Meta model-based global design optimization and exploration method

被引：0

作者：

Guo, Zhen-Dong ^{[1
]}

Song, Li-Ming ^{[1
]}

Li, Jun ^{[1
]}

Li, Guo-Jun ^{[1
]}

Feng, Zhen-Ping ^{[1
]}

机构：

[1] School of Energy & Power Engineering, Xi'an Jiaotong University, Xi'an

来源：

Tuijin Jishu/Journal of Propulsion Technology | 2015年 / 36卷 / 02期

关键词：

Data mining; Global optimization; Kriging model; Meta-modeling;

D O I：

10.13675/j.cnki.tjjs.2015.02.007

中图分类号：

学科分类号：

摘要：

To solve computationally expensive black box problem such as turbomachinery design optimization in an effective way, a meta-model based global design optimization and exploration method named MBOE is proposed by integrating a meta-model based global optimization algorithm named MBGO and data mining techniques. The MBGO algorithm can usually achieve the global optimum with minimum function evaluations. Data mining techniques provide a way to get insights into the interactions among parameters and uncover the mechanism behind performance improvement of the optimal design. Using MBOE, 3D design optimization and data mining of Rotor 37 blade are finished. Isentropic efficiency of the optimal design is 1.74% higher than that of the reference design. And the computing time of MBGO is just 1/5 of that by applying a modified differential evolution algorithm as the optimizer. Meanwhile, data mining results indicate that the leading edge and the 3D stacking style have great effect on the blade aerodynamic performance. The performance improvement of the optimal design is benefited from the changes of related parameters. Therefore, the correctness and effectiveness of MBOE method is demonstrated. ©, 2015, Editorial Department of Journal of Propulsion Technology. All right reserved.

引用

页码：207 / 216

页数：9

共 20 条

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