Scour Depth Prediction for Asa Dam Bridge, Ilorin, Using Artificial Neural Network

Abstract

Bridge Scour is the localized loss of the geomaterials around the foundation of a bridge as a result of the movement of water around it. Scour is a great risk to the stability of a bridge’s foundation, thus leading to collapse, loss of lives and setback in a nation’s socio-economic life. Artificial Neural Networks (ANN) are collections of simple, highly connected processing elements that learn according to sets of input parameters and use that to simulate the networks of nerve cells of humans or animal central nervous system. The Asa Dam Bridge, one of the longest bridges in Ilorin, Kwara State, Nigeria, has five (5) spans of 20m each. The bridge connects Ilorin to the Ogbomosho Express way (leading to the western part of the country) and the Eyenkorin-Jebba road (leading to the north). Thus, the bridge has a high economic value. In this research, factors such as flow depth, average flow velocity of the river and median sediment size were investigated to show how they affect the depth of scour around the bridge pile foundation. Data were taken for a period of 48 weeks and ANN was applied to predict and generate a model that shows how these factors relate to the scour depth of the riverbed. The model revealed that the hydraulic parameters and soil grading around the pile cap of Asa River Bridge bears significant influence on the scour depth of its foundation. The model was compared with five (5) other established scour equations.