An integrated method for lightweight design and additive manufacturing of UAV arms

Topology optimization and additive manufacturing (AM) have been widely applied to the lightweight design and fabrication of unmanned aerial vehicles (UAVs). However, existing topology optimization methods for UAVs typically assume isotropic materials, neglecting the anisotropy inherent in AM and the associated manufacturing precision constraints. This paper proposes a lightweight integrated method in MATLAB R2021a for the design and AM of UAV arms that simultaneously accounts for printing-induced anisotropy and minimum feature size constraints. A topology optimization model is proposed that uses nodal density and element printing angle as coupled design variables, and the corresponding sensitivity analysis is carried out. In the manufacturing phase, a contour-offset strategy is employed to generate printing paths for the optimized structures, achieving effective force transmission. The effects of manufacturing and optimization parameters on the design results are systematically investigated. The results show that, compared with the traditional optimization method, the compliance difference between the optimized structure obtained by the proposed method and the traditional method is only 0.46%. Furthermore, while ensuring manufacturability, printing efficiency is improved by approximately 69%. This approach establishes a unified design-to-manufacturing workflow, providing both a theoretical foundation and a practical pathway for the intelligent design and efficient fabrication of UAVs and other lightweight structural components.

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Publication Details

Journal
PLoS ONE
Published
2026-03-11
DOI
https://doi.org/10.1371/journal.pone.0344000
Primary Topic
Topology Optimization in Engineering
Type
article
Field-Weighted Citation Impact
0.00

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article

An integrated method for lightweight design and additive manufacturing of UAV arms

Wenwei Yang, Zhiru Liu, Yang Yu, Ruoyu Wang et al.
PLoS ONE
Topology Optimization in Engineering
article

An integrated method for lightweight design and additive manufacturing of UAV arms

Wenwei Yang, Zhiru Liu, Yang Yu, Ruoyu Wang, Xue Rao, Guoying Pang
article en

Abstract

Topology optimization and additive manufacturing (AM) have been widely applied to the lightweight design and fabrication of unmanned aerial vehicles (UAVs). However, existing topology optimization methods for UAVs typically assume isotropic materials, neglecting the anisotropy inherent in AM and the associated manufacturing precision constraints. This paper proposes a lightweight integrated method in MATLAB R2021a for the design and AM of UAV arms that simultaneously accounts for printing-induced anisotropy and minimum feature size constraints. A topology optimization model is proposed that uses nodal density and element printing angle as coupled design variables, and the corresponding sensitivity analysis is carried out. In the manufacturing phase, a contour-offset strategy is employed to generate printing paths for the optimized structures, achieving effective force transmission. The effects of manufacturing and optimization parameters on the design results are systematically investigated. The results show that, compared with the traditional optimization method, the compliance difference between the optimized structure obtained by the proposed method and the traditional method is only 0.46%. Furthermore, while ensuring manufacturability, printing efficiency is improved by approximately 69%. This approach establishes a unified design-to-manufacturing workflow, providing both a theoretical foundation and a practical pathway for the intelligent design and efficient fabrication of UAVs and other lightweight structural components.

PLoS ONEVol. 21(3)
Tianjin University (CN), Tianjin Academy of Fine Arts (CN), Tianjin Research Institute of Electric Science (China) (CN)
China Postdoctoral Science Foundation, Natural Science Foundation of Tianjin City, Tianjin Research Innovation Project for Postgraduate Students
Openalex Percentile: Top 25%
Topology Optimization in Engineering
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