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Nail-Planting to Enhance the Interface Bonding Strength in 3D Printed Concrete (2022-06)

10.1016/j.autcon.2022.104392

 Cao Xiangpeng, Yu Shiheng, Zheng Dapeng,  Cui Hongzhi
Journal Article - Automation in Construction, Vol. 141

Abstract

Weak adhesion between layers heavily declined the mechanical behavior of the 3D printed concrete. Six types of nails were inserted, screwed, and cast into the printable cementitious material to investigate the interfacial enhancement. The thread locking mechanism and nail planting were thoroughly studied via the pull-out, splitting, and computed tomography scanning tests. Flooring nails, screw nails, and self-tapping nails achieved promising pull-out strengths when inserted or screwed into the cast specimen and improved the layer bonding strength by 20.3%, 34.4%, and 38.2%, with one nail inserted, respectively; and the optimal inserted flooring nail density was found 0.3 nail/cm2 based on multi-nail inserting tests. The nail planting technique presented a promising and viable solution to improve the bonding strength between printed layers via mechanical thread locking. A hybrid manufacturing system of concrete printing and nail planting can be investigated and developed to fabricate 3D printed and nail reinforced structures.

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BibTeX
@article{cao_yu_zhen_cui.2022.NPtEtIBSi3PC,
  author            = "Xiangpeng Cao and Shiheng Yu and Dapeng Zheng and Hongzhi Cui",
  title             = "Nail-Planting to Enhance the Interface Bonding Strength in 3D Printed Concrete",
  doi               = "10.1016/j.autcon.2022.104392",
  year              = "2022",
  journal           = "Automation in Construction",
  volume            = "141",
}
Formatted Citation

X. Cao, S. Yu, D. Zheng and H. Cui, “Nail-Planting to Enhance the Interface Bonding Strength in 3D Printed Concrete”, Automation in Construction, vol. 141, 2022, doi: 10.1016/j.autcon.2022.104392.

Cao, Xiangpeng, Shiheng Yu, Dapeng Zheng, and Hongzhi Cui. “Nail-Planting to Enhance the Interface Bonding Strength in 3D Printed Concrete”. Automation in Construction 141 (2022). https://doi.org/10.1016/j.autcon.2022.104392.