关键词: 子元建模；Kriging模型；全局优化；数据挖掘

Abstract: 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.

Key words: Meta-modeling；Kriging model；Global optimization；Data mining