AUTOMATIC NEURAL NETWORK SYSTEM FOR VORTICITY OF SQUARE CYLINDERS WITH DIFFERENT CORNER RADII

The neural networks (NNs) simulation has been designed to simulate and predict the vortex wavelength ${\lambda}_x^*$, lateral vortex spacing ${\lambda}_y^*$, and normalized maximum vorticity at the vortex center near the wake of square cylinders with different corner radii. The system was trained on the available data of the three cases, although this data is very little. Therefore, we designed the system to work in automatic way for finding the best network that has the ability to have the best test and prediction. The proposed system shows an excellent agreement with that of an experimental data in these cases. The technique has been also designed to simulate the other distributions not presented in the training set and predicted them with effective matching.