Global Aero-Structural Optimization of Composite Forward-Swept Wings Considering Natural Laminar Flow

Forward-swept wings are more suitable for natural laminar flow than backward-swept wings. However, in order to reduce the difficulty of optimization, most aero-structural optimization studies of forward-swept wings do not consider the automatic laminar–turbulent transition, discrete variables, or large-scale constraints, which may result in undesirable optimization results. In this article, an efficient aero-structural optimization method for the composite forward-swept natural laminar flow (FSNLF) wing is proposed, which can solve MDO problems with those issues. Reynolds-averaged Navier–Stokes (RANS) equations coupled with the dual eN transition method are used to simulate subsonic viscous flows. A surrogate-based optimization (SBO) algorithm combining a discrete variable handling method is developed to solve the multidisciplinary design optimization (MDO) problem involving many discrete ply thickness variables of predefined angles (0°/±45°/90°). The Kreisselmeier–Steinhauser (KS) method is employed to handle large-scale geometric constraints, ply fraction constraints and material failure constraints. To verify the effectiveness of the proposed method, we perform the aero-structural optimization of an A320-class composite FSNLF wing. Results show that the proposed method offers great potential in the aero-structural optimization of the composite FSNLF wing. It can handle 32 discrete variables and 11,089 constraints, the drag coefficient and mass of the wing are reduced significantly, and the area of the laminar flow region on the wing upper surface is increased by 24.3% compared with the baseline.

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Publication Details

Journal
Aerospace
Published
2025-12-02
DOI
https://doi.org/10.3390/aerospace12121076
Primary Topic
Computational Fluid Dynamics and Aerodynamics
Type
article
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article

Global Aero-Structural Optimization of Composite Forward-Swept Wings Considering Natural Laminar Flow

Tao Wu, Bo-Wen Xiao, X.-J. Wang, Kai Wang et al.
Aerospace
Computational Fluid Dynamics and Aerodynamics
article

Global Aero-Structural Optimization of Composite Forward-Swept Wings Considering Natural Laminar Flow

Tao Wu, Bo-Wen Xiao, X.-J. Wang, Kai Wang, Jie Ding, Zhiyuan Shan, Xu Han
article en

Abstract

Forward-swept wings are more suitable for natural laminar flow than backward-swept wings. However, in order to reduce the difficulty of optimization, most aero-structural optimization studies of forward-swept wings do not consider the automatic laminar–turbulent transition, discrete variables, or large-scale constraints, which may result in undesirable optimization results. In this article, an efficient aero-structural optimization method for the composite forward-swept natural laminar flow (FSNLF) wing is proposed, which can solve MDO problems with those issues. Reynolds-averaged Navier–Stokes (RANS) equations coupled with the dual eN transition method are used to simulate subsonic viscous flows. A surrogate-based optimization (SBO) algorithm combining a discrete variable handling method is developed to solve the multidisciplinary design optimization (MDO) problem involving many discrete ply thickness variables of predefined angles (0°/±45°/90°). The Kreisselmeier–Steinhauser (KS) method is employed to handle large-scale geometric constraints, ply fraction constraints and material failure constraints. To verify the effectiveness of the proposed method, we perform the aero-structural optimization of an A320-class composite FSNLF wing. Results show that the proposed method offers great potential in the aero-structural optimization of the composite FSNLF wing. It can handle 32 discrete variables and 11,089 constraints, the drag coefficient and mass of the wing are reduced significantly, and the area of the laminar flow region on the wing upper surface is increased by 24.3% compared with the baseline.

AerospaceVol. 12(12)
China North Industries Group Corporation (China) (CN), Northwest Institute of Mechanical and Electrical Engineering (CN)
Openalex Percentile: Top 61%
Computational Fluid Dynamics and Aerodynamics
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