Using the movability number to model local clear-water scour in rivers
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University of Cape Town
Local scour is associated with a considerable number of bridge failures worldwide. It occurs at bridge piers and abutments as a result of interactions between complex flow features and the channel bed. The number of factors involved in the interactions makes it difficult to predict. A lot of research has therefore been performed by several investigators to gain insight into the scouring process and scour prediction. Currently, local scour is estimated using physical models, empirical formulae or numerical models. Of these methods, the use of numerical models appears to be more economical and ideal as it permits flexibility in the choice of flow parameters and allows different scenarios to be easily studied. The aim of this research was thus to investigation into the use of the commercial CFD code FLUENT 6.2 for scour prediction based on the Movability Number. The research, which focused exclusively on local clear-water scour at bridge piers, stemmed from previous works performed by Armitage & McGahey (2003) and Cunninghame (2005) in which the Movability Number approach was developed and assessed. Results from these studies indicated that there was considerable potential in the Movability Number approach and, also, there was a need for a completely automated procedure for scour prediction based on the approach. For the current research therefore, an 'equilibrium model' was developed in which the river bed was successively modified in response to computed bed Movability Numbers until the final result reflected an equilibrium clear-water scour hole. Unstructured grids were generated in GAMBIT 2.2 and imported into FLUENT for the simulations. The symmetry condition was applied and the grids were fined up in regions where large velocity gradients or changes in other fluid properties were expected. Before the clear-water scour evolution simulations were carried out, the performance of the standard k-& model was compared with that of the Reynolds Stress model, and standard wall functions with non-equilibrium wall functions for a flat bed. Both turbulence models predicted similar scour patterns. Results of the numerical simulations were compared with data from a physical model and it was found that the non-equilibrium wall functions predicted scouring in regions on the bed where scour was not observed in the physical model. The standard wall functions, on the other hand, appeared to give realistic results. Since the standard k-&model involved the solution of two transport equations whilst the Reynolds stress model involved the solution of seven, the former was used with the standard wall functions for the scour hole evolution simulations. It was believed that this would result in shorter simulation times. A scour potential was defined as the difference between a computed bed Movability Number and the critical Movability Number required for sediment movement. Scour was considered to occur at those locations where the scour potential values were greater than zero and the grid nodes were displaced in response. User-defined functions were written to perform the bed modifications and ensure the integrity of the mesh as the bed geometry changed. Five physical scour experiments were simulated numerically. These physical experiments were performed as part of the research and were carried out in a 0.6lm wide tilting flume in the Hydraulics laboratory of the Civil Engineering Department at the University of Cape Town. Results from the numerical simulations were compared with those from the physical models. Using the Movability Number to model local clear-water scour in rivers. Although, the numerically estimated equilibrium scour depths were relatively close to those from the physical models, the shapes of the scour holes were not that similar. This was attributed to numerical difficulties in accurately predicting the flow field (and hence the Movability Numbers) at the bed. It was recommended that ways of improving the accuracy of the flow field prediction be found in order to accurately predict the bed Movability Numbers. In general, however, the Movability Number approach showed considerable potential for use in the prediction of local clear-water scour.
Includes bibliographical references.
Abban, B. 2007. Using the movability number to model local clear-water scour in rivers. University of Cape Town.