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动力短舱多点气动优化设计OA

Multipoint Aerodynamic Design Optimization of Powered-on Nacelle

中文摘要英文摘要

跨声速发动机短舱的设计过程十分复杂,其设计往往需要在相互矛盾的设计要求中进行权衡.本文针对带动力短舱多点气动设计问题,采用类别形状函数变换法(CST)进行几何外形参数化,结合Kriging代理模型、Pareto遗传算法和松散式代理模型管理框架,构建了动力短舱多点优化设计平台.在巡航状态,优化目标是降低短舱外表面最大马赫数使短舱阻力减小,提高外流性能;在最大推力状态,优化目标是降低进气道最大马赫数使进气品质提升,提高内流性能.与初始短舱相比,优化设计结果在两个设计点性能上均有所提高,最大马赫数在巡航状态最多降低5%,而在最大推力状态最多降低10%.参数影响规律表明,短舱头部参数对外流和内流性能影响较大,且影响规律不同,应作为短舱综合优化设计的主要参数,并采用不同的优化设计策略.Pareto前沿阵面可以给出满足不同工程设计要求的最优方案.研究结果表明,本文建立的优化设计平台为动力短舱设计提供了有效工具,优化设计结果具有工程参考价值.

Design of the nacelle for a transonic engine is highly complicated and always a tradeoff between contradicting design objectives.In this paper,an optimization system for nacelle design is built up to improve the aerodynamic performance of a powered-on engine nacelle at two critical operation conditions.The class shape transformation(CST)method is developed for the parameterization of nacelle contour.The Pareto genetic algorithm(PGA)and the Kriging model are integrated by the loose surrogate management framework.At cruise,the minimization of external peak Mach number is the target function for total drag reduction and improving nacelle external performance.At maximum thrust condition,satisfied air supply should be ensured and the intake peak Mach number around throat is minimized to improve nacelle internal performance.Compared with the reference design,optimized nacelles obtain better performances with respect to both objectives,resulting in a peak Mach number reduction about 5%at cruise and 10%at full thrust condition.The parameter influence analysis indicates that the nacelle leading edge parameters have significant but different impact on nacelle internal and external performance.They should be chosen as the main design variables for integrated optimization design of the nacelle.The Pareto front can provide multiple choices for engineering applications.The results indicate that the optimization design system established in this paper provides an effective tool for the design of powered-on nacelles,and the optimization design results are of practical value.

顾文婷;马坤;韩杰

航空工业第一飞机设计研究院,陕西 西安 710089

动力短舱类别形状函数变换法Pareto遗传算法Kriging代理模型多点优化

powered-on nacelleCSTPGAKriging modelmultipoint optimization

《航空科学技术》 2024 (002)

23-30 / 8

航空科学基金(2020Z006003001)Aeronautical Science Foundation of China(2020Z006003001)

10.19452/j.issn1007-5453.2024.02.003

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