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自适应Kriging近似模型及其在二维扩压器优化设计中的应用
引用本文:王红涛,竺晓程,杜朝辉.自适应Kriging近似模型及其在二维扩压器优化设计中的应用[J].计算力学学报,2011,28(1):15-19.
作者姓名:王红涛  竺晓程  杜朝辉
作者单位:上海交通大学,机械与动力工程学院,上海,200240
基金项目:国家自然科学基金(50576052);博士点基金(20060248036)资助项目.
摘    要:将均匀设计方法、CFD技术、Kriging近似模型及小生境微种群遗传算法相结合发展了一种自适应全局优化设计方法.优化过程中综合考虑Kriging模型的预测值与预测标准差,引入了EI(Expected Improvement)函数得到校正点,解决了采用近似模型最优策略得到校正点带来的局部收敛问题.分别采用该方法和小生境微...

关 键 词:扩压器  全局优化  Kriging模型  试验设计方法
收稿时间:2009/2/26 0:00:00
修稿时间:2009/10/25 0:00:00

Application of adaptive Kriging approximation model in two dimensional diffuser aerodynamic optimization design
WANG Hong-tao,ZHU Xiao-cheng and DU Zhao-hui.Application of adaptive Kriging approximation model in two dimensional diffuser aerodynamic optimization design[J].Chinese Journal of Computational Mechanics,2011,28(1):15-19.
Authors:WANG Hong-tao  ZHU Xiao-cheng and DU Zhao-hui
Institution:School of Mechanical and Power Engineering, Shanghai Jiaotong University , Shanghai 200240, China;School of Mechanical and Power Engineering, Shanghai Jiaotong University , Shanghai 200240, China;School of Mechanical and Power Engineering, Shanghai Jiaotong University , Shanghai 200240, China
Abstract:An adaptive global optimization method was developed coupled with uniform experimental design, CFD analysis, Kriging approximation model and niching micro genetic algorithm. In the optimization procedure, EI function was introduced to identify the next sampled point by considering the prediction and mean squared error of Kriging model to decrease the risk of trapping into the local optimum when the optimal strategy was used. The proposed method and niching micro genetic algorithm have been applied to the diffuser optimization design respectively, average static pressure recovery coefficient is selected as objective function and Nurbs curve is used to parameterize the geometric model. 8.5% improvement of average static pressure recovery coefficient is obtained and the result shows that the method is more effective than stochastic optimization algorithm.
Keywords:diffuser  global optimization  kriging model  experimental design method
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