Development of a Relationship for Air Vent Discharge in Bottom Outlets Using Numerical Simulation

Source: ICHE Conference Archive - https://mdi-de.baw.de/icheArchiv

Numerical modeling of boundary shear stress distribution in compound channel flow

Proceedings of the Seventh International Conference on Hydroscience and Engineering, Philadelphia, PA, September 2006. http://hdl.handle.net/1860/732In compound channels, turbulence effects of bed friction and large shear layer at the interaction region between the slow moving flow in the flood plain and fast moving flow in the main channel results in a complex three dimensional flow structure. This structure implies the necessity of 3D numerical models. In the present investigation, shear stress distribution at boundaries of compound channels was calculated using a 3-D shallow water numerical model. To develop the model, a multilayer scheme was implemented. Since one of the important features of flow in such channels is the effect of turbulence on flow behavior, a Prandtle mixing length model, a Nezu-Rodi zero equation model, and a two-equation standard k −ε model were applied in the present research and their results were compared. To verify flow behavior for these turbulence models in different relative depths two sets of experimental data were utilized. Results showed that the model was able to show correctly the trend of shear stress distribution in such a complex flow especially at higher relative depths and could be used in practical engineering calculations. All three turbulence models showed similar results with slightly better results found from the k −ε model

Wave Evolution in Water Bodies using Turbulent MPS Simulation

Moving Particle Semi-implicit (MPS) which is a meshless and full Lagrangian method is employed to simulate nonlinear hydrodynamic behavior in a wide variety of engineering application including free surface water waves. In the present study, a numerical particle-based model is developed by the authors using MPS method to simulate different wave problems in the coastal waters. In this model fluid and solid are treated as separate phases and governing equations of momentum and continuity are solved for them concurrently. For simulations of turbulent wavy flows, constant eddy viscosity, Prandtl’s mixing length theory and k-ε models were considered. In addition, higher order of MPS operators was applied to suppress numerical oscillation in comparison with previous studies. The developed method was applied to some cases, including still water reservoir, solitary wave propagation in a tank, tsunami run-up on an inclined wall and wave generation due to the landslide. Evaluation of the developed model results, in compare with data cited in the literature showed enhancement in the accuracy of the developed numerical model especially in compare with existing inviscid models. Besides, the numerical tests results have shown that applying k-ε turbulence model, have equipped MPS model with a useful, powerful and reliable tool for simulating water free surface in wave motion, wave impact and the breaking process

Experimental study of head shape effects on shear stress distribution around a single groyne

River hydrodynamicsInteraction with structure

Design of Riprap Stone Around Bridge Piers Using Empirical and Neural Network Method

An attempt was made to develop a method for sizing stable riprap around bridge piers based on a huge amount of experimental data, which is available in the literature. All available experimental data for circular as well as round-nose-and-tail rectangular piers were collected. The data for rectangular piers, with different aspect ratios, aligned with the flow or skewed at different angles to the flow, were used in this analysis. In addition, new experiments were also conducted for larger pier width to riprap size ratio, which was not available in the literature. Based on at least 190 experimental data, the effect of important parameters on riprap stability were studied which showed that the effective pier width is the most effective parameter on riprap stability. In addition, an empirical equation was developed by multiple regression analysis to estimate the stable riprap stone size around bridge piers. The ratio of predicted to experiment riprap size value for all experimental data is larger than one with an average value of 1.75, which is less than many other empirical equations. Finally, in order to achieve a higher accuracy for riprap design, the artificial neural network (ANN) method based on utilizing non-dimensional parameters was deployed. The results showed that the ANN model provides around a 7% improved prediction for riprap size compared to the conventional regression formula