Roughness effects on the Reynolds stress budgets in near-wall turbulence

2014 ◽  
Vol 760 ◽  
Author(s):  
Junlin Yuan ◽  
Ugo Piomelli
Keyword(s):  
Kinetic Energy ◽  
Outer Layer ◽  
Reynolds Shear Stress ◽  
Wall Turbulence ◽  
Roughness Sublayer ◽  
Spatial Inhomogeneity ◽  
Mean Flow ◽  
Production Term ◽  
Turbulent Fluctuations ◽  
Wake Production

AbstractThe physics of the roughness sublayer are studied by direct numerical simulations (DNS) of an open-channel flow with sandgrain roughness. A double-averaging (DA) approach is used to separate the spatial variations of the time-averaged quantities and the turbulent fluctuations. The spatial inhomogeneity of velocity and Reynolds stresses results in an additional production term for the turbulent kinetic energy (TKE) – the ‘wake production’; it is the excess wake kinetic energy (WKE), generated from the work of mean flow against the form drag, that is not directly dissipated into heat, but instead converted into turbulence. The wake production promotes wall-normal turbulent fluctuations and increases the pressure work, which ultimately leads to more homogeneous turbulence in the roughness sublayer, and to the increase of Reynolds shear stress and the drag on the rough wall. In the fully rough regime, roughness directly affects the generation of the wall-normal fluctuations, while in the transitionally rough regime, the region affected by roughness is separated from the region of intense generation of these fluctuations. The budget of the WKE and the connection between the wake and the turbulence suggest strong interactions between the roughness sublayer and the outer layer that are insensitive to the variation of the outer-layer conditions. Furthermore, the present results may have implications for the relationship between the roughness geometry and the flow dynamics in the region directly affected by roughness.

scholarly journals On the Evaluation of Seasonal Variability of the Ocean Kinetic Energy

2017 ◽  
Vol 47 (7) ◽  
pp. 1675-1683 ◽  
Author(s):  
Dujuan Kang ◽  
Enrique N. Curchitser
Keyword(s):  
Kinetic Energy ◽  
Seasonal Variability ◽  
Moving Average ◽  
Spatial Inhomogeneity ◽  
Mean Flow ◽  
Annual Cycles ◽  
Residual Term ◽  
The Mean ◽  
Mean Differences ◽  
Average Filter

AbstractThe seasonal cycles of the mean kinetic energy (MKE) and eddy kinetic energy (EKE) are compared in an idealized flow as well as in a realistic simulation of the Gulf Stream (GS) region based on three commonly used definitions: orthogonal, nonorthogonal, and moving-average filtered decompositions of the kinetic energy (KE). It is shown that only the orthogonal KE decomposition can define the physically consistent MKE and EKE that precisely represents the KEs of the mean flow and eddies, respectively. The nonorthogonal KE decomposition gives rise to a residual term that contributes to the seasonal variability of the eddies, and therefore the obtained EKE is not precisely defined. The residual term is shown to exhibit more significant seasonal variability than EKE in both idealized and realistic GS flows. Neglecting its influence leads to an inaccurate evaluation of the seasonal variability of both the eddies and the total flow. The decomposition using a moving-average filter also results in a nonnegligible residual term in both idealized and realistic GS flows. This type of definition does not ensure conservation of the total KE, even if taking into account the residual term. Moreover, it is shown that the annual cycles of the three types of EKEs or MKEs have different phases and amplitudes. The local differences of the EKE cycles are very prominent in the GS off-coast domain; however, because of the spatial inhomogeneity, the area-mean differences may not be significant.

The response of sheared turbulence to additional distortion

1980 ◽  
Vol 98 (1) ◽  
pp. 171-191 ◽  
Author(s):  
A. A. Townsend
Keyword(s):  
Shear Stress ◽  
Energy Transfer ◽  
Water Waves ◽  
Reynolds Shear Stress ◽  
Equations Of Motion ◽  
Mixing Layer ◽  
Wall Turbulence ◽  
Mean Flow ◽  
History Of ◽  
Stress Ratios

In unidirectional flows, the ratios of Reynolds shear stress to total intensity (except near positions of zero stress) remain remarkably constant from one flow to another, but curvature or strong divergence of the mean flow causes very considerable changes in the stress ratios. A scheme for calculating the changes is described, based on the rapid-distortion approximation of the equations of motion. The results depend to some extent on the effective history of distortion of the turbulence and on the magnitude of an eddy viscosity that models the effect of nonlinear transfer of energy to smaller eddies of the dissipation sequence, but the correspondence with measured values in a distorted wake and in a curved mixing layer is fairly good. In particular, the curious behaviour of stress ratios in the curved mixing-layer can be reproduced qualitatively without any difficulty. Small perturbations of wall turbulence provide a simple application, and earlier calculations of the energy transfer between wind and water waves have been repeated including the changes in the stress ratios predicted by the scheme. In the latter case, very large changes in the distributions of pressure and shear stress are found, and the rates of energy transfer are much larger and in better agreement with observations.

