A recently developed hybrid RANS/LES model, known as the Limited Nu- merical Scale approach (LNS), is applied to the simulation of the flow around a square cylinder at a Reynolds number, based on the free-stream velocity and on the side length, equal to Re = 2.2 · 104. The hybrid model uses an eddy-viscosity which is given by a local blending, depending on the grid resolution, between two eddy viscosities coming re- spectively from the k − ε RANS closure and from the Smagorinsky LES model. A mixed finite-element/finite-volume formulation on unstructured grids is used to discretize the LNS equations. The results obtained with the hybrid approach are compared with those given by RANS and LES simulations for two different grid resolutions; comparisons with experimental data and numerical results in the literature are also provided. It is shown that, when the resolution is adequate for LES, the LES accuracy is recovered by the LNS model. For a coarser resolution, the blending criterion noticeably improves the results with respect to both RANS and LES approaches.
An Hybrid RANS/LES Approach Applied to Bluff-Body Flow Simulation
CAMARRI, SIMONE;SALVETTI, MARIA VITTORIA;
2004-01-01
Abstract
A recently developed hybrid RANS/LES model, known as the Limited Nu- merical Scale approach (LNS), is applied to the simulation of the flow around a square cylinder at a Reynolds number, based on the free-stream velocity and on the side length, equal to Re = 2.2 · 104. The hybrid model uses an eddy-viscosity which is given by a local blending, depending on the grid resolution, between two eddy viscosities coming re- spectively from the k − ε RANS closure and from the Smagorinsky LES model. A mixed finite-element/finite-volume formulation on unstructured grids is used to discretize the LNS equations. The results obtained with the hybrid approach are compared with those given by RANS and LES simulations for two different grid resolutions; comparisons with experimental data and numerical results in the literature are also provided. It is shown that, when the resolution is adequate for LES, the LES accuracy is recovered by the LNS model. For a coarser resolution, the blending criterion noticeably improves the results with respect to both RANS and LES approaches.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
