Diana-Andreea Sterpu

Tuning Machine Learning Outcomes for Airfoil Aerodynamics Seed Sensitivity in Predictive Performance

Abstract. Accurate aerodynamic performance prediction remains critical in preliminary design and optimization workflows. This study proposes a hybrid deep learning framework that combines convolutional neural networks (CNNs), operating directly on raw airfoil geometries, with two fully connected branches that process e...