Modeling of a One-Equation LES for Plant Canopy Flows

2011 ◽  
Author(s):  
Hisashi Hiraoka
Keyword(s):  
Kinetic Energy ◽  
Energy Equation ◽  
Navier Stokes ◽  
Plant Canopy ◽  
Production Term ◽  
Eddy Simulation ◽  
Dissipation Term ◽  
Wake Production ◽  
Canopy Flows ◽  
Basic Equations

A one-equation-type subgrid-scale (SGS) model was proposed in order to enable the large eddy simulation (LES) of plant canopy flows. The SGS kinetic energy equation was derived from the equations of continuity and Navier-Stokes. This equation was closed by modeling the unknown terms according to the physical meaning of each term in the equation. The wake production term in the SGS kinetic equation could be derived analytically. However, the wake dissipation term did not appear when the SGS kinetic energy equation was derived from the basic equations.

scholarly journals Near-field flow structure of a confined wall jet on flat and concave rough walls

2008 ◽  
Vol 606 ◽  
pp. 27-49 ◽  
Author(s):  
I. ALBAYRAK ◽  
E. J. HOPFINGER ◽  
U. LEMMIN
Keyword(s):  
Shear Stress ◽  
Shear Layer ◽  
Outer Layer ◽  
Reynolds Shear Stress ◽  
Near Field ◽  
Wall Jet ◽  
Reynolds Stresses ◽  
Mean Flow ◽  
Free Jet ◽  
The Mean

Experimental results are presented of the mean flow and turbulence characteristics in the near field of a plane wall jet issuing from a nozzle onto flat and concave walls consisting of fixed sand beds. This is a flow configuration of interest for sediment erosion, also referred to as scouring. The measurements were made with an acoustic profiler that gives access to the three components of the instantaneous velocities. For the flat-wall flow, it is shown that the outer-layer spatial growth rate and the maxima of the Reynolds stresses approach the values accepted for the far field of a wall jet at a downstream distance x/b0 ≈ 8. These maxima are only about half the values of a plane free jet. This reduction in Reynolds stresses is also observed in the shear-layer region, x/b0 < 6, where the Reynolds shear stress is about half the value of a free shear layer. At distances x/b0 > 11, the maximum Reynolds shear stress approaches the value of a plane free jet. This change in Reynolds stresses is related to the mean vertical velocity that is negative for x/b0 < 8 and positive further downstream. The evolution of the inner region of the wall jet is found to be in good agreement with a previous model that explicitly includes the roughness length.On the concave wall, the mean flow and the Reynolds stresses are drastically changed by the adverse pressure gradient and especially by the development of Görtler vortices. On the downslope side of the scour hole, the flow is nearly separating with the wall shear stress tending to zero, whereas on the upslope side, the wall-friction coefficient is increased by a factor of about two by Görtler vortices. These vortices extend well into the outer layer and, just above the wall, cause a substantial increase in Reynolds shear stress.

scholarly journals Spatial modulations of kinetic energy in the roughness sublayer

2018 ◽  
Vol 850 ◽  
pp. 584-610 ◽  
Author(s):  
Jérémy Basley ◽  
Laurent Perret ◽  
Romain Mathis
Keyword(s):  
Kinetic Energy ◽  
Outer Layer ◽  
Large Scale ◽  
Stereoscopic Particle Image Velocimetry ◽  
Spatial Modulation ◽  
Roughness Sublayer ◽  
Small Scale ◽  
Smooth Wall ◽  
Wall Bounded Flows ◽  
Scale Turbulence

