首页|飞行器乘波前体/Bump型面优化设计方法研究

飞行器乘波前体/Bump型面优化设计方法研究

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飞行器前体和Bump型面是乘波体思想在飞行器部件设计中的两大经典案例,可有效提升飞行器总体气动性能,已经成为飞行器总体设计的核心技术.为寻求乘波前体和Bump型面的最优设计以提升飞行器设计效率,提出了一种可应用于乘波前体和Bump型面的优化设计方法.采用密切锥理论和圆锥绕流流场生成初始的乘波前体和Bump型面,并通过面元法快速预估气动性能;结合BP神经网络建立的代理模型和遗传算法NSGA-II对乘波前体和Bump型面快速优化;利用数据挖掘方法分析乘波前体和Bump型面的流动机理.优化后的乘波前体升阻比提升了25.6%,体积提升41.4%.Bump型面阻力系数减少10.9%,横向压力梯度增加12.1%.研究结果表明,提出的优化方法能够有效应用于乘波前体和Bump气动型面的设计优化,对飞行器整体气动性能的优化具有指导意义,在工程应用中具有重大潜力.
Research on Optimization Design Method of Waverider Forebody/Bump Profile of Aircraft
The waverider forebody and Bump profile of aircraft are two classic cases reflecting the waverider idea in aircraft component design.They can effectively improve the overall aerodynamic performance of aircraft and have become the core technology of aircraft overall design.In order to seek the optimal design of the waverider forebody and Bump profile to improve the efficiency of aircraft design,an optimization design method for the waverider forebody and Bump profile is proposed in this paper.The initial waverider forebody and Bump profile are generated by the osculating cone theory and conical flow field,and the aerodynamic performance is quickly estimated by the panel method.The surrogate model established by the back-propagation(BP)neural network and genetic algorithm NSGA-II are used to optimize the waverider forebody and Bump profile quickly.The data mining method is used to analyze the flow mechanism of the waverider forebody and Bump profile.The lift-to-drag ratio and volume of the optimized waverider forebody are increased by 25.6%and 41.4%,respectively.The drag coefficient of the Bump profile is decreased by 10.9%,and the lateral pressure gradient is increased by 12.1%.The results show that the proposed optimization method can be applied to the design optimization of the waverider forebody and Bump aerodynamic profile,which has guiding significance for the optimization of the overall aerodynamic performance of the aircraft and has great potential in engineering applications.

waverider forebodyBump profileNSGA-IIhypersonic velocityoptimization research

邱家林、黄俊、舒鹏、王庆凤、刘志勤、乔文友

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西南科技大学 计算机系,四川 绵阳 621000

西南科技大学 燃烧空气动力学研究中心,四川 绵阳 621000

乘波前体 Bump型面 NSGA-II 高超声速 优化研究

四川省自然科学基金四川省自然科学基金1912项目

2022NSFSC08942022NSFSC04462019-JCJQ-DA-001-057

2024

系统仿真学报
北京仿真中心 中国系统仿真学会

系统仿真学报

CSTPCD北大核心
影响因子:0.551
ISSN:1004-731X
年,卷(期):2024.36(3)
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