Letter: Similarity model for corner roll in turbulent Rayleigh-Bénard convection

Wei-ping, Zhou; Chen, J. G.

doi:10.1063/1.5054647

Cited by 16 publications

(3 citation statements)

References 41 publications

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“…Interestingly, there is only one corner vortex in the LSC diagonal Y = 300mm − X near the heating plate and near the cooling plate. The corner vortex in the LSC diagonal is either not resolved in the particle tracks due to its tiny size or it is not present at frame 32600 because the LSC contains much more energy and the emergence of secondary structures is suppressed (Zhou and Jun, 2018) compared to cases studied in the literature via DNS. At a later time step, e.g.…”

Section: Phase (Ii) -Lsc Reorientationmentioning

confidence: 93%

Large scale reorientation in cubic Rayleigh-Bénard convection using particle tracking velocimetry

Barta,

Wagner

2024

Preprint

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We measured the three-dimensional velocity field of a large-scale reorientation in turbulent Rayleigh-Bénard convection with a high Rayleigh number Ra = $2.5\cdot 10^9$ by long-term particle tracking velocimetry measurements over 30 hours in a water-filled cubic cell with a side length of $L=300$ mm. Reorientations are characterized by the large-scale circulation in the flow changing its orientation from one cell diagonal to the other, and they are rare events; one can expect about one reorientation per day in our measurement. No other three-dimensional velocity field measurements of such events are known in the literature. Dominant flow structures during the reorientation are extracted from the measurement data using POD. The convergence of the POD is supported by applying the symmetries of the cubic RB cell to our data set to make it equiprobalbe so that it mimics a long time series of reorientation events. The decomposition reveals degenerate mode pairs, i.e. modes that have the same energy and describe the same state, which is consistent with reorientation results found in the literature for DNS of turbulent RBC in cubic cells. The first six modes of the decomposition account for about 70\% of the total energy and contain the most important coherent structures in the system. Modes 1-3 reflect the orientation and dynamics of the large-scale circulation, i.e., the primary flow structure, and modes 4-6 provide the orientation and dynamics of corner circulations, i.e., the secondary flow structures. A pure $Y$ roll structure is observed in the middle of the reorientation event.

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Section: Phase (Ii) -Lsc Reorientationmentioning

confidence: 93%

Large scale reorientation in cubic Rayleigh-Bénard convection using particle tracking velocimetry

Barta,

Wagner

2024

Preprint

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“…Recently, due to the discovery of heat-transport enhancement in the slim-box, turbulent convection in quasi-2D system has become one important topic in the community of RB convection (see, e.g., Refs. [28][29][30]). However, quasi-2D system is still fundamentally different from the true 2D case.…”

Section: Introductionmentioning

confidence: 99%

Effects of Prandtl number in two-dimensional turbulent convection*

Fang

Gao

et al. 2021

Chinese Phys. B

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We report a numerical study of the Prandtl-number (Pr) effects in two-dimensional turbulent Rayleigh–Bénard convection. The simulations were conducted in a square box over the Pr range from 0.25 to 100 and over the Rayleigh number (Ra) range from 107 to 1010. We find that both the strength and the stability of the large-scale flow decrease with the increasing of Pr, and the flow pattern becomes plume-dominated at high Pr. The evolution in flow pattern is quantified by the Reynolds number (Re), with the Ra and the Pr scaling exponents varying from 0.54 to 0.67 and –0.87 to –0.93, respectively. It is further found that the non-dimensional heat flux at small Ra diverges strongly for different Pr, but their difference becomes marginal as Ra increases. For the thermal boundary layer, the spatially averaged thicknesses for all the Pr numbers can be described by δθ ∼ Ra −0.30 approximately, but the local values vary a lot for different Pr, which become more uniform with Pr increasing.

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“…18 Moreover, many numerical simulations, physical experiments, and analytical solutions have been conducted to investigate the dynamics of buoyant plumes, [19][20][21][22][23][24][25][26][27][28][29][30][31] and the research for the plumes generated by thermal convection is also abundant. [32][33][34][35][36] In particular, Lavelle 37 described the behavior of hydrothermal plumes in a rotating stratified environment by a convection model, and he showed the model to be feasible when simulating the characteristics in the plume cap region and the circulation in the surrounding environment. Pham et al 38 investigated turbulent thermal plumes by direct numerical simulation (DNS) and large eddy simulation (LES).…”

Section: Introductionmentioning

confidence: 99%

Numerical simulation of two coalescing turbulent forced plumes in linearly stratified fluids

Lou

Jiang

et al. 2019

Physics of Fluids

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Letter: Similarity model for corner roll in turbulent Rayleigh-Bénard convection

Cited by 16 publications

References 41 publications

Large scale reorientation in cubic Rayleigh-Bénard convection using particle tracking velocimetry

Large scale reorientation in cubic Rayleigh-Bénard convection using particle tracking velocimetry

Effects of Prandtl number in two-dimensional turbulent convection*

Numerical simulation of two coalescing turbulent forced plumes in linearly stratified fluids

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