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Multi-objective optimization of arc star honeycomb and bidirectional reentrant honeycomb using NSGA-II

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Abstract

In this paper, the multi-objective optimization design of arc star honeycomb (ASH) and bi-directional reentrant honeycomb (BRH) is carried out by Python script to improve Young's modulus based on the lightweight of the honeycomb. A large number of models of different structural parameters are established by the Python script and analyzed by the finite element method, and then the response surface model (RSM) is established according to the results of finite element analysis. On this basis, the non-dominated sorting genetic algorithm (NSGA-II) and RSM are combined to perform multi-objective optimization of the 2D and 3D configurations of the two types of honeycomb, and the optimal set of parameters is selected by comparing the individual fitness values. The results show that after multi-objective optimization, Young's modulus of the ASH and BRH is enhanced in both 2D and 3D configurations with the smallest possible mass. In addition, the ASH has performance advantages over the BRH in 2D configuration, and BRH is better in 3D configuration. It can also be observed that the ASH and BRH have Poisson ratio adjustable properties. The results also show that this multi-objective optimization method can effectively save the analysis and calculation time. The lightweight, high-strength metamaterial is expected to be used in key fields such as aerospace.

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The data that support the findings of this study are available on request from the corresponding author.

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Funding

The funding was provided by the Special Project for the Central Government to Guide Local Scientific and Technological Development of Hebei Province (Grand No. 226Z2201G) and National Natural Science Foundation of China (Grand No. 11702079).

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  1. School of Mechanical Engineering, Hebei University of Technology, Xiping Road No. 5340, Beichen District, Tianjin, 300401, People’s Republic of China

    Chen-Yu Zhao & Hai-Tao Liu

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  1. Chen-Yu Zhao
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  2. Hai-Tao Liu
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Zhao, CY., Liu, HT. Multi-objective optimization of arc star honeycomb and bidirectional reentrant honeycomb using NSGA-II. Int J Mech Mater Des 19, 375–389 (2023). https://doi.org/10.1007/s10999-022-09628-3

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