Determination of sequent depth of hydraulic jump over sloping floor with rounded and crushed aggregates using experimental and ANN model Available to Purchase

Hydraulic jump has numerous applications in the field of hydraulic engineering, such as energy dissipation over spillways, chlorinating of wastewater and many others. The sequent depth ratio is one of the important characteristics of hydraulic jump useful in designing the stilling basin. Despite its importance, the exact value of sequent depth ratio is still undetermined. In the present study an attempt has been made to find out the effects of roughness heights and slopes by conducting an experimental study and artificial neural network (ANN) model. Three different roughness heights of crushed and rounded aggregates and two positive bed slopes were used. The experimental results show that the reductions in sequent depth ratios are more in the case of crushed aggregate (4%–35%) than rounded on the same slope. By increasing bed slope, the sequent depth ratios show increasing trend in the range 3%–45%. The proposed ANN model has the capability to predict the sequent depth ratio with least MAPE (mean absolute percentage error) value 3.15%. Therefore, based on the results obtained from the empirical model and ANN model, it has been concluded that the present study can be better utilized for the estimation of the sequent depth ratio of hydraulic jump.