ANALYSIS OF AERODYNAMIC SHAPE OPTIMIZATION OF UNMANNED AERIAL VEHICLES BASED ON CFD SIMULATION AND ITS IMPACT ON FLIGHT STABILITY

Abstract

 This study presents a comprehensive analysis of aerodynamic shape optimization of unmanned aerial vehicles (UAVs) using Computational Fluid Dynamics (CFD) simulations, with a particular focus on its implications for flight stability. By integrating adjoint-based optimization methods with high-fidelity CFD modeling, the research systematically evaluated wing–fuselage configurations, static margins, and dynamic stability parameters under varied operating conditions. The results demonstrated substantial improvements in aerodynamic efficiency, with drag reductions of up to 15% in optimized configurations and lift-to-drag ratio increases of 12–18% compared to baseline models. Stability assessments indicated that optimized UAVs exhibited enhanced static margins and improved pitch and yaw damping coefficients, leading to superior longitudinal and lateral stability. Cross-validation with wind tunnel experiments confirmed the accuracy of the CFD predictions, underscoring the reliability of simulation-driven optimization in UAV design. Iterative refinement further highlighted that performance gains could be achieved without compromising stability, demonstrating the scalability and robustness of the optimization framework. The findings conclude that coupling aerodynamic performance with stability-focused optimization yields UAV designs that are both efficient and resilient, offering valuable insights for the advancement of next-generation UAV platforms in surveillance, logistics, and defense applications.