A Large-Eddy Simulation of the Near Wake of a Circular Cylinder

1998 ◽  
Vol 120 (2) ◽  
pp. 243-252 ◽  
Author(s):  
S. A. Jordan ◽  
S. A. Ragab
Keyword(s):  
Circular Cylinder ◽  
Large Eddy Simulation ◽  
Dynamic Model ◽  
Curvilinear Coordinates ◽  
Reynolds Stresses ◽  
Near Wake ◽  
Mean Velocity ◽  
Eddy Simulation ◽  
Large Eddy ◽  
Global And Local

The formation and the downstream transport of the Strouhal vortices in the near wake of a circular cylinder are investigated using the large-eddy simulation (LES) method. The governing equations are formulated in curvilinear coordinates to accommodate a nonorthogonal grid with formal development of a dynamic model to account for the subgrid turbulent scales. Results were produced with and without use of the model. The focus of the investigation is at a subcritical Reynolds number of 5600. Using the dynamic model, the LES results compared best to the published experimental data in terms of both the global and local wake characteristics such as the drag and base pressure coefficients, shedding and detection frequencies, peak vorticity, and the downstream mean velocity-defect and Reynolds stresses. The results further showed streamwise filaments that connect subsequent Strouhal vortices. Qualitatively, the time-averaged Reynolds stresses of the formation region revealed similar symmetric characteristics over the range 525 ≤ Re ≤ 140,000.

Large-Eddy Simulation of Physiological Pulsatile Flow Based on a Dynamic Nonlinear Subgrid-Scale Stress Model

2011 ◽  
Author(s):  
Md. Mamun Molla ◽  
Bing-Chen Wang ◽  
David C. S. Kuhn
Keyword(s):  
Kinetic Energy ◽  
Large Eddy Simulation ◽  
Pulsatile Flow ◽  
Dynamic Models ◽  
Transitional Flow ◽  
Subgrid Scale ◽  
Reynolds Stresses ◽  
Mean Velocity ◽  
Eddy Simulation ◽  
Large Eddy

Pulsatile laminar-turbulent transitional flow in a three-dimensional (3D) constricted channel represents a challenging topic and has many important applications in bio-medical engineering. In this research, we numerically investigate the physics of a physiological pulsatile flow confined within a 3D channel with an idealized stenosis formed eccentrically on the top wall using the method of large-eddy simulation (LES). The advanced dynamic nonlinear subgrid-scale stress (SGS) model of Wang and Bergstrom [1] was implemented in the current LES approach to properly resolve the unrealistic SGS dissipation effects and numerical instabilities that are intrinsic to the Smagorinsky type dynamic models (DM). The Reynolds numbers tested in the simulation are 1700 and 2000, which are characteristic of human blood flows in large arteries. An in-house 3-D LES code has been modified to conduct our unsteady numerical simulations, and the results obtained have been validated using two different grid arrangements and the experimental results of Ahmed and Giddens [2]. The numerical results have been examined in terms of the resolved mean velocity, turbulence kinetic energy, viscous wall shear stress, resolved and subgrid-scale Reynolds stresses, as well as the local kinetic energy fluxes between the filtered and subgrid scales.

Large eddy simulation study of turbulent flow around smooth and rough domes

2013 ◽  
Vol 227 (12) ◽  
pp. 2686-2700 ◽  
Author(s):  
N Kharoua ◽  
L Khezzar
Keyword(s):  
Large Eddy Simulation ◽  
Turbulent Flow ◽  
Flow Behavior ◽  
Pressure Coefficient ◽  
Horseshoe Vortex ◽  
Scale Model ◽  
Stream Velocity ◽  
Mean Velocity ◽  
Eddy Simulation ◽  
Large Eddy

Large eddy simulation of turbulent flow around smooth and rough hemispherical domes was conducted. The roughness of the rough dome was generated by a special approach using quadrilateral solid blocks placed alternately on the dome surface. It was shown that this approach is capable of generating the roughness effect with a relative success. The subgrid-scale model based on the transport of the subgrid turbulent kinetic energy was used to account for the small scales effect not resolved by large eddy simulation. The turbulent flow was simulated at a subcritical Reynolds number based on the approach free stream velocity, air properties, and dome diameter of 1.4 × 105. Profiles of mean pressure coefficient, mean velocity, and its root mean square were predicted with good accuracy. The comparison between the two domes showed different flow behavior around them. A flattened horseshoe vortex was observed to develop around the rough dome at larger distance compared with the smooth dome. The separation phenomenon occurs before the apex of the rough dome while for the smooth dome it is shifted forward. The turbulence-affected region in the wake was larger for the rough dome.

Kinetic-energy-flux-constrained model using an artificial neural network for large-eddy simulation of compressible wall-bounded turbulence

2021 ◽  
Vol 932 ◽  
Author(s):  
Changping Yu ◽  
Zelong Yuan ◽  
Han Qi ◽  
Jianchun Wang ◽  
Xinliang Li ◽  
...  
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Kinetic Energy ◽  
Large Eddy Simulation ◽  
Energy Flux ◽  
Mean Velocity ◽  
New Model ◽  
Eddy Simulation ◽  
Large Eddy ◽  
Wall Bounded Turbulence

Kinetic energy flux (KEF) is an important physical quantity that characterizes cascades of kinetic energy in turbulent flows. In large-eddy simulation (LES), it is crucial for the subgrid-scale (SGS) model to accurately predict the KEF in turbulence. In this paper, we propose a new eddy-viscosity SGS model constrained by the properly modelled KEF for LES of compressible wall-bounded turbulence. The new methodology has the advantages of both accurate prediction of the KEF and strong numerical stability in LES. We can obtain an approximate KEF by the tensor-diffusivity model, which has a high correlation with the real value. Then, using the artificial neural network method, the local ratios between the real KEF and the approximate KEF are accurately modelled. Consequently, the SGS model can be improved by the product of that ratio and the approximate KEF. In LES of compressible turbulent channel flow, the new model can accurately predict mean velocity profile, turbulence intensities, Reynolds stress, temperature–velocity correlation, etc. Additionally, for the case of a compressible flat-plate boundary layer, the new model can accurately predict some key quantities, including the onset of transitions and transition peaks, the skin-friction coefficient, the mean velocity in the turbulence region, etc., and it can also predict the energy backscatters in turbulence. Furthermore, the proposed model also shows more advantages for coarser grids.

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