Design, manufacturing, and performance characteristics analysis of atmospheric corona discharge propellers

This doctoral dissertation presents the design, fabrication, and performance evaluation of electrohydrodynamic (EHD) thrusters operating under atmospheric conditions. The study aims to enhance efficiency by reinforcing the ionic wind produced via corona discharge with Lorentz forces. After reviewing the historical development, physical mechanisms, and theoretical models of EHD systems, a hybrid thruster with a multi-needle-to-cylinder electrode configuration was designed and constructed. A solenoid coil was integrated to examine the influence of magnetic fields on ion dynamics and flow velocity. In addition, a novel laser–photodiode–based device, immune to external electric and magnetic fields, was developed to achieve high-precision flow measurements. Experimental findings verified that magnetic fields significantly improved EHD performance, leading to increased ionic wind velocity and thrust. The experimental data were analyzed using Support Vector Regression (SVR), Random Forest (RF), Gradient Boosting (GB), K-Nearest Neighbors (KNN), and ensemble learning methods. Among these, SVR and GB provided the most accurate predictions, demonstrating that machine learning techniques can outperform conventional theoretical models in forecasting system behavior. The main contributions of this study include: development of a hybrid EHD thruster, experimental validation of Lorentz force effects under atmospheric conditions, design of a high-accuracy flow measurement system, and application of artificial intelligence to model and optimize EHD performance. In conclusion, the research shows that EHD flows can be effectively enhanced through hybrid electro–magnetic approaches, offering a promising foundation for applications ranging from micro-scale cooling systems to space propulsion technologies.