Validation of Low and High-Fidelity Turbulence Models for Prediction of Turbulent Heat Transfer in Low Prandtl Number Flows Under Buoyant and Separated Flow Conditions

Abstract The objective of this study is to assess the predictive capabilities of low and high-fidelity turbulence models for low-Prflows. For this purpose, predictions by two-equation (k-ε) Reynolds-Averaged Navier Stokes (RANS), partially-averaged Navier Stokes (PANS) hybrid RANS/Large Eddy Simulation (LES), and DSM, WALE, filtered LES models are compared for four different test cases, namely vertical channel flow, vertical backward facing step, flow over a rod bundle and heat transfer in ascending and descending flow through a pipe with a constant wall heat flux. The test cases involve a range of complex flow conditions including separation/reattachment and aiding and opposing buoyant forcing (Re ranging from 640 to 40K; Ri ranging from −0.65 to 0.65) for water (Pr = 0.71) and liquid metals (Pr = 0.00585 to 0.025) flows. The validation study demonstrates that turbulence models are 4% more accurate for higher Prflows that for low-Pr flows; 6% more accurate for forced convective conditions than for flows involving mixed convective conditions; and predict aiding buoyant flow conditions better than the opposing buoyant flow conditions. Overall, LES performed the best and provided averaged error of 6% followed by 10% by PANS and RANS showed the largest error of 14%.