Author(s): Gabor Fleit; Sandor Baranya; Hans Bihs

Linked Author(s): Gábor Fleit, Sándor Baranya, Hans Bihs

Keywords: CFD modeling; Level set method; RANS; Sediment transport

Abstract: Three-dimensional computational fluid dynamics (CFD) is more and more often used to solve various hydraulic engineering problems, such as the prediction of complex transient flow conditions or local scouring. Such 3D models offer the prediction of complex flow patterns determining the morphodynamic conditions (e.g., coherent turbulent structures), where the proper reproduction of the free surface is usually of key importance. In the direct vicinity of obstacles like bridges, piers or other hydraulic structures, the free surface problem becomes increasingly difficult due to high surface gradients, turbulent water level fluctuations or even hydraulic jumps. In this study, the level set method (LSM) based, CFD model REEF3D is used for the simulation of complex free surface flow and local scouring in the vicinity of submerged bridges, where pressurized flow conditions occur under the bridge decks. The open-source CFD code uses the LSM in a coherent manner for the representation of the free surface, the sediment bed and the solid boundaries (i.e., obstacles) as well. The numerical simulations are based on well-documented laboratory experiments – one focusing on the complex hydrodynamics over a schematic bridge geometry and another one on the local scouring under an arch bridge. Both Reynolds-averaged and large eddy simulations (LES) are performed, and their performance is assessed from the hydrodynamic and morphodynamic point of view as well. The LSM-based modeling framework offers the robust numerical simulation of complex hydro- and morphodynamic conditions, making REEF3D and other competent CFD models valuable tools to complement or partially replace expensive and time demanding physical model experiments. It is noted, that due to the uncertainties in the theoretical background of bedload transport, additional numerical tests and sensitivity analyses are required.

DOI: https://doi.org/10.3850/IAHR-39WC252171192022851

Year: 2022