G. Eriş

Deep-Learning-Based Inverse Airfoil Design Using Global Aerodynamic Performance Metrics

This paper introduces a framework for airfoil inverse design, using a deep-learning approach and incorporating both the parametric section (PARSEC) and class–shape transformation (CST) airfoil parameterization techniques for comparative evaluation. A predictive model has been established to estimate the PARSEC and CST...