Stress gradient balance layers and scale hierarchies in wall-bounded turbulent flows

Fife, Paul C.; Wei, Tie; Klewicki, Joseph; McMurtry, Patrick

doi:10.1017/s0022112005003988

Cited by 55 publications

(94 citation statements)

References 30 publications

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“…Klewicki and co-authors [5][6][7] have proposed an alternative, four-layer structure based on relative magnitudes of terms in the momentum budget, as observed in direct numerical simulation (DNS) and experimental data. Another potentially useful route is to consider the role of turbulent statistical fluctuations in generating macroscopic phenomena such as the MVP.…”

Section: )mentioning

confidence: 99%

“…30) and is possibly the result of streaks within the buffer region that are known to not scale with distance from the wall. 31 The four-layer model proposed by Klewicki and co-authors [5][6][7] proposes a self-similar region governed by a hierarchy of length-scales linearly related to y + , spanning y + = 2.6 √ Re τ to y = 0.5R. For this DNS dataset, the self-similar region (and associated scaling with y + ) is predicted to begin at y + = 2.6 × √ 2003 = 116, in good agreement with the observed height at which k a+ begins varying with y + in the DNS dataset.…”

Section: B Assumption 2: Idealized Form Of F Vv +mentioning

confidence: 99%

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Mean-velocity profile of smooth channel flow explained by a cospectral budget model with wall-blockage

et al. 2016

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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 direct numerical simulation (DNS) dataset at moderate Reynolds number that includes all the requisite spectral and co-spectral information. Starting with several hypotheses for the cause of the “missing” curvature in the buffer layer, it is shown that the curvature deficit is mainly due to mismatches between (i) the modelled and DNS-observed pressure-strain terms in the cospectral budget and (ii) the DNS-observed Fvv and the idealized form used in previous models. By replacing the current parameterization for the pressure-strain term with an expansive version that directly accounts for wall-blocking effects, the modelled and DNS reported pressure-strain profiles match each other in the buffer and logarithmic layers. Forcing the new model with DNS-reported Fvv rather than the idealized form previously used reproduces the missing buffer layer curvature to high fidelity thereby confirming the “spectral link” between Fvv and the MVP across the full profile. A broad implication of this work is that much of the macroscopic properties of the flow (such as the MVP) may be derived from the energy distribution in turbulent eddies (i.e., Fvv) representing the microstate of the flow, provided the link between them accounts for wall-blocking.

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Section: )mentioning

confidence: 99%

Section: B Assumption 2: Idealized Form Of F Vv +mentioning

confidence: 99%

Mean-velocity profile of smooth channel flow explained by a cospectral budget model with wall-blockage

et al. 2016

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“…In doing so, it also, for T : mesoscaled turbulent thermal heat flux example, unambiguously reveals that viscous forces affect dynamics much farther into the flow from the wall than previously believed. Furthermore, this framework has provided the impetus for follow-on studies [12][13][14][15] that explore in detail many scaling considerations and implications for physical models. More broadly, these efforts clarify that the physical/mathematical interpretations of the unintegrated form of the mean momentum balance are directly associated with the mechanisms describing the time rate of change of mean momentum; while the first integral of this equation has a distinctly different interpretation, describing the mechanisms associated with the contributions to the flux of momentum.…”

Section: Introductionmentioning

confidence: 99%

Scaling heat transfer in fully developed turbulent channel flow

Wei

Fife

Klewicki

et al. 2005

International Journal of Heat and Mass Transfer

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“…[11,12]. The relative weight of T over the viscous term was quantified from both experimental and direct numerical simulations data and used to the explain dynamical properties of each layer.…”

Section: Introductionmentioning

confidence: 99%

Characteristics of sources and sinks of momentum in a turbulent boundary layer

Fiscaletti

Ganapathisubramani

2018

Phys. Rev. Fluids

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General rightsThis document is made available in accordance with publisher policies. Please cite only the published version using the reference above. Full terms of use are available: http://www.bristol.ac.uk/pure/about/ebr-terms In turbulent boundary layers, the wall-normal gradient of the Reynolds shear stress identifies momentum sources and sinks (T = ∂[−uv]/∂y). These motions can be physically interpreted in two ways: (1) as contributors to the turbulence term balancing the mean momentum equation, and (2) as regions of strong local interaction between velocity and vorticity fluctuations. In this paper, the space-time evolution of momentum sources and sinks is investigated in a turbulent boundary layer at the Reynolds number (Re τ ) = 2700, with time-resolved planar particle image velocimetry in a plane along the streamwise and wall-normal directions. Wave number-frequency power spectra of T fluctuations reveal that the wave velocities of momentum sources and sinks tend to match the local streamwise velocity in proximity to the wall. However, as the distance from the wall increases, the wave velocities of the T events are slightly lower than the local streamwise velocities of the flow, which is also confirmed from the tracking in time of the intense momentum sources and sinks. This evidences that momentum sources and sinks are preferentially located in low-momentum regions of the flow. The spectral content of the T fluctuations is maximum at the wall, but it decreases monotonically as the distance from the wall grows. The relative spectral contributions of the different wavelengths remains unaltered at varying wall-normal locations. From autocorrelation coefficient maps, the characteristic streamwise and wall-normal extents of the T motions are respectively 60 and 40 wall units, independent of the wall distance. Both statistics and instantaneous visualizations show that momentum sources and sinks have a preferential tendency to be organized in positive-negative pairs in the wall-normal direction.

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Stress gradient balance layers and scale hierarchies in wall-bounded turbulent flows

Cited by 55 publications

References 30 publications

Mean-velocity profile of smooth channel flow explained by a cospectral budget model with wall-blockage

Mean-velocity profile of smooth channel flow explained by a cospectral budget model with wall-blockage

Scaling heat transfer in fully developed turbulent channel flow

Characteristics of sources and sinks of momentum in a turbulent boundary layer

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