AI RESEARCH

Optimization and Generation in Aerodynamics Inverse Design

arXiv CS.LG

ArXi:2602.03582v3 Announce Type: replace Aerodynamic inverse design can improve vehicle and aircraft efficiency, but practical design rarely seeks performance alone: vehicle refinement must reduce drag while preserving visual features linked to design language, brand recognition and user perception. Traditional CFD-driven optimization is accurate but slow for broad exploration, and current learning-based methods are still largely performance-driven and lack a coherent target linking optimization, generation and visual consistency.