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火箭弹气动学科代理模型构建方法研究
引用本文:赵良玉,杨树兴,佘浩平.火箭弹气动学科代理模型构建方法研究[J].固体火箭技术,2007,30(1):1-4,38.
作者姓名:赵良玉  杨树兴  佘浩平
作者单位:北京理工大学机电工程学院,北京,100081
基金项目:国防基础科研项目基金(K1305060614)
摘    要:针对火箭弹多学科优化体系中气动学科采用计算流体力学方法计算时间过长的问题,提出了一种综合运用CFD技术、试验设计技术、径向基函数神经网络技术构建火箭弹气动学科代理模型的方法,并对其流程进行了详细分析说明。通过算例分析,证明了该方法的可行性和有效性。该方法在保证一定精度前提下大大降低了火箭弹气动学科的计算周期。

关 键 词:多学科设计优化  代理模型  火箭弹  RBF神经网络
文章编号:1006-2793(2007)01-0001-04
收稿时间:2006-05-26
修稿时间:2006-05-262006-10-11

Research on constructing surrogate model of rocket aerodynamic discipline
ZHAO Liang-yu,YANG Shu-xing,SHE Hao-ping.Research on constructing surrogate model of rocket aerodynamic discipline[J].Journal of Solid Rocket Technology,2007,30(1):1-4,38.
Authors:ZHAO Liang-yu  YANG Shu-xing  SHE Hao-ping
Institution:School of Electromechanical Engineering,Beijing Institute of Technology,Beijing 100081 ,China
Abstract:Aiming at long calculation time when computational fluid dynamics method was used for optimization of rocket aerodynamic multidiscipline,a new method for constructing surrogate model for rocket aerodynamic discipline was put forward by means of computational fluid dynamics(CFD),experiment design and radial basis function(RBF) neural network techniques,and its flow chart was analyzed in detail.Through example analysis,the method was proven to be feasible and effective.Under the high-precision precondition,the RBF neural network surrogate modeling method can greatly reduce computational time.
Keywords:multidisciplinary design optimization  surrogate model  rocket  RBF neural network
本文献已被 CNKI 维普 万方数据 等数据库收录!
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