Integrated aerodynamic optimization of wing/nacelle based on Gaussian process regression

被引：0
|
作者：
Ji T.-W. [1 ]
Mo S.-C. [1 ]
Xie F.-F. [1 ]
Zhang X.-S. [1 ]
Jiang Y.-Y. [1 ]
Zheng Y. [1 ]
机构：
[1] School of Aeronautics and Astronautics, Zhengjiang University, Hangzhou
来源：
Zhejiang Daxue Xuebao (Gongxue Ban)/Journal of Zhejiang University (Engineering Science) | 2023年 / 57卷 / 03期
关键词：
aerodynamic optimization design; Bayesian optimization (BO); Gaussian process regression (GPR); parametric modeling; wing/nacelle;
D O I：
10.3785/j.issn.1008-973X.2023.03.022
中图分类号：
学科分类号：
摘要：
A new optimization design method based on Gaussian process regression (GPR) model was proposed to resolve the high-dimensional nonlinear optimization problem of integrated aerodynamic design of wing/nacelle. The geometric parametric modeling of the airfoils in the integrated configuration of wing/nacelle was realized by the class and shape transformation (CST) method. The deformation of the integrated configuration of wing/nacelle was achieved by controlling the wing shape parameters, the nacelle shape parameters and the nacelle installation parameters. The parametric modeling process included 50 design parameters in total. The GPR model was used to construct a surrogate model between the design parameters and the aerodynamics performance of the integrated wing/nacelle geometry. Bayesian optimization (BO) algorithm was used to realize the self-update of the surrogate model and the acquisition of the optimal aerodynamic shape. Results showed that the drag coefficient of the integrated configuration was reduced by 10.95% after the optimization. The flow field analysis shows that the optimization of the wing shape and the nacelle shape improves the surface flow field structure, and the optimization of the nacelle’s installation position reduces the aerodynamic interference between wing and nacelle. © 2023 Zhejiang University. All rights reserved.
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页码：632 / 642
页数：10
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