Neural network modeling of scour cone geometry around outlet in the pressure flushing

Abstract

When flushing carry out as pressure condition, a scour cone is performed around the outlet. As the flow around the outlet in the pressure flushing is three dimensional, therefore that it is difficult to establish a general empirical model to provide accurate estimation for scour cone volume and length. In this study artificial neural network (ANN) with multi-layer perception which using backpropagation algorithm (MLP/BP) was used. The scour cone volume (Vf) and length (Lf) were modeled as a function of three variables; water depth (HW), mean flow velocity through outlet (uf) and mean grain diameter (D50). For training and testing model, experimental data in two forms of original and non-dimensional are selected. The results of this research indicate that MLP/BP model can predict the scour cone volume and length. Finally, sensitivity analysis with original and nondimensional data set show that mean flow velocity through outlet (uf) and uf/√(g (Gs-1)D50) have a greater influence on scour cone volume and length rather than other parameters. © 2012 Global NEST.