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Efficient aero-structure coupled wing optimization using decomposition and adaptive metamodeling techniques

delete2019-12-01
delete8
PRE
AI
龙
龙腾 (Teng Long)
Y
Yufei Wu
王
王祝 (Zhu Wang) *
Y
Yifan Tang
D
Di Wu
于勇 封面图
于勇 (Yong Yu)
DOI:10.1016/j.ast.2019.105496delete
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摘要

摘要

En 中文
This paper proposes an efficient decomposition-based optimization framework using adaptive metamodeling for expensive aero-structure coupled wing optimization problems. First, high-fidelity aero-structure coupled analysis method is presented through spatial interpolations of distributed aerodynamic loads and structural deformation. The proposed optimization framework decomposes the original complex coupled optimization problem into 2-D airfoil optimization (i.e., Stage-I) and 3-D wing optimization (i.e., Stage-II) to alleviate the expensive computational costs. In Stage-II, a two-level optimization strategy is tailored to further decompose the 3-D wing optimization into system-level and subsystem-level for dimension reduction. An adaptive response surface method using intelligent space exploration strategy is used to perform optimization tasks involving CFD simulations (i.e., 2-D airfoil optimization and system-level optimization in Stage-II), while sequential quadratic programming is employed to optimize the massive subsystem structure sizing variables. The effectiveness of two-level optimization strategy is validated on a numerical testing problem and a simplified wing optimization case. Finally, the developed models and proposed methods are successfully applied to aero-structure coupled optimization of a high aspect ratio wing. The optimization results demonstrate the effectiveness of the developed aero-structural analysis models and efficiency of the proposed optimization methods. (C) 2019 Elsevier Masson SAS. All rights reserved.
Keyword:
Aero-structure coupled optimization
Wing optimization
Decomposition
Adaptive metamodeling
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期刊

Aerospace Science and Technology 封面图
Aerospace Science and Technology
IF:
5.8
论文数:
1.0W
被引数:
3.0W

机构

S
Simon Fraser University
学者数:
1.0W
论文数: 1.0W
被引数: 1.4W
B
beijing institute of technology
学者数:
5.5W
论文数: 4.0W
被引数: 63
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