2016
DOI: 10.1063/1.4943599
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Mean-velocity profile of smooth channel flow explained by a cospectral budget model with wall-blockage

Abstract: A series of recent studies has shown that a model of the turbulent vertical velocity variance spectrum (Fvv) combined with a simplified cospectral budget can reproduce many macroscopic flow properties of turbulent wall-bounded flows, including various features of the mean-velocity profile (MVP), i.e., the “law of the wall”. While the approach reasonably models the MVP’s logarithmic layer, the buffer layer displays insufficient curvature compared to measurements. The assumptions are re-examined here using a dir… Show more

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Cited by 20 publications
(12 citation statements)
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“…In contrast to previous studies, the approach proposed here solves for φ m and φ h explicitly, in terms of φ w and φ b and other parameters related to the spectra. This approach avoids the need for parametrizations of terms in the cospectral budget, which may be particularly ill‐suited to low Reynolds numbers (McColl et al , 2016). Our model can be viewed as describing the partitioning of kinetic ( φ w , F ww ) and potential energy ( φ b , F bb ) between the turbulent transport of momentum ( φ m ) and heat ( φ h ).…”
Section: Discussionmentioning
confidence: 99%
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“…In contrast to previous studies, the approach proposed here solves for φ m and φ h explicitly, in terms of φ w and φ b and other parameters related to the spectra. This approach avoids the need for parametrizations of terms in the cospectral budget, which may be particularly ill‐suited to low Reynolds numbers (McColl et al , 2016). Our model can be viewed as describing the partitioning of kinetic ( φ w , F ww ) and potential energy ( φ b , F bb ) between the turbulent transport of momentum ( φ m ) and heat ( φ h ).…”
Section: Discussionmentioning
confidence: 99%
“…Fourth, the model spectra used in this study are highly idealized, and their fit with DNS spectra is not always perfect (Figure ). We have deliberately chosen functional forms with heritage in the literature (Katul et al , 2013; Li et al , 2015b; McColl et al , 2016) that capture crossovers between different scaling regimes, but also keep the analysis tractable. Many corrections could be made to the idealized forms used here: for instance, an exponential correction could be added at high wavenumbers to account for viscous truncation of the inertial range at low Reynolds number.…”
Section: Discussionmentioning
confidence: 99%
“…where S is the mean streamwise velocity gradient along the vertical direction, A UU is a parameter in the gradient diffusion model for the flux transfer term, A U is the Rotta parameter associated with the slow-component of ⇡ uw , 29 whereas the (3/5)P uw term is associated with the fast-component (wall blocking is ignored at z sufficiently far from the boundary for reasons discussed elsewhere 30 ), and ⌧(k) = ✏ 1/3 k 2/3 is a wavenumber-dependent relaxation time scale derived from K41 dimensional considerations 31 where ✏ is the mean TKE dissipation rate. In statistical mechanics, the relaxation time scale measures the time required for a perturbed system to go back to an equilibrium state.…”
Section: Theorymentioning
confidence: 99%
“…Despite the maximum simplicity of this approach relative to the original derivation in Brutsaert [], the proposed structure function approach suffers from a number of limitations. To begin with, it is known that near roughness elements, production, and dissipation of TKE are not in balance and production may be up to 1.7 times larger than ϵ [ Pope , ] even for very high Reynolds numbers and close to the surface at zu/ν10 [ McColl et al ., ]. However, this imbalance may not be as detrimental given the subunity exponent dependency of k T on ϵ .…”
Section: Discussion and Study Limitationmentioning
confidence: 99%