Parallel Dynamic Large Eddy Simulation of Turbulent Flow Around MIRA Model

For the large scale computation of turbulent flows around an arbitrarily shaped body, a parallel LES (large eddy simulation) code has been recently developed in which domain decomposition method is adopted. METIS and MPI (message passing interface) libraries are used for domain partitioning and data communication between processors, respectively. For unsteady computation of the incompressible Navier-Stokes equation, 4-step splitting finite element algorithm [1] is adopted and Smagorinsky or dynamic LES model can be chosen for the modeling of small eddies in turbulent flows. For the outlet (open) boundary condition, a Dirichlet boundary condition for the pressure is proposed. For the validation and performance-estimation of the parallel code, a three-dimensional laminar flow generated by natural convection inside a cube has been solved. We have confirmed that our code gives accurate results compared with previous studies. Regarding the speed-up of the code, the present parallel code with parallel block-Jacobi preconditioner is about 50 times faster than the corresponding serial code with 64 processors when approximately one million grid points are used. Most of the CPU time is consumed in solving elliptic type pressure equation. For the validation of LES models, turbulent channel flows are simulated at Re = 180, which is based on the channel half height and friction velocity using 51 × 71 × 71 grid system. It has been shown that our results agree well with the well-known results by Kim et al. [2] with less grid points than used by them in terms of time-averaged velocity field and velocity fluctuation. Lastly, we have solved the turbulent flow around MIRA (Motor Industry Research Association) model at Re = 1.6 × 10⁶ which is based on the model height and inlet free stream velocity. Both Smagorinsky and dynamic models are tested, comparing estimated drag coefficients and pressure distribution along the model surface with the existing experimental data [3]. With the help of the parallel code developed in this study, we are able to obtain a unsteady solution of the turbulent flow field around a vehicle discretized by approximately three million grid points within two weeks when 32 IBM-SP2-processors are used. The calculated drag coefficient agrees better with the experimental result [3] than those using two equation turbulence models [4].