Transitions to turbulence in helium gas

Heslot, F.; Castaing, B.; Libchaber, Albert

doi:10.1103/physreva.36.5870

Cited by 436 publications

(266 citation statements)

References 16 publications

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“…It has been reported in experiments starting with Heslot et al (1987) and Castaing et al (1989). An almost exponential shape was emphasized by Yakhot (1989) on the basis of a hierarchy of moment equations for the temperature fluctuations.…”

Section: Total Temperature and Its Fluctuationsmentioning

confidence: 99%

Fine-scale statistics of temperature and its derivatives in convective turbulence

Emran

Schumacher

2008

J. Fluid Mech.

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We study the fine-scale statistics of temperature and its derivatives in turbulent RayleighBénard convection. Direct numerical simulations are carried out in a cylindrical cell with unit aspect ratio filled with a fluid with Prandtl number equal to 0.7 for Rayleigh numbers between 10 7 and 10 9 . The probability density function of the temperature or its fluctuations is found to be always non-Gaussian. The asymmetry and strength of deviations from the Gaussian distribution are quantified as a function of the cell height. The deviations of the temperature fluctuations from the local isotropy, as measured by the skewness of the vertical derivative of the temperature fluctuations, decrease in the bulk, but increase in the thermal boundary layer for growing Rayleigh number, respectively. Similar to the passive scalar mixing, the probability density function of the thermal dissipation rate deviates significantly from a log-normal distribution. The distribution is fitted well by a stretched exponential form. The tails become more extended with increasing Rayleigh number which displays an increasing degree of small-scale intermittency of the thermal dissipation field for both the bulk and the thermal boundary layer. We find that the thermal dissipation rate due to the temperature fluctuations is not only dominant in the bulk of the convection cell, but also yields a significant contribution to the total thermal dissipation in the thermal boundary layer. This is in contrast to the ansatz used in scaling theories and can explain the differences in the scaling of the total thermal dissipation rate with respect to the Rayleigh number.

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Section: Total Temperature and Its Fluctuationsmentioning

confidence: 99%

Fine-scale statistics of temperature and its derivatives in convective turbulence

Emran

Schumacher

2008

J. Fluid Mech.

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“…The dynamics of the LSC include oscillations [6,7,8,12,13,14,15,16,17,18,19] in which the orientation of the upper half of the LSC oscillates out of phase with the lower half [9,20].…”

Section: Introductionmentioning

confidence: 99%

A model of diffusion in a potential well for the dynamics of the large-scale circulation in turbulent Rayleigh–Bénard convection

2008

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Experimental measurements of properties of the large-scale circulation (LSC) in turbulent convection of a fluid heated from below in a cylindrical container of aspect ratio one are presented and used to test a model of diffusion in a potential well for the LSC. The model consists of a pair of stochastic ordinary differential equations motivated by the Navier-Stokes equations. The two coupled equations are for the azimuthal orientation θ 0 , and for the azimuthal temperature amplitude δ at the horizontal midplane. The dynamics is due to the driving by Gaussian distributed white noise that is introduced to represent the action of the small-scale turbulent fluctuations on the large-scale flow. Measurements of the diffusivities that determine the noise intensities are reported. Two time scales predicted by the model are found to be within a factor of two or so of corresponding experimental measurements. A scaling relationship predicted by the model between δ and the Reynolds number is confirmed by measurements over a large experimental parameter range. The Gaussian peaks of probability distributions p(δ) and p(θ 0 ) are accurately described by the model; however the non-Gaussian tails of p(δ) are not. The frequency, angular change, and amplitude bahavior during cessations are accurately described by the model when the tails of the probability distribution of δ are used as experimental input.

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“…Intermittent bursts of thermal plumes from the thermal boundary layers and the coherent largescale circulation, which modifies the boundary layer via its shear, are found to coexist in the convection cell. These salient features are directly related to the heat transport across the cell, and have been adopted in several theoretical models [3][4][5] to explain the observed scaling laws in the heat flux and temperature statistics [4,6]. In this Letter, we describe a novel convection experiment in a closed cell with rough upper and lower surfaces.…”

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confidence: 99%

Enhanced Heat Transport in Turbulent Convection over a Rough Surface

Tong

1998

Phys. Rev. Lett.

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A novel convection experiment is conducted in a cell with rough upper and lower surfaces. The heat transport across the rough cell is found to be increased by more than 76%. Flow visualization and nearwall temperature measurements reveal new dynamics for the emission of thermal plumes. The discovery of the enhanced heat transport has important applications in engineering and atmospheric convection.[ S0031-9007(98) PACS numbers: 47.27. Te, 05.60. + w, 44.25. + f, 47.27.Nz Turbulent flows over a rough surface are ubiquitous in nature. An example is convection in the atmosphere and oceans, where the underlying surfaces are almost always rough. The study of turbulence over a rough surface is of fundamental interest for understanding the structure and dynamics of turbulent boundary layers and is also relevant to many practical applications, ranging from effective heat transfer for a reentry vehicle to turbulent drag reduction of a commercial aircraft. Our current knowledge about the roughness effect on turbulent flows comes largely from experiments in wind tunnels and other open systems [1], where the disturbance flow produced by a rough wall is confined in the near-wall region and is quickly discharged to the downstream. Because of these reasons the surface roughness usually does not perturb the turbulent bulk region very much, and its effect can often be described by rescaling the relevant parameters with the surface roughness height k [2]. This situation is changed completely for flows in a closed cell, in which the disturbances produced by the boundaries are inevitably mixed into the turbulent bulk region.Turbulent Rayleigh-Bénard convection is an example of such a closed system, which has attracted much attention in recent years [3]. Intermittent bursts of thermal plumes from the thermal boundary layers and the coherent largescale circulation, which modifies the boundary layer via its shear, are found to coexist in the convection cell. These salient features are directly related to the heat transport across the cell, and have been adopted in several theoretical models [3][4][5] to explain the observed scaling laws in the heat flux and temperature statistics [4,6]. In this Letter, we describe a novel convection experiment in a closed cell with rough upper and lower surfaces. It is found that when k becomes much larger than the thermal boundary layer thickness d, the heat transport across the rough cell is increased by more than 76%. Flow visualization and near-wall temperature measurements reveal that the large-scale circulation interacts with the surface roughness and produces more thermal plumes from the tip of the rough elements. The striking effect of the surface roughness provides new insights into the nature of convective turbulence, and also has a myriad of applications in engineering, geography, and meteorology.The experiment is conducted in a cylindrical cell filled with water. Details about the apparatus have been described elsewhere [7], and here we mention only some key points. The rough upper and...

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Transitions to turbulence in helium gas

Cited by 436 publications

References 16 publications

Fine-scale statistics of temperature and its derivatives in convective turbulence

Fine-scale statistics of temperature and its derivatives in convective turbulence

A model of diffusion in a potential well for the dynamics of the large-scale circulation in turbulent Rayleigh–Bénard convection

Enhanced Heat Transport in Turbulent Convection over a Rough Surface

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