新概念融合升力体气动布局设计优化方法研究
Aerodynamic shape design and optimization method for a new blended lifting body
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摘要: 参考国内外高升阻比飞行器气动布局设计经验,针对进出空间飞行器的气动特性要求,开展跨速域高升阻比融合升力体气动布局(BLB)研究以适应进出空间飞行器的各种要求,在传统的翼/身外形的气动效率与纯升力体高容量效率之间寻求平衡。研究表明通过构建融合升力体数模,研究气动外形的系统参数化描述方法,选择设计变量及变化范围,研究优化算法,建立融合升力体气动布局设计及优化工具,开展融合升力体气动外形优化设计是一种值得深入探讨的研究方法。本文主要通过优化平台集成数模参数化程序、网格自动化及基于Euler方程的快速流场求解程序进行优化设计并对优化结果进行分析计算,发展了一种快速有效的气动布局优化设计方法,设计了初步满足设计要求的新型高升阻比融合升力体气动布局。设计的新布局能为再入飞行器气动布局设计提供参考,所发展的优化设计方法计算速度快,成本低,可以为走向工程实用化的复杂外形气动布局优化设计打下技术基础。Abstract: Taking the references of the high lift-to-drag ratio vehicle aerodynamic shape design experiences, aimed at the aerodynamic performance requirements of the reenter vehicle, a blended lifting body aerodynamic shape with high lift-to-drag ratio is investigated to fit the various requirements of the reentry vehicle, and to quest a balance between the aerodynamic performance of the traditional wing/body shape and the high cubage efficiency of lifting body. The prophase research shows that it is an advisable method to develop the blended lifting body aerodynamic shape optimization method by building the blended lifting body model, researching the parameterization method for the blended lifting body aerodynamic shape, selecting the design variables and their range, researching the optimization algorithm, building the blended lifting body aerodynamic shape design and optimization tool. In this paper, the optimization process is proposed by integrating the geometry dimensions parameterization program, the automatic grid generation technique and the fast aerodynamic numerical calculation program based on Euler equations. A fast aerodynamic shape optimization method is developed, and the optimization result is obtained and analyzed. A new blended lifting body shape with high lift-to-drag ratio is designed. The new shape provides an useful reference for the reentry vehicle design, and the optimization method has obvious advantages in computing speed and cost, and lays a technique foundation for the practical complex aerodynamic shape optimization.