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利用内凹型负泊松比结构提高缓冲垫的抗压性。

Enhancing the compression resistance of buffer cushions using an inner concave negative Poisson's ratio structure.

作者信息

Li Daizhou, Zhang Xiufen, Li Haibin

机构信息

College of Science, Inner Mongolia University of Technology, Hohhot, PR China.

Inner Mongolia Key Laboratory of Robotics and Intelligent Equipment Technology, Hohhot, PR China.

出版信息

PLoS One. 2025 Apr 4;20(4):e0321379. doi: 10.1371/journal.pone.0321379. eCollection 2025.

Abstract

To enhance the compression resistance of the existing buffer cushions, this paper developed a novel buffer cushion with an inner concave negative Poisson's ratio (NPR) structure. The structure parameters of buffer cushion were optimized based on orthogonal experimental design and theoretical analysis. Furthermore, the finite element models of the NPR cushion and a comparable hexagonal cushion were established. Then the quasi-static compression and dynamic impact compression simulations and compression experiments using a 3D printed model were conducted to analyze the compression resistance of the NPR cushion. The results showed that the developed NPR cushion exhibited good compressive properties under a uniform load of at most 47 MPa, and its deformation was 73.49% of the deformation of the hexagonal cushion, indicating an improvement in compressive resistance. In the simulation analysis, the stresses of the two buffer cushions in the case of dynamic impact compression were much larger than those in quasi-static compression. The consistency between simulations and experiments results validated the design's effectiveness in improving compression resistance, offering a valuable reference for the application of NPR structures in cushion design.

摘要

为提高现有缓冲垫的抗压性能,本文开发了一种具有内部凹形负泊松比(NPR)结构的新型缓冲垫。基于正交试验设计和理论分析对缓冲垫的结构参数进行了优化。此外,建立了NPR缓冲垫和可比的六边形缓冲垫的有限元模型。然后进行了准静态压缩和动态冲击压缩模拟以及使用3D打印模型的压缩实验,以分析NPR缓冲垫的抗压性能。结果表明,所开发的NPR缓冲垫在最高47 MPa的均匀载荷下表现出良好的压缩性能,其变形量为六边形缓冲垫变形量的73.49%,表明抗压性能有所提高。在模拟分析中,动态冲击压缩情况下两种缓冲垫的应力远大于准静态压缩时的应力。模拟结果与实验结果的一致性验证了该设计在提高抗压性能方面的有效性,为NPR结构在缓冲垫设计中的应用提供了有价值的参考。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/58e2/11970642/4b72c6a78be2/pone.0321379.g001.jpg

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