Hybrid-parameterization-based robust design optimization for a blended-wing-body aircraft

Compared with conventional configurations, the Blended Wing Body (BWB) features a more compact system layout and offers significant aerodynamic benefits. However, it is also characterized by strong coupling among the airframe, intake/exhaust, and propulsion systems, together with high sensitivity to flight-condition variations. To fully exploit the advantages of the BWB configuration and improve performance robustness, this paper proposes a hybrid parameterization that combines the Free-Form Deformation (FFD) technique with a two-dimensional shape-blending function and a B-spline method, enabling geometric deformation of both the airframe and the intake/exhaust systems. By integrating it with uncertainty quantification and the gradient-based optimization framework, an integrated internal-external flow robust design optimization (RDO) methodology is established to perform both deterministic (“DeOpt”) and robust (“UnOpt”) optimizations. The corresponding gradients of the parameterization and statistical moments are derived and coupled with the discrete-adjoint-based framework. The optimization results show that the hybrid parameterization improves the overall performance of the BWB by refining key airframe and inlet geometric features. Specifically, “DeOpt” reduces the drag coefficient ( C_d ) and distortion coefficient (▵σ‾) by 19.2% and 49.8%, respectively, while increasing the total pressure recovery coefficient ( σ _AV) by 1.8%. Compared with “DeOpt”, “UnOpt” yields slightly lower design-point performance but significantly improves robustness, with the standard deviations of C_d, σ _AV, and ▵σ‾ reduced by 30%, 1.5%, and 2.7%, respectively. These results demonstrate the capability of the proposed method to capture key BWB geometric characteristics and improve both overall performance and robustness, thereby providing a methodological foundation for future airframe-engine integrated design.