Measured Local Heat Transport in Turbulent Rayleigh-Bénard Convection

Shang, Xiaodong; Qiu, Xin; Tong, Penger; Xia, Ke‐Qing

doi:10.1103/physrevlett.90.074501

Cited by 134 publications

(120 citation statements)

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“…This asymmetry in the vertical flux distribution was interpreted to be caused by the plumes [7]. We use these results to test our scheme of plume extraction.…”

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confidence: 97%

“…The velocity v(t) was measured using a two-component laser Doppler velocimetry (LDV) system [8] while the temperature T (t) was measured using a small movable thermistor of 0.2 mm in diameter, 15 ms in time constant, and 1 mK/Ω in temperature sensitivity. The velocity and temperature measurements were simultaneously taken using a multi-channel LDV interface module to synchronize the data acquisition [7]. A triggering pulse from the LDV signal processor initiates the acquistion of an analog temperature signal.…”

mentioning

confidence: 99%

“…Our method makes explicit use of the physical intuition that plumes are generated by buoyancy and thus the velocity of a plume should correlate with the temperature fluctuation. Using this method, we obtain the temperature dependence of the plume velocity and the average local heat flux in the vertical direction at the cell center.The experimental measurements that we use to illustrate and test our scheme of plume extraction were taken in an aspect-ratio-one cylindrical cell of height L = 20.5 cm and filled with water [7]. The velocity v(t) was measured using a two-component laser Doppler velocimetry (LDV) system[8] while the temperature T (t) was measured using a small movable thermistor of 0.2 mm in diameter, 15 ms in time constant, and 1 mK/Ω in temperature sensitivity.…”

mentioning

confidence: 99%

“…The experimental measurements that we use to illustrate and test our scheme of plume extraction were taken in an aspect-ratio-one cylindrical cell of height L = 20.5 cm and filled with water [7]. The velocity v(t) was measured using a two-component laser Doppler velocimetry (LDV) system [8] while the temperature T (t) was measured using a small movable thermistor of 0.2 mm in diameter, 15 ms in time constant, and 1 mK/Ω in temperature sensitivity.…”

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confidence: 99%

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Extraction of Plumes in Turbulent Thermal Convection

et al. 2004

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We present a scheme to extract information about plumes, a prominent coherent structure in turbulent thermal convection, from simultaneous local velocity and temperature measurements. Using this scheme, we study the temperature dependence of the plume velocity and understand the results using the equations of motion. We further obtain the average local heat flux in the vertical direction at the cell center. Our result shows that heat is not mainly transported through the central region but instead through the regions near the sidewalls of the convection cell. where v is the velocity field, p the pressure divided by density, T the temperature field, andẑ is the unit vector in the vertical direction. Furthermore, δT = T − T 0 where T 0 is the mean temperature of the bulk fluid, g is the acceleration due to gravity and α, ν, and κ are respectively the volume expansion coefficient, kinematic viscosity and thermal diffusivity of the fluid. The state of fluid motion is characterized by the geometry of the cell and two dimensionless parameters: the Rayleigh number, Ra = αg∆L 3 /(νκ), which measures how much the fluid is driven and the Prandtl number, Pr = ν/κ, which is the ratio of the diffusivities of momentum and heat of the fluid. Here ∆ is the maintained temperature difference between the bottom and the top, and L is the height of the cell. When Ra is sufficiently large, the convective motion becomes turbulent. In turbulent convection, local velocity and temperature measurements taken at a point within the convection cell display complex fluctuations in time. On the other hand, visualization of the flow reveals recurring coherent structures. One prominent coherent structure is a plume, which is a mushroom-like flow generated by buoyancy. Thus at least two strategies can be employed to study turbulent thermal convection or turbulent flows in general. One is to analyze and understand the fluctuations of the local measurements. The other is to characterize the coherent structures and study and understand their dynamics. These two approaches are not independent but provide complementary knowledge of turbulent flows. In particular, there is the natural question of whether and how information about the coherent structures can be extracted from the local measurements.For turbulent flows not driven by buoyancy, various methods including proper orthogonal decomposition, conditional sampling and wavelet analysis have been proposed to identify coherent vortical structures from local velocity measurements [2]. On the other hand, much less work has been done in identifying plumes or extracting information about plumes in turbulent thermal convection [3,4,5]. Belmonte and Libchaber[3] used the skewness of the temperature derivative as a signature of the plumes. Zhou and Xia[4] associated the difference in the skewness of the positive and negative parts of the temperature difference with the presence of plumes and identified the plumes whenever the temperature difference becomes larger than a chosen threshold [6]. In Ref.[5], plu...

