An adaptive machine learning-based optimization method in the aerodynamic analysis of a finite wing under various cruise conditions

Zhang, Zilan; Ao, Yu; Li, Shaofan; Gu, Grace X.

doi:10.1016/j.taml.2023.100489

Theoretical and Applied Mechanics Letters

2024

DOI: 10.1016/j.taml.2023.100489

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An adaptive machine learning-based optimization method in the aerodynamic analysis of a finite wing under various cruise conditions

Zilan Zhang,

Yu Ao,

Shaofan Li

et al.

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2024

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Cited by 1 publication

References 26 publications

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Transferable machine learning model for the aerodynamic prediction of swept wings

Yang,

Li,

Zhang

et al. 2024

Physics of Fluids

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With their development, machine learning models can be used instead of computational fluid dynamics simulations to predict flow fields in aerodynamic optimization. However, it is difficult to construct a prediction model for swept wings with various planform geometries because too many samples are required to cover the parameter space. In the present paper, a new model framework is proposed to predict wing surface pressure and friction distributions with fewer samples. The distributed geometry parameters along spanwise are used as model inputs instead of the global planform parameters, and processors are designed to help the model better learn the local effect of geometric variation. The model is trained and tested on simple swept wings with single segment and linear twist distribution, where it outperforms the global input model by 57.6% in terms of lift coefficient prediction errors on small dataset sizes. The distributed input also enables the model to be transferred from single wings to more engineering-practical yet complex kink wings. After fine-tuning with a few samples, model accuracy for kink wings can be similar to that of simple wings, which proves the model for wings with complex planform geometries can be efficiently built with the proposed method.

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Transferable machine learning model for the aerodynamic prediction of swept wings

Yang,

Li,

Zhang

et al. 2024

Physics of Fluids

View full text Add to dashboard Cite

show abstract

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An adaptive machine learning-based optimization method in the aerodynamic analysis of a finite wing under various cruise conditions

Cited by 1 publication

References 26 publications

Transferable machine learning model for the aerodynamic prediction of swept wings

Transferable machine learning model for the aerodynamic prediction of swept wings

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