Large Eddy Simulation of Turbulent Flows Using the CFD Code GASFLOW - MPI

نویسندگان

  • Han Zhang
  • Jianjun Xiao
  • Thomas Jordan
چکیده

GASFLOW-MPI is a scalable CFD software solution used to predict fluid dynamics, conjugate heat and mass transfer, chemical kinetics, aerosol transportation and other related phenomena. The generalized 3-D transient, compressible Navier-Stokes equations for multispecies are solved. It has been widely used to analyze safety problems in nuclear engineering. Turbulence models based on the ReynoldsAveraged Navier-Stokes (RANS) equations are implemented in the serial version of the 3-D CFD code GASFLOW. The computing power of the advanced parallel version of GASFLOW-MPI code has been greatly improved by using the message passing interface (MPI) and domain decomposition. In order to capture more details of turbulence and flow features in applications of scientific research and engineering problems, the large eddy simulation (LES) turbulent model is implemented in the advanced CFD parallel version GASFLOW-MPI. The standard Smagorinsky subgrid scale (SGS) model is utilized in the LES turbulence model. And the turbulent inflow boundary based on white noise is developed for LES to consider the turbulent intensity at the inlet. The parallelization technique based on PETSc library is described and the speed up ratio is analyzed. The preliminary validation of LES is carried out for a jet flow at high Re=10 and a backward-facing step flow at medium Re = 5100. The numerical results have been compared with the experimental data in literatures. Both time-averaged velocity profile and turbulent intensity are analyzed and agree well with the experimental data. Furthermore, the frequency spectrum is presented and a −5/3 energy decay is observed for a wide range of frequencies, satisfying the turbulent energy spectrum theory. Additional SGS models will be developed in GASFLOW-MPI while concentrating on the effects of chemical reactions and turbulent-shock interactions in subsonic and supersonic flows.

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تاریخ انتشار 2017