A Computational Framework for Tailfin Geometry Optimization in Low Reynolds Number Flight

This project optimizes tailfin (vertical stabilizer) planform geometry for low Reynolds number flight (Re ≈ 50k–100k) through a closed loop that connects parametric CAD, transition-modelled OpenFOAM, a machine-learning surrogate with a Pareto search, and wind tunnel validation. The first three stages are complete, and the headline result is an optimized fin that buys roughly 40% more directional stability for about 14% more drag versus an RQ-11 Raven style baseline.