Large Eddy Simulation of Active Flow Control Over SD7003 at Reynolds Number of 60,000

Author(s):  
Djavad Kamari ◽  
Mehran Tadjfar ◽  
Ali Tarokh

Abstract Large Eddy Simulation for active flow control (AFC) by employing synthetic and continuous blowing is done to investigate their effects on resizing separation. The flow around an SD7003 airfoil at Reynolds number of 60,000 and angles of attack of 13° is considered where a widespread separation occurs at post stall. In this work, the Dynamic Smagorinsky model is used as to calculate the turbulent viscosity.

2001 ◽  
Vol 17 (3) ◽  
pp. 121-129
Author(s):  
Mei-Jiau Huang

ABSTRACTDirect numerical simulations of 2D turbulent flows, freely decaying as well as forced, are performed to examine the mechanism of the enstrophy cascade and serve as a template of developing LES models. The stretching effect on the 2D vorticity gradients is emphasized on the analogy of the stretching effect on 3D vorticity. The enstrophy cascade rate, the Reynolds stresses and the associated eddy viscosity for 2D turbulence are correspondingly derived and investigated. Proposed herein is that the enstrophy cascade rate to be modeled in a large-eddy simulation can be and should be calculated using the only available large-eddy information, especially when the Reynolds number is not very large or when the flow is not stationary.The simulation results suggest all Kolmogorov's, Kraichnan's, and Saffman's similarity spectra. The Kolmogorov's spectrum appears in front of forced wave numbers and creates a subrange of a zero enstrophy cascade rate and a constant energy cascade rate. The Saffman's spectrum is the dissipation spectrum at large wave numbers. Kraichnan's spectrum shows up at intermediate wave numbers when the Reynolds number is sufficiently high. When the Smagorinsky model is employed for a large eddy simulation, its inability of capturing the significant reverse cascade phenomenon as observed in the DNS data becomes a fatal defect. Nonetheless, if only the mean cascade rate is concerned, the required Smagorinsky constant is evaluated using the DNS data and compared with the theoretical prediction of the Kraichnan's spectrum.


2014 ◽  
Vol 136 (5) ◽  
Author(s):  
Trushar B. Gohil ◽  
Arun K. Saha ◽  
K. Muralidhar

A large eddy simulation (LES) of an incompressible spatially developing circular jet at a Reynolds number of 10,000 is performed. The shear-improved Smagorinsky model (Lévêque et al., 2007, “A Shear-Improved Smagorinsky Model for the Large-Eddy Simulation of Wall-Bounded Turbulent Flows,” J. Fluid Mech., 570, pp. 491–502) is used for the resolution of the subgrid stress tensor within the filtered three-dimensional unsteady Navier–Stokes equations. Higher-order spatial and temporal discretization schemes are used for capturing the details of the turbulent flow field. With the help of instantaneous and time-averaged flow data, the spatial transition from the laminar state to the turbulent is analyzed. Flow structures are visualized using isosurfaces of the Q-criterion. Instantaneous flow patterns show single tearing and multiple pairing processes. Tracing individual vortex rings over a longer time period, a detailed understanding of the vortex interaction is revealed. The observed trends and the length of the potential core are in conformity with the findings of earlier experiments. The time-averaged axial velocity profile shows that the jet attains self-similarity and the computed profile matches well with the experimental results of Hussein et al. (1994, “Velocity Measurements in a High-Reynolds-Number, Momentum-Conserving, Axisymmetric, Turbulent Jet,” J. Fluid Mech., 258, pp. 31–75). The centerline decay of the velocity and entrainment rate are in agreement with published experiments. The Reynolds stress components u'u'¯, v'v'¯, and u'v'¯ and the third-order velocity moment are in good agreement with thr experimental results, thus confirming the validity of the present simulation.


2020 ◽  
Vol 86 ◽  
pp. 108698
Author(s):  
Qingxiang Shui ◽  
Cuie Duan ◽  
Xinyi Wu ◽  
Yunwei Zhang ◽  
Xilian Luo ◽  
...  

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