Aerodynamic Interference Mechanisms and Optimization of Two-Dimensional Tandem Airfoils Based on a Bayesian Optimization Framework
Year: 2026
Type: article
Abstract: The highly nonlinear aerodynamic interference in tandem-airfoil configurations significantly hinders the precise exploitation of their aerodynamic potential. To address this issue, this study establishes a high-fidelity computational fluid dynamics benchmark. A high-quality sample set is constructed using Latin hypercube sampling combined with an intra-layer replacement strategy. Subsequently, a Gaussian process surrogate model and Bayesian optimization are employed to maximize the total system lift coefficient across a four-dimensional design space comprising longitudinal and vertical separations, fore airfoil angle of attack, and angle of attack difference. Global sensitivity analysis indicates that longitudinal separation dominates the interference modes. Optimization reveals a distinct mode switching phenomenon using a longitudinal separation of twice the chord length as the critical threshold. In the close-coupled configuration, a negative optimal angle of attack difference enhances the slot effect and upwash induction, thereby delaying rear airfoil stall and achieving synergistic lift enhancement. Conversely, in the distant-coupled configuration, the system transitions to a decoupled compensation mode, where a positive angle of attack difference compensates for the effective angle of attack loss induced by wake downwash. This research elucidates the competitive mechanisms between inter-airfoil slot flow and wake interference, providing a theoretical reference for the aerodynamic layout optimization of tandem-airfoil aircraft.
Source: Applied Sciences
DOI: 10.3390/app16105145
Authors: Haijun Gong, Jiayi Li, Tianyu Xia, Haiqing Si, Hao Dong
Institution: Nanjing University of Aeronautics and Astronautics
Language: English
Subfield: Computational Mechanics
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,896
Awards: G1320505835, G1775096532
OpenAlex ID: W7162011693
