Abstract
The predictive capability of RANS, hybrid RANS/LES and LES turbulence models are assessed for low-Pr flows involving complex flow features expected in engineering applications, such as forced convection, buoyancy, shear, reattachment, and recirculation. The models are tested for three test case vertical channel, vertical backward facing step with heated wall and rod bundle lattice cases for Pr ranging from 0.002 to 2.0. k-ε based model is used for RANS, partially averaged Navier Stokes (PANS) for hybrid RANS/LES and dynamic Smagorinsky model for LES. The channel and backward facing step cases show that LES performs the best followed by PANS and RANS. The RANS model performs reasonably well for flows with strong buoyant forces, which augments the mean flow more than the turbulent features. But for moderate buoyant flow condition, which augments turbulence characteristics and associated diffusion, RANS models do not perform well. Considering both the computational cost and accuracy, the PANS provides a good compromise between RANS and LES.
