Study of flow in a planar asymmetric diffuser using large-eddy simulation

Abstract

Large-eddy simulation (LES) has been used to study the flow in a planar asymmetric diffuser. The wide range of spatial and temporal scales, the presence of an adverse pressure gradient, and the formation of an unsteady separation bubble in the rear part of the diffuser make this flow a challenging test case for assessing the predictive capability of LES. Simulation results for mean flow, pressure recovery and skin friction are in excellent agreement with data from two recent experiments. The inflow consists of a fully developed turbulent channel flow at a Reynolds number based on shear velocity, Reτ=500. It is found that accurate representation of the in flow velocity field is critical for accurate prediction of the flow in the diffuser. Although the simulation in the diffuser is well resolved, the subgrid-scale model plays a significant role for both mean momentum and turbulent kinetic energy balances. Subgrid-scale stresses contribute a maximum of 8% to the local value of the total shear stress with the maximum values found in the inlet duct and along the flat wall where the flow remains attached. The subgrid-scale model adapts to the enhanced turbulence levels in the rear part of the diffuser by providing more than 80% of the dissipation rate for turbulent kinetic energy. The unsteady separation excites large scales of motion which extend over the major part of the duct cross-section and penetrate deeply into the core of the flow. Instantaneous flow reversal is observed along both walls immediately behind the diffuser throat which is far upstream of the location of main separation. While the mean flow profile changes gradually as the flow enters the expansion, turbulent stresses undergo rapid changes over a short streamwise distance along the deflected wall. An explanation is offered which considers the strain field as well as the influence of geometry changes. The effect of grid resolution and spanwise domain size on the flow field prediction has been documented and this allows an assessment of the computational requirements for carrying out such simulations.