基于代理模型的大型民机机翼气动优化设计

Translated title of the contribution: Aerodynamic optimization design of large civil aircraft wings using surrogate-based model

Zhonghua Han, Yu Zhang, Chenzhou Xu, Kai Wang, Mengmeng Wu, Zhen Zhu, Wenping Song

Research output: Contribution to journalArticlepeer-review

30 Scopus citations

Abstract

Advanced methods of aerodynamic shape optimization are playing an increasingly important role in improving performance and saving cost for the design of a large transport aircraft. In this article, the design principles of the modern large transport aircraft wing, from the perspective of an aerodynamicist, are presented. Using the surrogate-based approach, an efficient multi-round aerodynamic shape optimization for engineering applications is proposed. The proposed method is verified by test cases using an analytical test function, an airfoil design and an aerodynamic shape optimization of wing-body configuration. Then, the aerodynamic shape optimization for supercritical wing of a dual-aisle large transport aircraft is exercised by combining the proposed method with the method of directly modifying the shape (drawing on the experience of an aerodynamic designer). A comprehensive evaluation of aerodynamic performances of the optimal wing is conducted by using different Reynolds-averaged Navier-Stokes (RANS) equations flow solvers. The results show that the proposed method is feasible and effective for aerodynamic shape optimization for complex aircraft configurations, with good capability of constraints handling and global optimization. This study shows that the proposed optimization design method is applicable to engineering aerodynamic design of the supercritical wing of a wide-body transport aircraft.

Translated title of the contributionAerodynamic optimization design of large civil aircraft wings using surrogate-based model
Original languageChinese (Traditional)
Article number522398
JournalHangkong Xuebao/Acta Aeronautica et Astronautica Sinica
Volume40
Issue number1
DOIs
StatePublished - 25 Jan 2019

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