RANS MODELING OF FLOW IN ROTATING CAVITY SYSTEM

Overview & Synopsis

The accurate prediction of fluid flow within rotating systems has a primary role for the reliability and performance of gas turbine engine. The selection of a suitable turbulence model for the study of such complex flows remains an open issue in the literature. This paper reports a numerical benchmark of the most used eddy viscosity RANS models available within the commercial CFD solvers Fluent and CFX together with an innovative Reynolds Stress Model closure. The predictions are compared to experimental data and previous numerical calculations available in the open literature for three test cases. Test case 1 corresponds to a rotating cavity with a radial outflow, considered experimentally by Owen and Pincombe. In that case, the main difficulty arises from the choice of the boundary conditions at the outlet. Several types of boundary conditions have been then considered. All models fail to predict the radial velocity distribution. Nevertheless, the RSM offers the best agreement against the experimental data in terms of the averaged tangential velocity in the core. Test case 2 corresponds to a Taylor-Couette system with an axial Poiseuille flow studied experimentally by Escudier and Gouldson. Even if the two-equation models provide reliable data for the mean velocity field, they strongly underestimate the turbulence intensities everywhere. The agreement between the RSM and the measurements is rather satisfactory for the mean and turbulent fields, though this second-order closure does not predict the asymmetry of the normal stresses. The main discrepancies appear indeed very close to the stator. Test case 3 is a rotor-stator system with throughflow, corresponding to the test rig of Poncet et al. All the models catch the main features of rotor-stator flows, such as the value of the entrainment coefficient or the location of the transition from the Stewartson to the Batchelor flow structures. The RSM improves especially the predictions of the shear stress.