Masoud Nobakhti

Efficient pitching moment prediction for canard-controlled missiles via transfer learning-based deep learning

This work proposes an efficient multilayer neural network framework to predict the pitching moment coefficient of canard-controlled missiles, significantly reducing the need for costly CFD data and providing a powerful surrogate tool for rapid design optimization based on trim angle of attack and geometric parameters.