4.6 Article

Compressive property and shape memory effect of 3D printed continuous ramie fiber reinforced biocomposite corrugated structures

期刊

SMART MATERIALS AND STRUCTURES
卷 31, 期 12, 页码 -

出版社

IOP Publishing Ltd
DOI: 10.1088/1361-665X/ac95e4

关键词

3D printing; continuous ramie fiber; corrugated structure; shape memory

资金

  1. National Natural Science Foundation of China [51905555]
  2. Hu-Xiang Youth Talent Program [2018RS3002, 2020RC3009]
  3. Innovation-Driven Project of Central South University [2019CX017]

向作者/读者索取更多资源

This study investigated the compression behaviors of 3D printed continuous ramie fiber reinforced biocomposite corrugated structures. The results showed that the compression property and energy absorption capacity of the structures increased with decreasing fiber volume fraction and the addition of continuous ramie yarn. The inverted trapezoid cell shape corrugated structures outperformed other cell shapes in compression strength and specific energy absorption. An analytical model for the compression strength of these structures was derived and showed good agreement with experimental measurements. Additionally, the study proposed a continuous natural fiber reinforced composite structure for shape memory.
The present work aimed to study the quasi-static compression behaviors of 3D printed continuous ramie fiber reinforced biocomposite corrugated structures (CFCSs) with excellent shape memory effects. The in-plane compression test was conducted to evaluate the effects of cell shapes, fiber volume fraction (f (v)) and addition of fiber on the compression behaviors and energy absorption (EA) characteristics of the corrugated structures. The results showed that the compression property and EA capacity of the 3D printed CFCSs increased with decreasing f (v) and the addition of continuous ramie yarn. The 3D printed continuous ramie fiber reinforced biocomposite with inverted trapezoid cell shape corrugated structures (CFITCSs) outperformed other cell shapes in the compression strength and specific EA. The analytical model for the in-plane compression strength of CFITCSs was derived, and predictions were in good agreement with measurements. In addition, continuous natural fiber reinforced composite structure for shape memory was proposed for the first time. The shape recovery testing results demonstrated that 3D printed CFCSs had the potential to be a key element of lightweight programmable smart systems.

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