Multi-Fidelity Aerodynamic Optimisation of Fixed-Geometry UAV Systems Under Operational Design Constraints

Unmanned aerial systems are increasingly deployed in low-infrastructure environments, where long-range beyond-visual-line-of-sight missions must be performed with variable payloads and across multiple operational roles. For aircraft already in service, aerodynamic improvement must often be achieved without changing the underlying architecture. In such contexts, optimisation is not an unconstrained configuration design problem, but a constrained performance-improvement problem in which geometric freedom is limited by structural, integration, and operational requirements.This paper establishes aerodynamic optimisation for fixed-geometry UAV systems as a constrained performance-improvement problem and develops a structured multi-fidelity optimisation framework aligned with this class of problem. The approach is motivated by the limitations of existing methods, in which low-order models do not capture local aerodynamic interactions required for meaningful refinement, while high-fidelity methods are computationally prohibitive when applied across broad design spaces. The proposed framework separates global exploration and local refinement according to the structure of the problem, combining low-order wing-shape exploration with targeted high-fidelity fuselage optimisation.The methodology is applied to the HANSARD UAV developed by UAVAid Ltd. The optimised wing and fuselage are integrated into a final aircraft configuration and assessed using RANS simulations. For the final configuration, the lift-to-drag ratio increased from 13.503 to 16.09 under the evaluated operating conditions, corresponding to a 19.18\% improvement in aerodynamic efficiency. The approach is also relevant to other fixed-geometry aircraft systems, including retrofit and incremental development contexts in both unmanned and manned aviation, where performance improvements must be achieved within constrained design spaces.