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Tradeoff Analysis of Aerodynamic Wing Design for RLV

机译:RLV气动翼设计的权衡分析

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摘要

The wing shape of flyback booster for a Two-Stage-To-Orbit reusable launch vehicle has been optimized considering four objectives. The objectives are to minimize the shift of aerodynamic center between supersonic and transonic conditions, transonic pitching moment and transonic drag coefficient, as well as to maximize subsonic lift coefficient. The three-dimensional Reynolds-averaged Navier-Stokes computation using the modified Spalart-Allmaras one-equation model is used in aerodynamic evaluation accounting for possible flow separations. Adaptive range multi-objective genetic algorithm is used for the present study because tradeoff can be obtained using a smaller number of individuals than conventional multi-objective genetic algorithms. Consequently, four-objective optimization has produced 102 non-dominated solutions, which represent tradeoff information among four objective functions. Moreover, Self-Organizing Maps have been used to analyze the present non-dominated solutions and to visualize tradeoffs and influence of design variables to the four objectives. Self-Organizing Maps contoured by the four objective functions and design variables are found to visualize tradeoffs and effects of each design variable.
机译:考虑到四个目标,已经对两阶段轨道可重复使用运载火箭的反激式助推器的翼形进行了优化。目的是最小化在超音速和跨音速状态之间的空气动力学中心的偏移,跨音速俯仰力矩和跨音速阻力系数,以及最大化亚音速升力系数。使用改进的Spalart-Allmaras一方程模型的三维雷诺平均Navier-Stokes计算在空气动力学评估中考虑了可能的气流分离。自适应范围多目标遗传算法用于本研究,因为与常规的多目标遗传算法相比,可以使用更少的个体获得权衡。因此,四目标优化产生了102个非支配解,它们代表了四个目标函数之间的折衷信息。此外,自组织映射已用于分析当前的非主导解决方案,并可视化权衡和设计变量对四个目标的影响。发现了由四个目标函数和设计变量绘制轮廓的自组织图,以可视化每个设计变量的权衡和效果。

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