Development of Aero AI for Initial Flight Shape Design of Small Fixed-Wing UAV

We created Aero Artificial Intelligence (Aero AI), an innovative AI platform for optimal Unmanned Aerial Vehicle (UAV) flight shape design. Aero AI guides designers to select UAV shape parameters intuitively. It assembles an initial UAV model based on selected parameters for shape evaluation. Then, it utilizes Stanford University Unstructured (SU2) for aerodynamic analysis and employs AI for neural network deep learning to generate reliable aerodynamic parameters without extensive wind tunnel tests for design. Aero AI reduces reliance on wind tunnel tests, saves energy and resources, and expedites the shape design process. AI platforms have permeated human life at an expeditious pace in recent years. Aero AI furnishes instantaneous and personalized responses to aerodynamic parameters. The development of such platforms facilitates a diverse spectrum of aerodynamic configurations and designs from commonplace knowledge-based inquiries to intricate domain-specific topics. By employing natural language processing methodologies, user interrogatives and proffer corresponding resolutions are enabled. The Aero AI platform applies continuous learning algorithms to augment response accuracy and relevance. Being intelligent inquiry-based, ubiquitous applications across myriad domains are possible, including customer service provisioning on web-based platforms, educational instruction aids, enterprise knowledge management, and issue resolution paradigms.