Energy Loss Prediction in a Compound Channel having Skewed Flood Plains using Artificial Neural Network

Abstract

Energy loss in a compound channel is an essential requirement for determining any hydraulic parameters in a compound channel. Compound channels are generally classified as prismatic compound channels and non-prismatic compound channels. In prismatic compound channel the geometry of the channel remains same throughout the channel length and the energy loss takes place in a simple manner where as in the case of non-prismatic compound channels the geometry of the channel does not remains same throughout the channel length and the energy loss takes place in a complex phenomenon. In the present study non-prismatic compound channel with skewed flood plains is taken into consideration and the effect of skew angle and the skewed distance on the energy loss is studied. Artificial Neural Networks (ANN) is used as a tool for developing a relation among energy loss and different hydraulic parameters. Software named Computational Centre for Hydro-science and Engineering (CCHE-2D) is used to analyse the flow characteristics in a compound channel having skewed flood plains by simulating the Digital Elevation Model(DEM) of an artificial channel created using software named ARC-GIS. The flow parameters include depth averaged velocity and boundary shear stress values. Variation of depth averaged velocities of the compound channel was studies along five different sections along the skewed region of the channel. From the study it was clear that as the skew angle increases the velocity along the sections decreases. From ANN a model equation has developed using trained weights and biases and in order to find out the important parameter that is responsible for energy loss a technique called sensitivity analysis was carried out. From this sensitivity analysis skew angle (θ) was found to be the most important influencing parameter.