Computational technologies for simulation of complex near-wall turbulent flows using unstructured meshes

2014 ◽  
Vol 6 (2) ◽  
pp. 162-171 ◽  
Author(s):  
A. P. Duben
Author(s):  
Michael Leschziner ◽  
Ning Li ◽  
Fabrizio Tessicini

This paper provides a discussion of several aspects of the construction of approaches that combine statistical (Reynolds-averaged Navier–Stokes, RANS) models with large eddy simulation (LES), with the objective of making LES an economically viable method for predicting complex, high Reynolds number turbulent flows. The first part provides a review of alternative approaches, highlighting their rationale and major elements. Next, two particular methods are introduced in greater detail: one based on coupling near-wall RANS models to the outer LES domain on a single contiguous mesh, and the other involving the application of the RANS and LES procedures on separate zones, the former confined to a thin near-wall layer. Examples for their performance are included for channel flow and, in the case of the zonal strategy, for three separated flows. Finally, a discussion of prospects is given, as viewed from the writer's perspective.


2012 ◽  
Vol 550-553 ◽  
pp. 2014-2018
Author(s):  
Xiao Lan Zhou ◽  
Cai Xi Liu ◽  
Yu Hong Dong

Electrochemical mass transfer in turbulent flows and binary electrolytes is investigated. The primary objective is to provide information about mass transfer in the near-wall region between a solid boundary and a turbulent fluid flow at different Schmidt numbers. Based on the computational fluid dynamics and electrochemistry theories, a model for turbulent electrodes channel flow is established. The turbulent mass transfer in electrolytic processes has been predicted by the direct numerical simulation method under limiting current and galvanostatic conditions, we investigate mean concentration and the structure of the concentration fluctuating filed for different Schmidt numbers from 0.1 to 100 .The effect of different concentration boundary conditions at the electrodes on the near-wall turbulence statistics is also discussed.


2010 ◽  
Vol 659 ◽  
pp. 405-419 ◽  
Author(s):  
K. YEO ◽  
B.-G. KIM ◽  
C. LEE

The behaviour of fluid-particle acceleration in near-wall turbulent flows is investigated in numerically simulated turbulent channel flows at low to moderate Reynolds numbers, Reτ = 180~600). The acceleration is decomposed into pressure-gradient (irrotational) and viscous contributions (solenoidal acceleration) and the statistics of each component are analysed. In near-wall turbulent flows, the probability density function of acceleration is strongly dependent on the distance from the wall. Unexpectedly, the intermittency of acceleration is strongest in the viscous sublayer, where the acceleration flatness factor of O(100) is observed. It is shown that the centripetal acceleration around coherent vortical structures is an important source of the acceleration intermittency. We found sheet-like structures of strong solenoidal accelerations near the wall, which are associated with the background shear modified by the interaction between a streamwise vortex and the wall. We found that the acceleration Kolmogorov constant is a linear function of y+ in the log layer. The Reynolds number dependence of the acceleration statistics is investigated.


2012 ◽  
Vol 710 ◽  
pp. 234-259 ◽  
Author(s):  
B.-Q. Deng ◽  
C.-X. Xu

AbstractNear-wall streamwise vortices are closely related to the generation of high skin friction in wall-bounded turbulent flows. A common feature of controlled, friction-reduced turbulent flows is weakened near-wall streamwise vortices. In the present study, the streak transient growth (STG) mechanism for generating near-wall streamwise vortices by Schoppa & Hussain (J. Fluid Mech., vol. 453, 2002, pp. 57–108) is employed, and the opposition control proposed by Choi, Moin & Kim (J. Fluid Mech., vol. 262, 1994, pp. 75–110) is imposed during the transient growth process of perturbations to determine how active control affects the generation of quasi-streamwise vortices. In the transient growth stage, when the detection plane is located near the wall (${ y}_{d}^{+ } = 15$), the control can suppress the production of streamwise vorticity by weakening the near-wall vertical velocity; when the detection plane moves away from the wall (${ y}_{d}^{+ } = 28$), the control has the opposite effect. In the vortex generation stage, the control cannot change the dominance of the stretching effect. Controls imposed at different stages reveal the importance of the STG stage in vortex generation. Strengthened out-of-phase control and lessened in-phase control are proposed as an extension of the original opposition-control scheme. Application in a fully developed turbulent channel flow shows that strengthened ${ y}_{d}^{+ } = 10$ control can yield an even higher drag reduction rate than the original ${ y}_{d}^{+ } = 15$ control. Moreover, lessened ${ y}_{d}^{+ } = 28$ control can also achieve drag reduction and turbulence suppression.


2001 ◽  
Vol 124 (1) ◽  
pp. 86-99 ◽  
Author(s):  
G. A. Gerolymos ◽  
J. Neubauer ◽  
V. C. Sharma ◽  
I. Vallet

In this paper an assessment of the improvement in the prediction of complex turbomachinery flows using a new near-wall Reynolds-stress model is attempted. The turbulence closure used is a near-wall low-turbulence-Reynolds-number Reynolds-stress model, that is independent of the distance-from-the-wall and of the normal-to-the-wall direction. The model takes into account the Coriolis redistribution effect on the Reynolds-stresses. The five mean flow equations and the seven turbulence model equations are solved using an implicit coupled OΔx3 upwind-biased solver. Results are compared with experimental data for three turbomachinery configurations: the NTUA high subsonic annular cascade, the NASA_37 rotor, and the RWTH 1 1/2 stage turbine. A detailed analysis of the flowfield is given. It is seen that the new model that takes into account the Reynolds-stress anisotropy substantially improves the agreement with experimental data, particularily for flows with large separation, while being only 30 percent more expensive than the k−ε model (thanks to an efficient implicit implementation). It is believed that further work on advanced turbulence models will substantially enhance the predictive capability of complex turbulent flows in turbomachinery.


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