Abstract Airfoils are mostly inefficient in their off-design conditions. In order to improve the aerodynamic performance of airfoils in these conditions, using an optimized cavity on airfoils as a passive method can be useful. In this study, a cavity on a Risø_B1_18 airfoil, which is used as a wind turbine airfoil, was optimized at an off-design angle of attack by incorporating a genetic algorithm into a RANS flow solver. For the cavity optimization, the geometry and downstream suction surface were defined by 16 parameters, and the lift-to-drag ratio was considered as the cost function at 14° angle of attack. The numerical solution showed that the optimized cavity traps a vortex, which postpones the stall. Due to the uncertainty of CFD especially at off-design conditions, it was necessary to evaluate the performance of the optimized cavity in a wide range of angles of attack. This study used the particle image velocimetry (PIV) measurement method to evaluate the improved flow structures over the optimized cavity. Two models of airfoils with and without the cavity were made of aluminum and installed inside the test section of an open-jet wind tunnel with an air speed of 30 m/s and a cross section of 30 × 30 cm 2 . The air flow on the suction side of the airfoils was measured at 7°–15° angles of attack by PIV. A comparison between the measured flow fields over the two airfoils showed that the optimized cavity postpones the stall angle by 3°. Furthermore, the cavity increases the momentum behind the airfoil at the angles of attack greater than 9°. After this angle, a further increase in the angle of attack increases the difference between the momentums behind the airfoils with and without cavity. The Risø_B1_18 airfoil with the optimized cavity can be used as a wind turbine airfoil at high angles of attack to increase the stall angle and decrease the instability and fluctuation at off-design conditions. Graphic abstract

中文翻译：

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通过 PIV 测量评估具有优化腔的 Risø_B1 翼型的气动性能增强

摘要 机翼在非设计条件下效率低下。为了在这些条件下提高翼型的空气动力学性能，在翼型上使用优化的空腔作为被动方法可能很有用。在这项研究中，作为风力涡轮机翼型的 Risø_B1_18 翼型上的空腔通过将遗传算法结合到 RANS 流求解器中，以非设计攻角进行了优化。对于空腔优化，几何形状和下游吸力面由 16 个参数定义，升阻比被视为 14°攻角下的成本函数。数值解表明优化后的空腔会捕获涡流，从而推迟失速。由于 CFD 的不确定性，尤其是在非设计条件下，有必要评估优化腔体在各种攻角范围内的性能。本研究使用粒子图像测速 (PIV) 测量方法来评估优化腔体上改进的流动结构。两种型号的带腔和不带腔的翼型件由铝制成，安装在风速为 30 m/s 和横截面为 30 × 30 cm 2 的开放式喷射风洞的测试段内。PIV 在 7°–15° 攻角下测量翼型吸力侧的气流。两个翼型上测得的流场之间的比较表明，优化的空腔将失速角推迟了 3°。此外，空腔在攻角大于 9° 时增加了翼型后面的动量。这个角度之后，攻角的进一步增加增加了带空腔和不带空腔的翼型后面动量之间的差异。具有优化腔体的 Risø_B1_18 翼型可用作大迎角的风力涡轮机翼型，以增加失速角并减少非设计条件下的不稳定性和波动。图形摘要