Abstract
The goal of this study was to provide more experimental data on the main geometric characteristics of an inclined negatively buoyant jet discharged into deep stagnant water, as well as to use the data for developing and evaluating the performance of the proposed model. Series of laboratory experiments were performed using a high-resolution digital camera to determine the main geometric characteristics of two jet discharge angles, 15 degrees and 52 degrees. Various densimetric Froude numbers (Fr-d) were used in this study, ranging from 11 to 75. The results showed that the behavior of the jet is significantly affected by the Fr-d and the initial discharge angle (theta). A comparison of the present results with previously reported data showed good agreement for all geometric parameters, especially for the angle of 15 degrees, while the 52 degrees values differed slightly. A nonlinear method (artificial neural network, ANN) called the group method of data handling (GMDII) was employed in this study to develop explicit equations for the geometric characteristics of the two studied angles. This method has not previously been used in the prediction of mixing of inclined dense jets. Moreover, different statistical indices were utilized to evaluate the accuracy of the proposed equations. The values of R-squared (R-2) and the mean absolute percentage error (MAPE) for the geometric characteristic ranged between 0.964 to 0.995 and from 2.6% to 8.4% respectively, which indicate that the GMDH model performed very well. The GMDH results provided good predictions for both angles for the data used within this study.