scholarly journals The characteristics of coherent structures in the near-wall region of turburent channel flow changing with Reynolds number

1989 ◽  
Vol 33 ◽  
pp. 541-546
Author(s):  
Takanori SAGA ◽  
Hirofumi OHNARI ◽  
Katutosi WATANABE ◽  
Takashi SAITOU
Keyword(s):  
Reynolds Number ◽  
Channel Flow ◽  
Coherent Structures ◽  
Wall Region ◽  
Near Wall

scholarly journals Exact coherent states of attached eddies in channel flow

2019 ◽  
Vol 862 ◽  
pp. 1029-1059 ◽  
Author(s):  
Qiang Yang ◽  
Ashley P. Willis ◽  
Yongyun Hwang
Keyword(s):  
Reynolds Number ◽  
Channel Flow ◽  
Coherent Structures ◽  
Time Scale ◽  
Coherent States ◽  
Plane Channel ◽  
Reynolds Numbers ◽  
Wall Region ◽  
Self Similar ◽  
Near Wall

A new set of exact coherent states in the form of a travelling wave is reported in plane channel flow. They are continued over a range in $Re$ from approximately $2600$ up to $30\,000$, an order of magnitude higher than those discovered in the transitional regime. This particular type of exact coherent states is found to be gradually more localised in the near-wall region on increasing the Reynolds number. As larger spanwise sizes $L_{z}^{+}$ are considered, these exact coherent states appear via a saddle-node bifurcation with a spanwise size of $L_{z}^{+}\simeq 50$ and their phase speed is found to be $c^{+}\simeq 11$ at all the Reynolds numbers considered. Computation of the eigenspectra shows that the time scale of the exact coherent states is given by $h/U_{cl}$ in channel flow at all Reynolds numbers, and it becomes equivalent to the viscous inner time scale for the exact coherent states in the limit of $Re\rightarrow \infty$. The exact coherent states at several different spanwise sizes are further continued to a higher Reynolds number, $Re=55\,000$, using the eddy-viscosity approach (Hwang & Cossu, Phys. Rev. Lett., vol. 105, 2010, 044505). It is found that the continued exact coherent states at different sizes are self-similar at the given Reynolds number. These observations suggest that, on increasing Reynolds number, new sets of self-sustaining coherent structures are born in the near-wall region. Near this onset, these structures scale in inner units, forming the near-wall self-sustaining structures. With further increase of Reynolds number, the structures that emerged at lower Reynolds numbers subsequently evolve into the self-sustaining structures in the logarithmic region at different length scales, forming a hierarchy of self-similar coherent structures as hypothesised by Townsend (i.e. attached eddy hypothesis). Finally, the energetics of turbulent flow is discussed for a consistent extension of these dynamical systems notions to high Reynolds numbers.

scholarly journals Geometric study of Lagrangian and Eulerian structures in turbulent channel flow

2011 ◽  
Vol 674 ◽  
pp. 67-92 ◽  
Author(s):  
YUE YANG ◽  
D. I. PULLIN
Keyword(s):  
Reynolds Number ◽  
Channel Flow ◽  
Inclination Angle ◽  
Turbulent Channel Flow ◽  
Small Scale ◽  
Wall Region ◽  
Sweep Angle ◽  
Multi Scale ◽  
Geometric Study ◽  
Near Wall

We report the detailed multi-scale and multi-directional geometric study of both evolving Lagrangian and instantaneous Eulerian structures in turbulent channel flow at low and moderate Reynolds numbers. The Lagrangian structures (material surfaces) are obtained by tracking the Lagrangian scalar field, and Eulerian structures are extracted from the swirling strength field at a time instant. The multi-scale and multi-directional geometric analysis, based on the mirror-extended curvelet transform, is developed to quantify the geometry, including the averaged inclination and sweep angles, of both structures at up to eight scales ranging from the half-height δ of the channel to several viscous length scales δν. Here, the inclination angle is on the plane of the streamwise and wall-normal directions, and the sweep angle is on the plane of streamwise and spanwise directions. The results show that coherent quasi-streamwise structures in the near-wall region are composed of inclined objects with averaged inclination angle 35°–45°, averaged sweep angle 30°–40° and characteristic scale 20δν, and ‘curved legs’ with averaged inclination angle 20°–30°, averaged sweep angle 15°–30° and length scale 5δν–10δν. The temporal evolution of Lagrangian structures shows increasing inclination and sweep angles with time, which may correspond to the lifting process of near-wall quasi-streamwise vortices. The large-scale structures that appear to be composed of a number of individual small-scale objects are detected using cross-correlations between Eulerian structures with large and small scales. These packets are located at the near-wall region with the typical height 0.25δ and may extend over 10δ in the streamwise direction in moderate-Reynolds-number, long channel flows. In addition, the effects of the Reynolds number and comparisons between Lagrangian and Eulerian structures are discussed.

