The neural networks (NNs) simulation has been designed to
simulate and predict the vortex wavelength
x, lateral vortex spacing
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 systemshows an excellent agreementwith 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. |
