Prediction of hydraulic jump length downstream of multi-vent regulators using Artificial Neural Networks

Multi-vent regulators are widely used in Egypt. Operation system of gates affects the characteristics of the flow downstream (DS) of multi-vent regulators. The current study aimed toward introducing the artificial intelligence technique as a new modeling tool in the prediction of the characteristics of the flow downstream of multi-vent regulators under the management and operating systems of multi-gates. Specially Artificial Neural Network (ANN) is utilized in the current study in conjunction with experimental data to predict the relative length of the submerged hydraulic jump (HJ) occured DS of multi-vent regulators under the different cases of gates operation. The results show that ANN technique is very successful in simulating the relative submerged hydraulic jump length occurred in stilling basins downstream of multi-vent regulators better than multiple linear regression (MLR).