Dynamic stall, which has a significant effect on the aerodynamic performances of dynamic airfoils, is closely related to the physics of the dynamic stall vortex (DSV). The physics of the DSV on the NACA 0012 airfoil was experimentally studied using unsteady pressure measurements with high time accuracy. The experimental Reynolds number was Re = 1.5 × 10⁶, and the reduced frequency was k = 0.069. The propagation of the unsteady pressure field during the dynamic stall process was analyzed in detail. The motion characteristics of the DSV were examined, including its near-wall development characteristics and near-wall evolution velocity. Moreover, the frequency characteristics of the near-wall DSV were studied using wavelet analysis combined with proper orthogonal decomposition (POD) technology. In addition, the effects of the mean angle of attack (AoA) and the amplitude on the DSV motion and frequency characteristics were examined in detail. The effects of the mean AoA on the near-wall DSV strength and the propagation velocity were linear, while the effects of amplitude were nonlinear. The mean AoA and amplitude had a significant influence on the frequency of the leading-edge vortex (LEV) at the initial stage of the DSV development (x/c = 0.10–0.20). This work allows the DSV physics to be understood more deeply. Graphic abstract

In this study, the aerodynamic performance of bionic airfoil was numerically studied by CFD method. The bionic airfoil was represented by the combination of airfoil and a small trailing edge flap. A variety of configurations were calculated to study the effect of flap parameters, such as the flap angle, position, and shape, on the bionic airfoil aerodynamic characteristics based on two layouts which were that (1) there was a tiny gap between the airfoil and the flap and (2) there was no gap between the two. The results showed that the flap angle and position had significant effects on the aerodynamic performance of the airfoil with the two layouts. Compared with the clean airfoil, the maximum lift coefficients of the first layout and the second layout could be increased by 10.9% and 7.9%, respectively. And the effective angle of attack (AoA) range for improving the lift-to-drag ratio could reach 7°. The flap shape also affected the airfoil aerodynamic characteristics, and the flap with the sinusoid curve shape showed ideal performance.

Studying the scale effect of dynamic airfoil is helpful for understanding the dynamic stall phenomenon and unsteady wall interference. In this paper, the scale effect of the dynamic stall characteristics of the dynamic National Advisory Committee for Aeronautics 0012 airfoil was studied using time-resolved pressure measurements for the first time, which is different from the Reynolds number effect as the experimental Reynolds number was not varied. The evolution of the pressure field and vortex development characteristics on different scaled models was investigated. Significant scale effects were observed on the dynamic airfoil during its dynamic stall. With the model scale increases from c = 500 to 900 mm, the shear layer vortex and the secondary separation were observed, indicating that vortices on the suction surface were enriched. Furthermore, the vortex-induced suction and its occurrence time were significantly affected. The vortex-induced suction varied from Cp ≈ −4.25 to −1.5. With the model scale increases from c = 500 to 900 mm, the vortex structure occurrence angle of attack was delayed by Δα ≈ 0.5°. Further analyses showed that the scale effects of the dynamic airfoil are attributed to the flow transition and unsteady wall interference interactions. Thus, two physical quantities, S_m and S_w, were innovatively defined to associate the vortex complexity, model scale, and wind tunnel wall pressure. This study helps deepen the understanding of the dynamic stall phenomenon and provides guidance for the unsteady wall interference correction.

Discovering design rules is essential for advancing interpretable and intelligent propeller design. This paper proposes a knowledge–data hybrid-driven method for discovering design rules for high-efficiency propellers, with the aim of expanding the pool of comparable design data while reducing the search space for candidate rule parameters. Based on the propeller ideal efficiency theory, an efficiency factor is introduced to address the lack of comparability among performance data caused by differences in propeller loading, thereby enabling all designs in the database to be used for data mining. Dimensionless composite features are then constructed using the principle of dimensional homogeneity and screened through correlation analysis within a knowledge–data hybrid-driven framework. Six characteristic load ratios are identified as rule parameters, yielding the following design rule: a propeller has a high efficiency factor when all six ratios lie within their respective optimal ranges. Finally, the rule is validated on 12 independent designs, including three designs of a different propeller. The proposed knowledge–data hybrid-driven feature-engineering framework provides a viable approach to design-rule discovery and may support inverse design and intelligent propeller design.