Efficient surrogate-based aerodynamic design optimization method with adaptive design space expansion

WANG Chao; GAO Zhenghong; ZHANG Wei; XIA Lu; HUANG Jiangtao

doi:10.7527/S1000-6893.2018.21745

ACTA AERONAUTICAET ASTRONAUTICA SINICA >

2018 , Vol. 39 >Issue 7: 121745 - 121745

DOI: https://doi.org/10.7527/S1000-6893.2018.21745

Fluid Mechanics and Flight Mechanics

Efficient surrogate-based aerodynamic design optimization method with adaptive design space expansion

WANG Chao ,
GAO Zhenghong ,
ZHANG Wei ,
XIA Lu ,
HUANG Jiangtao

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1. School of Aeronautics, Northwestern Polytechnical University, Xi'an 710072, China;
2. Computational Aerodynamics Institute, China Aerodynamic Research and Development Center, Mianyang 621000, China

Received date: 2017-09-15

Revised date: 2018-04-17

Online published: 2018-07-27

Supported by

National Natural Science Foundation of China (11372254,11402288)

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Abstract

The infill criterion and design space construction in Kriging-based aerodynamic shape optimization are studied in this paper. A hybrid infill method is proposed, which combines the Expected Improvement (EI) criterion and the Minimum Prediction (MP) criterion using an EI threshold. Global exploration is first implemented by the IE criterion, and local exploitation is then implemented by the MP criterion. Consequently, the convergence rate of Efficient Global Optimization (EGO) is accelerated in a certain design space. To find the global optimum in aerodynamic shape optimization, expansion of the design variable range and multi-round method are employed. Influence of the variable range on the size of design space and density of samples are discussed. To improve the efficiency of samples, an adaptive design space expansion method is proposed. In this method, the design space is dynamic and the range of design variable is expanded in potential dimensions. Accordingly, the samples are allocated efficiently through adaptive expansion of design space boundaries. ADODG airfoil optimization cases show that the adaptive design space expansion method has remarkable superiority over the conventional fixed design space method.

Key words： Kriging model; efficient global optimization; aerodynamic optimization; hybrid infill method; adaptive design space

Cite this article

WANG Chao , GAO Zhenghong , ZHANG Wei , XIA Lu , HUANG Jiangtao . Efficient surrogate-based aerodynamic design optimization method with adaptive design space expansion[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2018 , 39(7) : 121745 -121745 . DOI: 10.7527/S1000-6893.2018.21745

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