Assessment of RANS-Based Turbulence Models for Buoyancy-Influenced Forced Convection on a Heated Vertical Surface

Over the past 50 years, an industry-wide shift within the nuclear community has led to increased utilization of computational fluid dynamics (CFD) to supplement nuclear reactor safety (NRS) analyses. Although several “best practice” guidelines exist for individual safety evaluations, comprehensive validation efforts against benchmark-quality experimental data must occur to ensure the accuracy of these numerical models. One such area of interest to the nuclear engineering community is the capacity of computational models to predict heat transfer across a spectrum of buoyancy conditions. In this vein, the present investigation provides a robust assessment of 13 different Reynolds-averaged Navier–Stokes (RANS) turbulence models and their ability to predict thermal system response quantities (SRQs) in buoyancy-influenced forced convection conditions. Using experimental data from the rotatable buoyancy tunnel (RoBuT) as the basis of comparison, the predictive capabilities of each turbulence model are evaluated in both buoyancy-aided and opposed configurations. Thermocouple measurements are mapped to the boundaries of the computational models to permit direct comparisons of various SRQs. ASME standards are used to quantify numerical discretization uncertainties in the modeled results, while a Monte Carlo procedure is developed to account for input uncertainty. Generally, the collection of turbulence models fails to accurately predict thermal SRQs in the buoyancy-aided configuration, while analogous errors in streamwise velocity are observed in the buoyancy-opposed orientation. Both modeling errors are attributed to improper predictions of the turbulent viscosity, which will need to be rectified prior to wide-scale adoption for nuclear reactor safety calculations.