Predicting of Hydraulic Jump Characteristics of Sudden Expanding Stilling Basins Using Evolutionary Algorithm

Sudden expanding stilling basins are one of the energy dissipaters which can dissipate most of the kinetic energy of the flow through hydraulic jump. Accurate estimation of the hydraulic jump characteristics plays an important role in designing of hydraulic structures. Present study applies Gene Expression Programming (GEP) to estimate hydraulic jump characteristics in three different types of sudden expanding channels (i.e. channel without appurtenances, with a central sill and with a negative step). In this regard, different models were developed and tested. The results proved capability of GEP in predicting hydraulic jump characteristics in expanding channels. It was observed that the applied method is more accurate than semi-theoretical relationships. Also it was found that in the jump length prediction the model with input parameters Fr1 and (h2—h1)/h1 and in the sequent depth ratio and relative energy dissipation prediction the model with input parameters Fr1 and h1/B led to more accurate outcome. Sensitivity analysis showed that Fr1 had the key role in modeling. According to the results of the sensitivity analysis parameter Fr1 had the key role in modeling hydraulic jump characteristics.