normalized radius $\hat {r}=(r-r_i)$ for the marginal states at different $\eta$ and (a) $Ra=10^4$, (b) $Ra=10^6$ and (c) $Ra=10^7$.

Figure 3

Figure 4. (a) The critical Rayleigh number $Ra_c$ vs the global Richardson number $Ri_g$ for six radius ratios. The black line indicates the critical Rayleigh number vs the Richardson number of the transverse rolls in wall-sheared RBC. (b) A closer look at (a), showing the critical global Richardson number vs the radius ratio for $Ra=10^5,10^6,10^7,10^8$.

Figure 4

Figure 5. Eigenfunctions $(\boldsymbol {u'}, \theta ')$ of the critical modes for (a–e) $\eta =0.3$ and ( f–j) $\eta =0.7$ at corresponding Rayleigh numbers and global Richardson numbers. The contour denotes the temperature distribution and the vectors denote the velocity.

Figure 5

Figure 6. (a) The critical azimuthal wavenumber $n_c$ vs $Ra$ at $\eta =0.3,0.5,0.7,0.9$. (b) Variation of energy generation proportions $-W_{Ta}/W_{cB}$ and $D_\nu /W_{cB}$ with the global Richardson number $Ri_g$, for the modes of azimuthal wavenumber $n=1$ and $n=6$ at $Ra=10^7, \eta =0.3$. The blue vertical dashed line shows the critical $Ri_g$ for $n=6$ and the red vertical dashed line shows the critical $Ri_g$ for $n=1$.

Figure 6

Figure 7. The distribution of main simulation parameters and the corresponding azimuthal resolutions $N_\varphi$ in the $(\eta, Ri_g)$ domain under (a) $Ra=10^6$ and (b) $Ra=10^7$. The black solid lines denote the marginal state.

Figure 7

Figure 8. (a) Time series of the mean perturbation energy $E'_k=\langle |\boldsymbol {u'}|^2\rangle _{V}/2$ for three cases with $(\eta, Ri_g)=(0.3, 1)$, $(0.3, 10)$ and $(0.7, 1)$ at $Ra=10^7$. The dashed lines represent the predictions of LSA. (b–d) The perturbation temperature fields at the instants marked in panel (a) for corresponding cases.

Figure 8

Figure 9. Typical snapshots of the instantaneous temperature field on the $r-\varphi$ plane at $Ri_g=\infty,10,5,2,1$ for (a–e) $\eta =0.3$ and ( f–j) $\eta =0.7$. $Ra=10^6$.

Figure 9

Figure 10. Radial distribution of azimuthally and time-averaged temperature $\langle \theta \rangle _{t,\varphi }$ at different shear strengths for (a) $\eta =0.3$ and (b) $\eta =0.7$. $Ra=10^6$.

Figure 10

Figure 11. Variation of (a,d) $Nu_h$, (b,e) $Nu_\omega$ and (c, f) $\gamma$ with $Ri_g$ at $\eta =0.3$, $0.5$, $0.7$ and $0.9$. The data in the first row (a–c) are calculated at $Ra=10^6$, while the data in the second row (d–f) are calculated at $Ra=10^7$.

Figure 11

Table 1. Simulation parameters.