Abstract
This study investigates the computational fluid dynamics (CFD) modeling of supercritical open channel junction flow using two different turbulence models: k-ω shear stress transport (SST) and k-ω SST scale-adaptive simulation (SAS), in conjunction with Volume of Fluid (VOF) and mixture multiphase models. The efficacy of these models in predicting the intricate free surface fluctuation and free surface elevation in a supercritical junction is evaluated through a comprehensive analysis of time-averaged free surface data obtained from CFD simulations and Light Detection and Ranging (LIDAR) measurements. The dimensionless Reynolds (Re) and Froude (Fr) numbers of the investigated scenario were Fr = 9 and Re = 5.1 × 104 for the main channel, and Fr = 6 and Re = 3.3 × 104 for the side channel. The results of the analysis demonstrated a satisfactory level of agreement with the experimental data. However, certain limitations associated with both CFD and LIDAR were identified. Specifically, the CFD performance was limited by the model’s incapacity to consider small-scale turbulent effects and to model air bubbles smaller than the cell size while the LIDAR measurements were limited by instrument range, inability to provide insight into what is happening below the water surface, and blind spots. Nonetheless, the k-ω SST turbulent model with the VOF multiphase model most closely matched the LIDAR results.
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