Improvement of corner separation prediction using an explicit non-linear RANS closure

In this paper, an investigation into the effect of explicit non-linear turbulence modelling on anisotropic flows is presented. Such are typified in corner separations turbomachinery. The commonly used Reynolds-Averaged Navier-Stokes (RANS) closures, which Reynolds stress tensor modelled by Boussinesq (linear) constitutive relation with mean strain-rate tensor, often struggle to predict separation reasonable accuracy. physical reason for deficiency partially attributable hypothesis does not count anisotropy, whilst a separation, flow subject three-dimensional (3D) shear and effects due anisotropy may be ignored. light this, stress-strain developed Menter et al. adopted as modification Reynolds-stress anisotropy. Coupled Menter’s hybrid "k-?" ?"k-?" model, gives significantly improved predictions within compressor cascade, at both design off-design conditions. vorticity field studied further investigate reasons these improvements, highlighting its potential widespread applications prediction.