Yaser Sheikhi, Babak Lashkar-Ara
Friday 3 july 2015
9:45 - 10:00h
at Africa (level 0)
Themes: (T) Special session, (ST) Design of intake stations
Parallel session: 14D. Special session: Design of intake stations
Horizontal intakes are one of the most important parts of hydraulic sets such as river for irrigation or reservoir for power generation and industrial purposes. Intake submergence depth could result in formation of the vortices. Formation of the vortices in front of intake is the result of complex interaction between many parameters and cause operational problems for turbine or pump and reduction of coefficient of discharge. In this study, the equation for estimating critical submergence were developed using experimental data. Results compare with critical spherical sink surface (CSSS) presented by Yilderim et al (1995,2000,2002), equation presented by Gurbuzdal (2009) and artificial neural network (ANN) approach. According to the results, the neural network is more accurate than previous models proposed by researchers and equation presented in this study, but better agreement between the presented equation and experimental data than CSSS I, CSSS II and equation presented by Gurbuzdal (2009). Therefore the presented equation as a simple and precision equation with the value of RMSE and R^2 respectively 0.283 and 0.826, for estimation of the critical submergence is recommended Keywords: Critical Submergence, Nonlinear Regression, CSSS, Neural Network