Sensitivity analysis and multi-objective robust design optimization of compact aero-engine nacelles

Future civil aero-engines are expected to feature larger bypass ratios and fan diameters to reduce specific thrust and improve propulsive efficiency, thereby lowering specific fuel consumption. These new configurations introduce design challenges, as the traditional scaling will result in the increase of nacelle drag, weight and the integration effects of aircraft. For this reason, compact nacelles are preferred for integration with next-generation civil turbofan engines. Moreover, designing and optimizing compact aero-engine nacelles is particularly challenging due to the non-linear nature of transonic aerodynamics and the diverse operating conditions experienced across the flight envelope. This work first establishes a mapping relationship between geometric parameters and the nacelle drag coefficient through surrogate models across various operating conditions. Then, sensitivity analyses are performed by applying the Sobol sequence sampling method and variance-based sensitivity analysis within the design bounds. To investigate the impact of compactness on the uncertainty of the drag coefficient, compact nacelles with various length-to-highlight radius ratios are examined. The Sobol-based sensitivity analysis reveals that the ratio [Formula: see text] dominates the first-order effects, with its total-effect Sobol index remaining above 85% across all configurations. The optimized design shows significantly smaller absolute changes compared to the baseline, particularly in the nacelle cruise drag coefficient [Formula: see text] at mid-cruise condition, with the variation reduced from 0.0017 to 0.0004, indicating that the optimized nacelle design is more geometric robust and less sensitive to parameter variations. The novelty of this work lies in applying Sobol-based sensitivity analysis to quantify geometric parameter impacts on nacelle drag under uncertainty during cruise conditions. The qualitative and quantitative analysis results will provide valuable insights for determining the design space in the early stages of the design process and developing a robust design optimization framework for three-dimensional compact nacelles.