Abstract
In the present study, the main focus is to explore the Couette effect on turbulent secondary structures by simulating the turbulent Poiseuille, Couette-Poiseuille and Couette flows inside a square duct where the bulk Reynolds number is kept around 10000. Both the Smagorinsky model with Van Direst damping function and the dynamic Smagorinsky model employed here predict the mean and turbulence quantities well by comparisons with DNS data. The present numerical method was validated by computing the Poiseuille flow, which was then used as base to explore influences of the moving wall on Couette-Poiseuille flows. The turbulence generated secondary flow is modified by the presence of the top moving wall, where the symmetric vortex pattern vanishes. It is interesting to note that a linear relation exits between the angle and the parameter r = Ww=Wbulk, and change in slope occurs at r » 1:5. Near the moving wall due to the reduction of the streamwise velocity fluctuation at the moving wall, turbulence structure gradually moves towards a rod-like axi-symmetric turbulence as r increases. As the wall velocity increases further for r > 1:5, the rod like structure disappears, and turbulence reverts to the disk like structure. The near wall structures are first visualized by the instantaneous velocity field in one cross-plane of the square duct after the flow has achieved fully developed state. Along the top moving wall, the low mean shear rate suppresses the generation of these turbulent structures. Therefore, near the top corners the ejection events from the side walls are the dominant structures. The present numerical procedures are capable of simulating complex turbulent wall- bounded flows. It is demonstrated that the present results have shown the influence of top moving wall on the turbulent levels and anisotropic. Scientifically, results of this prediction have great reference value for researchers concerning turbulent duct flows or turbulence modeling. Finally, this work will allow the industry to benefit from the design and optimization.