scholarly journals Large-eddy simulation of the flow and acoustic fields of a Reynolds number 105 subsonic jet with tripped exit boundary layers

2011 ◽  
Vol 23 (3) ◽  
pp. 035104 ◽  
Author(s):  
Christophe Bogey ◽  
Olivier Marsden ◽  
Christophe Bailly
Keyword(s):  
Reynolds Number ◽  
Large Eddy Simulation ◽  
Boundary Layers ◽  
Acoustic Fields ◽  
Eddy Simulation ◽  
Large Eddy ◽  
Exit Boundary ◽  
Subsonic Jet

Subgrid-scale modelling for the large-eddy simulation of high-Reynolds-number boundary layers

1997 ◽  
Vol 336 ◽  
pp. 151-182 ◽  
Author(s):  
BRANKO KOSOVIĆ
Keyword(s):  
Boundary Layer ◽  
Reynolds Number ◽  
Large Eddy Simulation ◽  
Boundary Layers ◽  
Nonlinear Model ◽  
High Reynolds Number ◽  
Subgrid Scale ◽  
Eddy Simulation ◽  
Large Eddy ◽  
High Reynolds

It has been recognized that the subgrid-scale (SGS) parameterization represents a critical component of a successful large-eddy simulation (LES). Commonly used linear SGS models produce erroneous mean velocity profiles in LES of high-Reynolds-number boundary layer flows. Although recently proposed approaches to solving this problem have resulted in significant improvements, questions about the true nature of the SGS problem in shear-driven high-Reynolds-number flows remain open.We argue that the SGS models must capture inertial transfer effects including backscatter of energy as well as its redistribution among the normal SGS stress components. These effects are the consequence of nonlinear interactions and anisotropy. In our modelling procedure we adopt a phenomenological approach whereby the SGS stresses are related to the resolved velocity gradients. We show that since the SGS stress tensor is not frame indifferent a more general nonlinear model can be applied to the SGS parameterization. We develop a nonlinear SGS model capable of reproducing the effects of SGS anisotropy characteristic for shear-driven boundary layers. The results obtained using the nonlinear model for the LES of a neutral shear-driven atmospheric boundary layer show a significant improvement in prediction of the non-dimensional shear and low-order statistics compared to the linear Smagorinsky-type models. These results also demonstrate a profound effect of the SGS model on the flow structures.

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