Intermittency, pressure and acceleration statistics from hot-wire measurements in wind-tunnel turbulence

Gylfason, Ármann; Ayyalasomayajula, Sathyanarayana; Warhaft, Z.

doi:10.1017/s002211200300747x

Cited by 66 publications

(72 citation statements)

References 30 publications

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“…Skewness S = γ 3 = −0.4 and kurtosis K = γ 4 = 20 were calculated. Wind-tunnel observations (Gylfason et al, 2004) suggest a power-law dependency of S and K on the Tay ≈ 28, which are in qualitative agreement with the directly calculated S and K. It has to be considered that the hot-wire measurements have a spatial resolution of about 10 · η and the smallest relevant scales cannot be resolved, which can explain the possible underestimation of S and K. In free-atmospheric clouds K ≈ 8 has been observed at scales ∼ 20 · η with strongly increasing values with increasing resolution (Siebert et al, 2010b).…”

Section: Hot-wire Measurements: Fine-scale Turbulencementioning

confidence: 99%

High-resolution measurement of cloud microphysics and turbulence at a mountaintop station

et al. 2015

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Abstract. Mountain research stations are advantageous not only for long-term sampling of cloud properties but also for measurements that are prohibitively difficult to perform on airborne platforms due to the large true air speed or adverse factors such as weight and complexity of the equipment necessary. Some cloud-turbulence measurements, especially Lagrangian in nature, fall into this category. We report results from simultaneous, high-resolution and collocated measurements of cloud microphysical and turbulence properties during several warm cloud events at the Umweltforschungsstation Schneefernerhaus (UFS) on Zugspitze in the German Alps. The data gathered were found to be representative of observations made with similar instrumentation in free clouds. The observed turbulence shared all features known for high-Reynolds-number flows: it exhibited approximately Gaussian fluctuations for all three velocity components, a clearly defined inertial subrange following Kolmogorov scaling (power spectrum, and second-and thirdorder Eulerian structure functions), and highly intermittent velocity gradients, as well as approximately lognormal kinetic energy dissipation rates. The clouds were observed to have liquid water contents on the order of 1 g m −3 and size distributions typical of continental clouds, sometimes exhibiting long positive tails indicative of large drop production through turbulent mixing or coalescence growth. Dimensionless parameters relevant to cloud-turbulence interactions, the Stokes number and settling parameter are in the range typically observed in atmospheric clouds. Observed fluctuations in droplet number concentration and diameter suggest a preference for inhomogeneous mixing. Finally, enhanced variance in liquid water content fluctuations is observed at high frequencies, and the scale break occurs at a value consistent with the independently estimated phase relaxation time from microphysical measurements.

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Section: Hot-wire Measurements: Fine-scale Turbulencementioning

confidence: 99%

High-resolution measurement of cloud microphysics and turbulence at a mountaintop station

et al. 2015

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“…Second, to our knowledge, there are no experimental or numerical data that directly address the conditional acceleration term of Eq. (9), though related conditional data are accumulating rapidly [17,18].…”

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confidence: 99%

“…For an incomplete list, see Ref. [18,20,21]. We compare in Table I the theoretical numbers above with the data of [21] in the atmospheric boundary layer at very high Reynolds numbers and the latest wind tunnel measurements [18] in grid turbulence.…”

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confidence: 99%

Towards a dynamical theory of multifractals in turbulence

Yakhot

Sreenivasan

2004

Physica A: Statistical Mechanics and its Applications

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Making use of the exact equations for structure functions, supplemented by the equations for dissipative anomaly as well as an estimate for the Lagrangian acceleration of fluid particles, we obtain a main result of the multifractal theory of turbulence. The central element of the theory is a dissipation cut-off that depends on the order of the structure function. An expression obtained for the exponents sn in the scaling relations ( Questions of small-scale universality in fluid turbulence hover around the universality of the scaling exponents ξ n,0 of velocity structure functions defined through relations such aswhere u(x) is the velocity component along the separation distance r, measured at the position x and ǫ is the mean rate of energy dissipation. Here r lies in the inertial range given by η << r << L, where L is the large-scale at which the energy is being injected and η ≡ (ν 3 /ǫ) 1/4 is the dissipation scale, ν being the fluid viscosity. The zero index in ξ n,0 shows that no powers of the transverse velocity increments are involved in this particular definition (1). Kolmogorov [1] assumed that the velocity fluctuations in the inertial range are independent of both L and η, and that ǫ, regarded as equal to the energy flux across scales, is the only relevant dynamical parameter. As is well known, Kolmogorov's proposal yields the linear relation ξ n,0 = n/3. Since, in the limit of vanishing viscosity (or, as η → 0), Kolmogorov's scaling theory combines the exact expression [2] S 3,0 = − 4 5 ǫr, it is reasonable to regard the theory loosely as dynamic. However, experimental and numerical data in three-dimensional turbulence have shown (see Ref.[3] for a recent account) that the scaling exponents ξ n,0 depart from n/3, and that there exists a more complicated nonlinear spectrum of scaling exponents ξ n,0 . Its theoretical explanation for the velocity field has proved to be elusive, though considerable progress has been made for passive scalars [4].In recent past, the problem of scaling exponents in turbulence has been analyzed within a general framework of the theory of multifractal (MF) processes reviewed in Ref. [5]. This approach has led to interesting interpretations and novel work (see [5,6] for incomplete list), but its shortcoming is the lack of connection with the dynamical equations. In this paper, a main relation of the MF theory is derived from dynamical equations, supplemented both by an order-of-magnitude estimate for the Lagrangian acceleration of a fluid particle, and the earlier work on dissipative anomaly [7,8].For background, we review here the main ideas of the inertial-range MF theory, whose basis are the assumptions that (a) the velocity increments δ r u have the formwhere u ′ ∼ δ L u may be regarded as the root-mean-square value of u, and (b) there exists a spectrum of exponents h related to the fractal dimension of their support D(h). Thus, (r/L)3−D(h) is proportional to the probability of the velocity increment falling within a sphere of radius r on a set of dimension D(h). It is clea...

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“…Specifically, they suggest that the flatness factor increases up to Re k = 700, but then decreases before eventually increasing again. However, the wind-tunnel experiments of [2] show no such transition. Direct numerical simulation (DNS) of turbulent flows has the potential to settle this argument because it is free from experimental ambiguities such as the effects of using Taylor's hypothesis, one-dimensional surrogates and so on.…”

Section: Introductionmentioning

confidence: 93%

Large-scale forcing with less communication in finite-difference simulations of stationary isotropic turbulence

Onishi

Baba

Takahashi

2011

Journal of Computational Physics

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Intermittency, pressure and acceleration statistics from hot-wire measurements in wind-tunnel turbulence

Cited by 66 publications

References 30 publications

High-resolution measurement of cloud microphysics and turbulence at a mountaintop station

High-resolution measurement of cloud microphysics and turbulence at a mountaintop station

Towards a dynamical theory of multifractals in turbulence

Large-scale forcing with less communication in finite-difference simulations of stationary isotropic turbulence

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