Reduced order aerodynamics is a field of computational science focused on developing and applying simplified models to predict aerodynamic behavior. These models, often derived from or validated against high-fidelity data, capture the essential characteristics of complex flow phenomena while achieving significant computational efficiency compared to full-order simulations. This approach is vital for applications requiring rapid analysis, such as design optimization, control system design, and the prediction of unsteady or dynamic aerodynamic forces.