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“…This asymmetry in the vertical flux distribution was interpreted to be caused by the plumes [7]. We use these results to test our scheme of plume extraction.…”

mentioning

confidence: 97%

mentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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Extraction of Plumes in Turbulent Thermal Convection

et al. 2004

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“…More energy is pumped into kinetic energy through the mean buoyancy flux (left-hand pathway in Fig. 3), as a result of small-scale convective plumes being swept along the boundary layer and merging into larger scales [2,22,32]. The changes in " È z and È 0 z are gradual with Ra, but the ratio " È z =È 0 z increases rapidly at Ra > 10 11 .…”

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Completing the Mechanical Energy Pathways in Turbulent Rayleigh-Bénard Convection

2013

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A new, more complete view of the mechanical energy budget for Rayleigh-Bénard convection is developed and examined using three-dimensional numerical simulations at large Rayleigh numbers and Prandtl number of 1. The driving role of available potential energy is highlighted. The relative magnitudes of different energy conversions or pathways change significantly over the range of Rayleigh numbers Ra $ 10 7 -10 13 . At Ra < 10 7 small-scale turbulent motions are energized directly from available potential energy via turbulent buoyancy flux and kinetic energy is dissipated at comparable rates by both the largeand small-scale motions. In contrast, at Ra ! 10 10 most of the available potential energy goes into kinetic energy of the large-scale flow, which undergoes shear instabilities that sustain small-scale turbulence. The irreversible mixing is largely confined to the unstable boundary layer, its rate exactly equal to the generation of available potential energy by the boundary fluxes, and mixing efficiency is 50%. Introduction.-Flow in a horizontal layer of fluid heated uniformly from below and cooled from above-RayleighBénard convection (RBC)-is an idealized problem from which much can be learned about the nature of convective flow and heat transfer. Recent attention has focused on the relative importance of the boundary layer and interior behavior, including flow structures, at very large Rayleigh numbers [1][2][3][4][5][6]. The salient features of the flow can be usefully interpreted in terms of the energy budget, and previous work has considered the kinetic and thermal energy [2,3,7,8]. However, the existing framework is incomplete and provides limited insight into the exchange of mechanical energy among different forms or between fluid motions of different scales. In particular, the nature of the turbulent energy cascade in RBC is still not fully understood [3] and improved models are needed.Convection is caused by the generation of mechanical energy in the form of available potential energy (APE) by boundary buoyancy fluxes. APE is a subset of the total gravitational potential energy (GPE) and is the form essential for motions [9][10][11]. A complete mechanical energy framework has been recently developed for the case of horizontal convection forced by differential heating at one horizontal boundary [12,13] and recently extended to RBC [14]. In RBC there is a release of APE from thermal boundary layers adjacent to the top and bottom boundaries, driving flow at various scales, while complex feedbacks further distribute the potential and kinetic energy among the different scales or, through mixing, to the background potential energy. The role of APE in RBC was recognized in quantifying the overall rate of irreversible mixing [14]. Here we show that an account of GPE, its partition into available and background forms, and its links to kinetic energy at various scales are essential in a full understanding of the turbulent energy cascade and the relative roles of the boundary layer and the interior.

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Fabrication and Characterization of Miniaturized Thermocouples for Measurements in Flows

Munzel

Kittel

Springer Proceedings in Physics

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Measured Local Heat Transport in Turbulent Rayleigh-Bénard Convection

Cited by 134 publications

References 14 publications

Extraction of Plumes in Turbulent Thermal Convection

Extraction of Plumes in Turbulent Thermal Convection

Completing the Mechanical Energy Pathways in Turbulent Rayleigh-Bénard Convection

Fabrication and Characterization of Miniaturized Thermocouples for Measurements in Flows

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