战斗机后体流场数值模拟与减阻优化设计

来源 :空气动力学学报 | 被引量 : 0次 | 上传用户:YAOGUOCHUN
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采用数值计算方法模拟零迎角跨声速来流下战斗机后体流场,并进行后体外形的减阻优化设计。通过数值求解二维轴对称Navier-Stokes方程、k-ωSST湍流模型和气体组分方程,研究战斗机后体绕流与尾喷流相互耦合的流场特性,对三种欠膨胀喷管压比下的喷流进行数值模拟,同时对比多组分气体喷流和理想气体喷流对后体阻力的影响。采用梯度法对轴对称后体外形进行减阻优化设计,提出一种优化设计加速算法,其基本思路是通过逐步增加设计控制点个数并根据外形曲率合理分布设计控制点的位置,从而改善梯度法的优化效率。计算结果发现,超声速喷流会在后体尾部附近形成复杂的波系结构;与组分气体喷流相比,采用理想气体作为喷流介质时的后体阻力系数略高;在跨声速来流状态下,后体阻力系数值随喷压比的增大而减小。优化结果显示,优化后的的后体阻力系数可以降低13%左右;与一次性均匀分布优化控制点的梯度法优化方法相比,采用提出的优化加速算法可以缩短优化计算时间40%左右,并且可以提高优化设计的精度。 The numerical simulation method is used to simulate the transonic speed of zero-angle of attack to shed the body fluid field after fighter jet and to optimize the drag reduction of the rear body shape. By numerical solution of the two-dimensional axisymmetric Navier-Stokes equations, k-ωSST turbulence model and gas component equations, the flow field characteristics of the rear body flow around the fighter jet and the tail jet flow were studied. The numerical simulation of the jet flow was carried out, and the influence of multi-component gas jet and ideal gas jet on the rear body resistance was compared. After axisymmetric body shape for drag reduction using a gradient optimization design method, an optimization design is proposed to accelerate the algorithm, the basic idea is to design and rational distribution of the position of curvature control points according to the shape designed by gradually increasing the number of control points, thereby improving the gradient Law of optimization efficiency. The results show that the supersonic jet forms a complex wave structure near the tail of the rear body. Compared with the component jet, the drag coefficient of the rear body is slightly higher when the ideal gas is used as the jet medium. State, the rear body resistance coefficient decreases with the increase of the pressure ratio. The results show that optimization, the rear body drag coefficient optimization can be reduced about 13%; compared with disposable uniform distribution gradient optimization method of optimizing control point, the proposed optimization algorithm can be accelerated to shorten the calculation time optimization about 40%, and You can improve the accuracy of the design.
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