Inverse Design of Supercritical Wing Based on Enhanced RBF Neural Network

A novel inverse design method is established based on enhanced RBF neural network and improved differential evolution algorithm. This method combines some advantages of inverse design and optimization. The inverse design problems are transformed into optimization problems to some extent and the dependence on reasonable target pressure distribution is reduced. With enhanced RBF neural network, the calculation efficiency is improved. The application in supercritical wing design shows that this method is reasonable and can be used to research the effect of pressure distribution. The improvement of the drag divergence characteristic is owing to the change of shock location.