scholarly journals Large eddy simulation of turbulent channel flow using differential equation wall model

2018 ◽  
Vol 15 (2) ◽  
pp. 75-89
Author(s):  
Muhammad Saiful Islam Mallik ◽  
Md. Ashraf Uddin
Keyword(s):  
Differential Equation ◽  
Flow Field ◽  
Channel Flow ◽  
Turbulent Channel Flow ◽  
Wall Region ◽  
Computational Domain ◽  
Wall Model ◽  
Eddy Simulation ◽  
Large Eddy ◽  
Near Wall

A large eddy simulation (LES) of a plane turbulent channel flow is performed at a Reynolds number Re? = 590 based on the channel half width, ? and wall shear velocity, u? by approximating the near wall region using differential equation wall model (DEWM). The simulation is performed in a computational domain of 2?? x 2? x ??. The computational domain is discretized by staggered grid system with 32 x 30 x 32 grid points. In this domain the governing equations of LES are discretized spatially by second order finite difference formulation, and for temporal discretization the third order low-storage Runge-Kutta method is used. Essential turbulence statistics of the computed flow field based on this LES approach are calculated and compared with the available Direct Numerical Simulation (DNS) and LES data where no wall model was used. Comparing the results throughout the calculation domain we have found that the LES results based on DEWM show closer agreement with the DNS data, especially at the near wall region. That is, the LES approach based on DEWM can capture the effects of near wall structures more accurately. Flow structures in the computed flow field in the 3D turbulent channel have also been discussed and compared with LES data using no wall model.

Predictability Study of Viscoelastic Turbulent Channel Flow Using Deep Learning

2019 ◽  
Author(s):  
Atsushi Nagamachi ◽  
Takahiro Tsukahara
Keyword(s):  
Channel Flow ◽  
Viscoelastic Fluid ◽  
Coherent Structures ◽  
Turbulent Channel Flow ◽  
Wall Region ◽  
Nonlinear Relationship ◽  
Multi Layer Perceptron ◽  
Numerical Instability ◽  
Z Score ◽  
Score Normalization

Abstract We tested Artificial Neural Networks (ANNs) to predict a fully-developed turbulent channel flow of a viscoelastic fluid in preparation for elucidating flow phenomenon and solving the difficulty in DNS (Direct Numerical Simulation) due to numerical instability of the viscoelastic fluid. Two kinds of ANNs (multi-layer perceptron (MLP) and U-Net) were trained using DNS data to predict conformation stress from given instantaneous field. The MLP showed accurate predictions and predictions got better with z-score normalization. ANN predicted accurately in near-wall region having coherent structures. In addition, we demonstrated that ANN get the nonlinear relationship between velocity gradient and viscoelastic stress partially.

Effects of Spatial Resolution and Box Size on Numerical Solutions of Turbulent Flows

2005 ◽  
Author(s):  
Dongmei Zhou ◽  
Kenneth S. Ball
Keyword(s):  
Drag Reduction ◽  
Channel Flow ◽  
Spatial Resolution ◽  
Numerical Solutions ◽  
Velocity Profiles ◽  
Wall Region ◽  
Computational Domain ◽  
Mean Velocity ◽  
Significant Difference ◽  
Near Wall

This paper has two objectives, (1) to examine the effects of spatial resolution, (2) to examine the effects of computational box size, upon turbulence statistics and the amount of drag reduction with and without the control scheme of wall oscillation. Direct numerical simulation (DNS) of the fully developed turbulent channel flow was performed at Reynolds number of 200 based on the wall-shear velocity and the channel half-width by using spectral methods. For the first objective, four different grids were applied to the same computational domain and the biggest impact was observed on the logarithmic law of mean velocity profiles and on the amount of drag reduction with 28.3% for the coarsest mesh and 35.4% for the finest mesh. Other turbulence features such as RMS velocity fluctuations, RMS vorticity fluctuations, and bursting events were either overpredicted or underpredicted through coarse grids. For the second objective, two different minimal channels and one natural full channel were studied and 3% drag reduction difference was observed between the smallest minimal channel of 39.1% and the natural full channel of 36.2%. In the near-wall region, however, the minimal channel flow did not exhibit significant difference in the mean velocity profiles and other lower-order statistics. Finally, from this systematical study, it showed that the accuracy of DNS depends more on the spanwise resolution, and it also confirmed that a minimal channel model is able to catch key structures of turbulence in the near-wall region but is much less expensive.

