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ABSTRACT. A large eddy simulation (LES) of a turbulent channel flow is performed by using the third order low-storage Runge-Kutta method in time and second order finite difference formulation in space with staggered grid at a Reynolds number, Reτ = 590 based on the channel half width, δ and wall shear velocity, uτ . To reduce the calculation cost of LES, algebraic wall model (AWM) is applied to approximate the near-wall region. The computation is performed in a domain of 2πδ×2δ×πδ with 32×20×32 grid points. Standard Smagorinsky model is used for subgrid-scale (SGS) modeling. Essential turbulence statistics of the flow field are computed and compared with Direct Numerical Simulation (DNS) data and LES data using no wall model. Agreements as well as discrepancies are discussed. The flow structures in the computed flow field have also been discussed and compared with LES data using no wall model.

Direct numerical simulation (DNS) in two-dimensional homogeneous isotropic turbulence is performed by using the Spectral method at a Reynolds number Re = 1000 on a uniformly distributed 128 128 × grid points. The Reynolds number is low enough that the computational grid is capable of resolving all the possible turbulent scales. The statistical properties in the computed flow field show a good agreement with the qualitative behavior of decaying turbulence. The behavior of the flow structures in the computed flow field also follow the classical idea of the fluid flow in turbulence.

A large eddy simulation (LES) of a plane turbulent channel flow is performed at a Reynolds number Re? = 590 based on the channel half width, ? and wall shear velocity, u? by approximating the near wall region using differential equation wall model (DEWM). The simulation is performed in a computational domain of 2?? x 2? x ??. The computational domain is discretized by staggered grid system with 32 x 30 x 32 grid points. In this domain the governing equations of LES are discretized spatially by second order finite difference formulation, and for temporal discretization the third order low-storage Runge-Kutta method is used. Essential turbulence statistics of the computed flow field based on this LES approach are calculated and compared with the available Direct Numerical Simulation (DNS) and LES data where no wall model was used. Comparing the results throughout the calculation domain we have found that the LES results based on DEWM show closer agreement with the DNS data, especially at the near wall region. That is, the LES approach based on DEWM can capture the effects of near wall structures more accurately. Flow structures in the computed flow field in the 3D turbulent channel have also been discussed and compared with LES data using no wall model.