Machine Learning-Based Methodology for Predicting 2D Propeller–Airfoil–Flap Interactions
A surrogate modeling framework is developed that predicts the section-level aerodynamic response of a propeller–airfoil–flap configuration across a multi-dimensional space of propeller positioning, flap geometry, and operational conditions, enabling rapid, optimization-ready exploration of propeller–airfoil–flap config...