Assessment of the predictive capability of RANS models in simulating meandering open channel flows

• Published in: Journal of hydrodynamics. Series B Vol. 29; no. 1; pp. 40 - 51
• Main Author: 周建银 邵学军 王虹 假冬冬
• Format: Journal Article
• Language: English
• Published: Singapore Elsevier Ltd 01.02.2017; Springer Singapore
• Subjects: boundary layer separation; Engineering; Engineering Fluid Dynamics; Hydrology/Water Resources; meandering channel; near-wall treatment; Numerical and Computational Physics; RANS model; secondary flows; Simulation; turbulence model; secondary flows; RANS model; meandering channel; near-wall treatment; boundary layer separation; turbulence model
• DOI: 10.1016/S1001-6058(16)60714-X
• ISSN: 1001-6058

The predictive capability of Reynolds-averaged numerical simulation(RANS) models is investigated by simulating the flow in meandering open channel flumes and comparing the obtained results with the measured data. The flow structures of the two experiments are much different in order to get better insights. Two eddy viscosity turbulence models and different wall treatment methods are tested. Comparisons show that no essential difference exists among the predictions. The difference of turbulence models has a limited effect, and the near wall refinement improves the predictions slightly. Results show that, while the longitudinal velocities are generally well predicted, the predictive capability of the secondary flow is largely determined by the complexity of the flow structure. In Case 1 of a simple flow structure, the secondary flow velocity is reasonably predicted. In Case 2, consisting of sharp curved consecutive reverse bends, the flow structure becomes complex after the first bend, and the complex flow structure leads to the poor prediction of the secondary flow. The analysis shows that the high level of turbulence anisotropy is related with the boundary layer separation, but not with the flow structure complexity in the central area which definitely causes the poor prediction of RANS models. The turbulence model modifications and the wall treatment methods barely improve the predictive capability of RANS models in simulating complex flow structures.