摘要
针对样本数据少、信息缺乏的工程问题,研究了一种风机翼型气动性能区间的不确定性优化方法.通过建立区间模型非概率可靠性指标,在Kriging近似模型基础上,构建了稳健性优化模型.并采用了双重优化求解策略进行求解,以提高优化效率.为了提高叶型造型的拟合精度,采用五项多项式方法对翼型各截面进行参数化建模.通过和试验结果进行对比可知,该方法可满足风机气动性能优化精度要求.该方法为风机气动性能优化提供了新的途径,为轨道交通风机系统节能减排的市场实用化奠定了基础.
In view of the insufficient samples and information of engineering problem, an uncertain optimization design for aerodynamic performance of fan wing based on interval and robustness was studied. Based on the reliability index of interval variables, a robust optimization model was constructed on the basis of the mathematical model of Kriging approximate function, and the dual optimization method is used to solve the optimization problem in order to improve optimization efficiency. In order to improve the fitting precision of the leaf shape modeling, five polynomial methods were applied to establish the parameters of the airfoil model.The problem of insufficient sample data of fan blade parameters was solved effectively, and the results showed that the method could meet the requirement of accuracy of fan performance. A new approach was provided to fan aerodynamic performance optimization,the paper paved the way for the energy-saving emission reduction market.
出处
《中国科学：技术科学》
EI
CSCD
北大核心
2017年第9期955-964,共10页
Scientia Sinica(Technologica)
基金
国家自然科学基金项目(批准号:E050601)
湖南省科技计划重点项目(编号:2015CK3021)资助
关键词
风机
区间模型
不确定性优化
翼型气动
轨道列车
fan
interval model
uncertain optimization
airfoil aerodynamic
railway train