Assessing the Effects of Near Wall Corrections of the Force Acting on Particles in Gas-Solid Channel Flows

2005 ◽  
Author(s):  
Boris Arcen ◽  
Anne Tanie`re ◽  
Benoiˆt Oesterle´
Keyword(s):  
Channel Flow ◽  
Lift Force ◽  
Particle Concentration ◽  
Turbulent Channel Flow ◽  
Shear Velocity ◽  
Solid Particles ◽  
Wall Region ◽  
Wall Effects ◽  
Strong Shear ◽  
Near Wall

The importance of using the lift force and wall-corrections of the drag coefficient for modeling the motion of solid particles in a fully-developed channel flow is investigated by means of direct numerical simulation (DNS). The turbulent channel flow is computed at a Reynolds number based on the wall-shear velocity and channel half-width of 185. Contrary to most of the numerical simulations, we consider in the present study a lift force formulation that accounts for the weak and strong shear as well as for the wall effects (hereinafter referred to as optimum lift force), and the wall-corrections of the drag force. The DNS results show that the optimum lift force and the wall-corrections of the drag together have little influence on most of the statistics (particle concentration, mean velocities, and mean relative and drift velocities), even in the near wall region.

Merging Near-Wall RANS Models With LES for Separating and Reattaching Flows

2006 ◽  
Author(s):  
Suad Jakirlic´ ◽  
Bjo¨rn Kniesner ◽  
Sanjin Sˇaric´ ◽  
Kemal Hanjalic´
Keyword(s):  
Reynolds Number ◽  
Equation Model ◽  
Navier Stokes ◽  
Model Parameters ◽  
Wall Region ◽  
Detached Eddy Simulation ◽  
Rans Model ◽  
Eddy Simulation ◽  
Moderate Reynolds Number ◽  
Near Wall

A method of coupling a low-Reynolds-number k–ε RANS (Reynolds-Averaged Navier-Stokes) model with Large-Eddy Simulation (LES) in a two-layer Hybrid LES/RANS (HLR) scheme is proposed in the present work. The RANS model covers the near-wall region and the LES model the remainder of the flow domain. Two different subgrid-scale (SGS) models in LES were considered, the Smagorinsky model and the one-equation model for the residual kinetic energy (Yoshizawa and Horiuti, 1985), combined with two versions of the RANS ε equation, one governing the “isotropic” (ε˜; Chien, 1982) and the other the “homogeneous” dissipation rate (εh; Jakirlic and Hanjalic, 2002). Both fixed and self-adjusting interface locations were considered. The exchange of the variables across the interface was adjusted by smoothing the turbulence viscosity either by adjusting the RANS model parameters, such as Cμ (Temmerman et al., 2005), or by applying an additional forcing at the interface using a method of digital-filter-based generation of inflow data for spatially developing DNS and LES due to Klein et al. (2003). The feasibility of the method was illustrated against the available DNS, fine- and coarse grid LES, DES (Detached Eddy Simulation) and experiments in turbulent flow over a backward-facing step at a low (Yoshioka et al., 2001) and a high Re number (Vogel and Eaton, 1985), periodic flow over a series of 2-D hills (Fro¨hlich et al., 2005) and in a high-Re flow over a 2-D, wall-mounted hump (Greenblat et al, 2004). Prior to these computations, the method was validated in a fully-developed channel flow at a moderate Reynolds number Rem ≈ 24000 (Abe et al., 2004).

scholarly journals Asymmetrical Velocity Distribution in the Drag-Reducing Channel Flow of Surfactant Solution Caused by an Injected Ultrathin Water Layer

Symmetry ◽  
2020 ◽  
Vol 12 (5) ◽  
pp. 846
Author(s):  
Zaiguo Fu ◽  
Xiaotian Liang ◽  
Kang Zhang
Keyword(s):  
Velocity Distribution ◽  
Channel Flow ◽  
Reynolds Shear Stress ◽  
Surfactant Solution ◽  
Water Layer ◽  
Statistical Characteristics ◽  
Wall Region ◽  
Experimental Conditions ◽  
Mean Velocity ◽  
Near Wall

Although the turbulent intensity is suppressed in the drag-reducing channel flow by viscoelastic additives, the mean velocity distribution in the channel flow is symmetrical and tends to be similar to the laminar flow. In the study of near-wall modulation of the drag-reducing flow with an injected ultrathin water layer, an asymmetrical mean velocity distribution was found. To further investigate this phenomenon and the underlying cause, an experiment was carried out with the water injected from a porous channel wall at a small velocity (~10−4 m/s) into the drag-reducing flow of surfactant solution. The instantaneous concentration and flow fields were measured by using planar laser-induced fluorescence (PLIF) and particle imaging velocimetry (PIV) techniques, respectively. Moreover, analyses on turbulent statistical characteristics and spatial distribution of viscoelastic structures were carried out on the basis of comparison among various flow cases. The results showed that the injected ultrathin water layer under present experimental conditions affected the anisotropy of the drag-reducing flow. The characteristics, such as turbulence intensity, showed the zonal feature in the wall-normal direction. The Reynolds shear stress was enhanced in the near-wall region, and the viscoelastic structure was modified severely due to the redistributed stress. These results may provide experimental supports for the near-wall modulation of turbulence and the exploration of the drag-reducing mechanism by viscoelastic additives.

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