Analysis of hydraulic characteristics for hollow semi-circular weirs using artificial neural networks

Abstract

Weirs are small overflow dams used to alter and raise water flow upstream and regulate or spill water downstream watercourses and rivers. This paper presents the application of artificial neural network (ANN) to determine the discharge coefficient (Cd) for a hollow semi-circular crested weirs. Eighty five experiments were performed in a horizontal rectangular channel of 10m length, 0.3m width and 0.45m depth for a wide range of discharge. The results of examination for discharge coefficient were yielded by using multiple regression equation based on dimensional analysis. Then, the results obtained were also compared using ANN techniques. A multilayer perceptron MLP algorithm FFBP network was developed. The optimal configuration of ANN was [2,10,1] which gave mean square error (MSE) and correlation coefficient (R) of 0.0011 and 0.91, respectively. Performances of ANN model reveal that the Cd could be better estimated by the ANN technique in comparison with Cd obtained using statistical approach.