期刊文献+

基于代理模型的气动外形平面参数多目标匹配设计 被引量:11

Multi-object Aerodynamic Configuration Parameter Design Using Kriging Approximation
原文传递
导出
摘要 将Kriging代理模型和Pareto遗传算法引入气动外形平面参数匹配设计中,提出一种基于代理模型的多目标平面参数匹配设计方法。将拉丁超立方试验设计用于平面参数筛选,确定出参数匹配方案库;基于方案库的计算流体力学(CFD)分析结果构建Kriging气动代理模型;将Kriging模型替代CFD分析,用于气体布局参数匹配优化设计,提高了设计效率并保证了可信度;通过Pareto遗传算法优化解决多点设计要求下气动布局参数匹配问题,一次性给出参数匹配方案的最优解集,从Pareto前沿中根据设计偏向选择气动布局最佳匹配方案。以典型的双后掠布局平面参数多点匹配优化设计问题作为算例,研究结果表明:Kriging气动代理模型与实际CFD分析结果的误差均小于5%,满足精度要求;根据不同设计偏向,选择了3种参数匹配Pareto优化方案,与原样本方案相比超声速阻力减小6.0%~12.8%,跨声速升阻比增加0.01%~3.40%,证明了匹配设计方法的有效性;通过试验设计的Pareto分析与主、交互效应分析,获得了气动布局平面参数对气动性能影响的定量关系,能够为参数匹配设计提供依据。所提出的平面参数匹配设计方法可应用于其他常规与非常规气动布局型式。 By applying the Kriging model and the Pareto optimization method,a multi-object planform parameter design method based on approximation is proposed.The design of experiment is used to choose the configuration parameters and select configuration concept samples.The configuration samples are analyzed using the CFD,and the results are used to create the Kriging approximation model.Application of the Kriging model to parameter optimization can improve design efficiency and guarantee its precision.The Pareto multi-object genetic algorithm is used for parameter optimization,and the planform optimum results can be chosen in the Pareto front.A cranked-sweep configuration is selected as a design case.The design results indicate that Kriging approximation model can satisfy the requirement of precision with errors of less than 5%.Three planform optimums are chosen by different preferences in the Pareto front.Through optimization,the supersonic drag coefficient can be reduced by about 6.0%-12.8%,while the transonic lift to drag ratio can be increased by about 0.01%-3.40%.By Pareto of design of experiment,main effect and inter effect analysis,the quantitative relationship between the parameters and aerodynamic characteristics can be achieved.This method can be applied to other aerodynamic configurations including unconventional configurations.
出处 《航空学报》 EI CAS CSCD 北大核心 2010年第6期1141-1148,共8页 Acta Aeronautica et Astronautica Sinica
基金 国防预研基金
关键词 Pareto原则 试验设计 KRIGING模型 气动布局 参数匹配 Pareto principle design of experiment Kriging model aerodynamic configuration parameter matching
  • 相关文献

参考文献12

  • 1Pulliam T H, Nemec M, Holst T, et al. Comparison of evolutionary(genetic) algorithm and adjoint methods for multi-objective viscous airfoil optimizations [R]. AIAA- 2003-298, 2003.
  • 2Mason W H, Knill D L, Giunta A A. Getting the full benefits of CFD in conceptual design[R]. AIAA -1998 2531, 1998.
  • 3Lian Y S, Liou M S. Multiobjective optimization using coupled response surface model and evolutionary algorithm [J]. AIAAJournal, 2005, 43(6) :1316 -1325.
  • 4Ordaz I, Lee K H, Clark D M,et al. Aerodynamic optimization using physics-based response surface methodology for a multi-mission morphing unmanned combat air vehicle [R]. AIAA-2004-6336,2004.
  • 5Secanell M, Suleman A, Gamboa P. Design of a morphing airfoil for a light unmanned aerial vehicle using high fideli ty aerodynamics shape optimization [R]. AIAA 2005 1891, 2005.
  • 6熊俊涛,乔志德,韩忠华.基于响应面法的跨声速机翼气动优化设计[J].航空学报,2006,27(3):399-402. 被引量:56
  • 7穆雪峰,姚卫星,余雄庆,刘克龙,薛飞.多学科设计优化中常用代理模型的研究[J].计算力学学报,2005,22(5):608-612. 被引量:152
  • 8夏露,高正红,苏伟.Pareto遗传算法在气动外形优化中的应用[J].空气动力学学报,2007,25(2):194-198. 被引量:12
  • 9Kalyanmoy D, Pratap A, Agrawa S, et al. A fast and elitist multi-objective genetic algorithm: NSGA-II [J]. IEEE Transactions on Evolutionary Computation, 2002, 6 (2): 182- 197.
  • 10Koehler J R, Owen A B. Computer experiments[M] // Handbook of Statistics. New York: Elsevier Science, 1996: 261-308.

二级参考文献23

  • 1胡毓达.实用多目标规划[M].上海科学技术出版社,1990..
  • 2GOLOVIDOV, OLEG B, MASON, et al. Response Surface Approximations for Aerodynamic Parameters in High Speed Civil Transport Optimization[A]. Technical Report,Computer Science[DB/OL], Virginia Polytechnic Institute and State University. http://historical.ncstrl.org/tr/ps/vatechcs/TR-97-15.ps.
  • 3KNILL D L, GIUNTA A A, BAKER C A, et al. Response surface models combining linear and euler aerodynamics for supersonic transport design[J]. J Aircraft, 1999,36(1):75-86.
  • 4UNAL R, LEPSCH R A, MCMILLIN M. Response Surface Model Building and Multidisciplinary Optimization Using D-Optimal Designs[A]. Colle-ction of Technical Papers for 7th Annual AIAA/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization[C].1998,405-411.
  • 5JIN R, CHEN W, SIMPSON T W. Comparative studies of metamodeling techniques under multiple modeling criteria[J]. Journal of Structural and Multidisciplinary Optimization, 2001,23(1):1-13.
  • 6GIUNTA A A, DUDLEY J M, NARDUCCI R, et al. Noisy Aerodynamic Response and Smooth Approximations in HSCT Design[A]. Proceedings of the 5th AIAA/USAF/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization[C]. Panama City Beach, FL, AIAA Paper94-4376, 1994,1117-1128.
  • 7GIUNTA A A, WATSON L T. A Comparison of Approximation Modeling Techniques: Polynomial Versus Interpolating Models[A]. 7th AIAA/USAF/NASA/ISSMO Symposium on Multidiscipli-nary Analysis & Optimization[C]. St. Louis, MO, AIAA, September 2-4, 1998, 1:392-404.
  • 8SOREN N. Lophaven, Hans Bruun Nielsen, Jacob Sondergaard. Aspects of the Matlab Toolbox DACE[A]. Report IMM-REP-2002-12, Informatics and Mathematical Modeling[DB/OL],Technical Univer-sity of Denmark,2002. http://www.imm.dtu.dk/-hbn/dace/.
  • 9SOREN N. Lophaven, Hans Bruun Nielsen, Jacob Sondergaard. DACE A Matlab Kriging Toolbox[A].Report IMM -REP-2002-13,Informatics and Mathematical Modeling[DB/OL].Technical Univer-sity of Denmark, 2002. http://www.imm.dtu.dk/-hbn/dace/.
  • 10陈国良 王熙法 庄镇泉 王东生.遗传算法及其应用[M].北京:人民邮电出版社,1999..

共引文献215

同被引文献148

引证文献11

二级引证文献76

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部