High-Reynolds-number experiments are conducted in the roughness sublayer of a turbulent boundary layer developing over a cubical canopy. Stereoscopic particle image velocimetry is performed in a wall-parallel plane to evidence a high degree of spatial modulation of the small-scale turbulence around the footprint of large-scale motions, despite the suppression of the inner layer by the high roughness elements. Both Fourier and wavelets analyses show that the near-wall cycle observed in smooth-wall-bounded flows is severely disrupted by the canopy, whose wake in the roughness sublayer generates a new range of scales, closer to that of the outer-layer large-scale motions. This restricts significantly scale separation, hence a diagnostic method is developed to divide carefully and rationally the fluctuating velocity fields into large- and small-scale components. Our analysis across all turbulent kinetic energy terms sheds light on the spatial imprint of the modulation mechanism, revealing a very different signature on each velocity component. The roughness sublayer shows a preferential arrangement of the modulated scales similar to what is observed in the outer layer of smooth-wall-bounded flows – small-scale turbulence is enhanced near the front of high momentum regions and damped at the front of low momentum regions. More importantly, accessing spanwise correlations reveals that modulation intensifies the most along the flanks of the large-scale motions.

Secondary flow in weakly rotating turbulent plane Couette flow

1996 ◽  
Vol 317 ◽  
pp. 195-214 ◽  
Author(s):  
Knut H. Bech ◽  
Helge I. Andersson
Keyword(s):  
Kinetic Energy ◽  
Secondary Flow ◽  
Couette Flow ◽  
Three Dimensional ◽  
Wall Turbulence ◽  
Plane Couette Flow ◽  
Mean Flow ◽  
Comparable Amount ◽  
Flow Vorticity ◽  
Turbulent Plane

As in the laminar case, the turbulent plane Couette flow is unstable (stable) with respect to roll cell instabilities when the weak background angular velocity Ωk is antiparallel (parallel) to the spanwise mean flow vorticity (-dU/dy)k. The critical value of the rotation number Ro, based on 2Ω and dU/dy of the corresponding laminar flow, was estimated as 0.0002 at a low Reynolds number with fully developed turbulence. Direct numerical simulations were performed for Ro = ±0.01 and compared with earlier results for non-rotating Couette flow. At the low rotation rates considered, both senses of rotation damped the turbulence and the number of near-wall turbulence-generating events was reduced. The destabilized flow was more energetic, but less three-dimensional, than the non-rotating flow. In the destabilized case, the two-dimensional roll cells extracted a comparable amount of kinetic energy from the mean flow as did the turbulence, thereby decreasing the turbulent kinetic energy. The turbulence anisotropy was practically unaffected by weak spanwise rotation, while the secondary flow was highly anisotropic due to its inability to contract and expand in the streamwise direction.

Non-equilibrium scaling laws in axisymmetric turbulent wakes

2015 ◽  
Vol 781 ◽  
pp. 166-195 ◽  
Author(s):  
T. Dairay ◽  
M. Obligado ◽  
J. C. Vassilicos
Keyword(s):  
Kinetic Energy ◽  
Turbulent Kinetic Energy ◽  
Scaling Laws ◽  
Reynolds Shear Stress ◽  
Mean Flow ◽  
Turbulent Dissipation ◽  
Turbulent Wakes ◽  
The Mean ◽  
Energy Equations ◽  
Non Equilibrium

We present a combined direct numerical simulation and hot-wire anemometry study of an axisymmetric turbulent wake. The data lead to a revised theory of axisymmetric turbulent wakes which relies on the mean streamwise momentum and turbulent kinetic energy equations, self-similarity of the mean flow, turbulent kinetic energy, Reynolds shear stress and turbulent dissipation profiles, non-equilibrium dissipation scalings and an assumption of constant anisotropy. This theory is supported by the present data up to a distance of 100 times the wake generator’s size, which is as far as these data extend.

Near-wall turbulence statistics and flow structures over three-dimensional roughness in a turbulent channel flow

2011 ◽  
Vol 667 ◽  
pp. 1-37 ◽  
Author(s):  
JIARONG HONG ◽  
JOSEPH KATZ ◽  
MICHAEL P. SCHULTZ
Keyword(s):  
Channel Flow ◽  
Outer Layer ◽  
Large Scale ◽  
Wall Turbulence ◽  
Small Scale ◽  
Reynolds Stresses ◽  
Mean Flow ◽  
Dissipation Rates ◽  
Near Wall Turbulence ◽  
Near Wall

