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以跨声速机翼设计中权衡气动性能和总体设计要求的工程应用为出发点,在保证机翼结构重量和容积不变的约束下,提出了平面形状优化与剖面翼型优化结合的两步优化设计策略。应用神经网络和遗传算法,建立了相应的设计方法。采用两步优化方法进行跨声速机翼设计,第一步设计中,通过平面形状优化,增大机翼展弦比、减小诱导阻力是机翼气动性能改善的主要原因,但由于结构重量约束,平面形状变化不大,对机翼气动性能改善有限;第二步设计中,以第一步设计所优化的机翼平面形状为基础,并以机翼容积为约束,通过机翼剖面翼型优化,弱化较大马赫数下的激波、减小激波阻力是机翼气动性能改善的主要原因。经过这两步优化设计,机翼在两个设计点下的升阻比分别提高了3.02%和9.96%,阻力发散马赫数由0.854 0推迟到0.865 3,表明两步优化设计方法适合于工程应用。在无结构重量和容积约束下,采用单纯气动最优的平面形状和剖面翼型优化两种设计方法均可明显改善机翼气动性能,但不能满足机翼结构重量和容积不变的设计要求。
Based on the engineering application of balancing aerodynamic performance and overall design requirements in transonic wing design, a two-step optimization design combining planar shape optimization and profile airfoil optimization is proposed under the constraint of the weight and volume of the wing structure. Strategy. Application of neural networks and genetic algorithms, the establishment of the corresponding design method. In the first step, two-step optimization method is used to design the transonic wing. In the first step, the optimization of plane shape, increasing the aspect ratio of the wing and reducing the induced resistance are the main reasons for improving the aerodynamic performance of the wing. However, due to the structural weight constraint , Little change in the shape of the plane, to improve the aerodynamic performance of the wing is limited; the second step of the design, based on the plane shape of the wing optimized in the first step design, and wing-shaped airfoil Optimizing and weakening the shock wave at larger Mach number and reducing the shock resistance are the main reasons for improving the aerodynamic performance of the wing. After these two-step optimization design, the drag-and-drag ratio of the wing at both design points increased by 3.02% and 9.96% respectively, and the resistance divergence Mach number was delayed from 0.854 0 to 0.865 3, indicating that the two-step optimization design method is suitable for engineering application . Under the condition of no structural weight and volume constraints, both aerodynamic optimum planar shape and profiled airfoil optimization can significantly improve the aerodynamic performance of the wing, but can not meet the design requirements of the wing structure weight and volume.