Prediction of discharge through a sharp-crested triangular weir using ANN model trained with Levenberg-Marquardt algorithm

The measurement of discharge plays an important role in the design of open channels. Direct measurements of discharges in large canals and rivers are not feasible because of high flow. Weirs are the most widely used discharge-measuring device for open channels. In this study, the experimental study along with the modeling of discharge through a sharp-crested triangular weir using ANN model has been conducted. The sharp-crested triangular weirs having apex angles 30 degrees, 45 degrees, 60 degrees, 75 degrees, 90 degrees and weir heights 15 cm, 18 cm, and 20 cm have been used in this study. The experiments were conducted for each combination of weir angle and weir height. The head above the weir crest was measured for all such combinations of apex angles and weir heights for different discharges. These experimental data are then used to train the ANN model to predict the discharge over a sharp-crested triangular weir. The Levenberg-Marquardt algorithm has been used as training algorithm. The MSE and R have been used as statistical parameters to judge the performance of ANN model. The ANN model terminates after 18 epochs and the MSE obtained for training, validation and testing are 8.477e - 08, 1.471 e - 07 and 1.325 e - 07, respectively. The corresponding R values obtained for training, validation and testing are 0.9987, 0.9973 and 0.9962, respectively. It was also observed that the predicted discharge stays within the range of +/- 5% of the experimental discharge value. The model performance results are encouraging and conclusive and the developed ANN model may be used to predict the discharge over sharp-crested triangular weir precisely.