Utilizing an optically index-matched facility and high-resolution particle image velocimetry measurements, this paper examines flow structure and turbulence in a rough-wall channel flow for Reτ in the 3520–5360 range. The scales of pyramidal roughness elements satisfy the ‘well-characterized’ flow conditions, with h/k ≈ 50 and k+ = 60 ~ 100, where h is half height of the channel and k is the roughness height. The near-wall turbulence measurements are sensitive to spatial resolution, and vary with Reynolds number. Spatial variations in the mean flow, Reynolds stresses, as well as the turbulent kinetic energy (TKE) production and dissipation rates are confined to y < 2k. All the Reynolds stress components have local maxima at slightly higher elevations, but the streamwise-normal component increases rapidly at y < k, peaking at the top of the pyramids. The TKE production and dissipation rates along with turbulence transport also peak near the wall. The spatial energy and shear spectra show an increasing contribution of large-scale motions and a diminishing role of small motions with increasing distance from the wall. As the spectra steepen at low wavenumbers, they flatten and develop bumps in wavenumbers corresponding to k − 3k, which fall in the dissipation range. Instantaneous realizations show that roughness-scale eddies are generated near the wall, and lifted up rapidly by large-scale structures that populate the outer layer. A linear stochastic estimation-based analysis shows that the latter share common features with hairpin packets. This process floods the outer layer with roughness-scale eddies, in addition to those generated by the energy-cascading process. Consequently, although the imprints of roughness diminish in the outer-layer Reynolds stresses, consistent with the wall similarity hypothesis, the small-scale turbulence contains a clear roughness signature across the entire channel.

Note on Turbulent Kinetic Energy Production for Reynolds-Averaged Navier–Stokes Models

2016 ◽  
Vol 138 (11) ◽  
Author(s):  
Solkeun Jee ◽  
Gorazd Medic ◽  
Georgi Kalitzin
Keyword(s):  
Kinetic Energy ◽  
Strain Rate ◽  
Turbulent Kinetic Energy ◽  
Energy Equation ◽  
Boussinesq Approximation ◽  
Navier Stokes ◽  
Mean Flow ◽  
Production Term ◽  
The Mean ◽  
Reynolds Averaged Navier Stokes

Linear eddy-viscosity Reynolds-Averaged Navier–Stokes (RANS) turbulence models are based on the Boussinesq approximation that asserts the Reynolds stresses to be linearly dependent on the mean strain rate. Using the Boussinesq approximation for the Reynolds stress yields a production term in the turbulent kinetic energy equation that is proportional to the square of the magnitude of the strain rate tensor. For some flows, this relation to the strain causes overproduction of turbulence. Widely used ad hoc modifications of the production term using vorticity lead to an inconsistent energy balance in the mean flow kinetic energy equation, violating the energy conservation. In this note, how to obtain a consistent RANS framework for a given production term modification is shown.

scholarly journals Statistical evidence of anasymptotic geometric structure to the momentum transporting motions in turbulent boundary layers

2017 ◽  
Vol 375 (2089) ◽  
pp. 20160084 ◽  
Author(s):  
Caleb Morrill-Winter ◽  
Jimmy Philip ◽  
Joseph Klewicki
Keyword(s):  
Boundary Layers ◽  
Reynolds Shear Stress ◽  
Turbulent Boundary Layers ◽  
Wall Turbulence ◽  
Sensor Data ◽  
Joint Analysis ◽  
Large Reynolds Number ◽  
Mean Flow ◽  
Length Scales ◽  
The Mean

The turbulence contribution to the mean flow is reflected by the motions producing the Reynolds shear stress (〈− uv 〉) and its gradient. Recent analyses of the mean dynamical equation, along with data, evidence that these motions asymptotically exhibit self-similar geometric properties. This study discerns additional properties associated with the uv signal, with an emphasis on the magnitudes and length scales of its negative contributions. The signals analysed derive from high-resolution multi-wire hot-wire sensor data acquired in flat-plate turbulent boundary layers. Space-filling properties of the present signals are shown to reinforce previous observations, while the skewness of uv suggests a connection between the size and magnitude of the negative excursions on the inertial domain. Here, the size and length scales of the negative uv motions are shown to increase with distance from the wall, whereas their occurrences decrease. A joint analysis of the signal magnitudes and their corresponding lengths reveals that the length scales that contribute most to 〈− uv 〉 are distinctly larger than the average geometric size of the negative uv motions. Co-spectra of the streamwise and wall-normal velocities, however, are shown to exhibit invariance across the inertial region when their wavelengths are normalized by the width distribution, W ( y ), of the scaling layer hierarchy, which renders the mean momentum equation invariant on the inertial domain. This article is part of the themed issue ‘Toward the development of high-fidelity models of wall turbulence at large Reynolds number’.

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