Modeling of free jumps downstream symmetric and asymmetric expansions: theoritical analysis and method of stochastic gradient boosting

The general computational approach of Stochastic Gradient Boosting (SGB) is seen as one of the most powerful methods in predictive data mining. Its applications include regression analysis, classification problems with/without continuous categorical predictors. The present theoretical and experimental study aims to model the free hydraulic jump created through rectangular Channels Downstream (DS) symmetric and asymmetric expansions using SGB. A theoretical model for prediction of the depth ratio of jumps is developed using the governing flow equations. At the same time, statistical models using linear regression are also developed. Three different parameters of the hydraulic jump are investigated experimentally using modified angled-guide walls. The results from the modified SGB model indicate a significant improvement on the original models. The present study shows the possibility of applying the modified SGB method in engineering designs and other practical applications.