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Scientific Publication Citing Dragonfly

Extrusion-based 3D printing concrete with coarse aggregate: Printability and direction-dependent mechanical performance

Yidong Chen (1), Yunsheng Zhang (1,2), Bo Pang (1), Zhiyong Liu (1), Guojian Liu (3)
Construction and Building Materials, 296, August 2021. DOI: 10.1016/j.conbuildmat.2021.123624


3DCP; Extrusion-based; Coarse aggregate; Printability; Direction-dependent strength; Voids; Interlayer area; X-CT; SEM


Concrete with coarse aggregate in the 3D concrete printing (3DCP) has broad prospects for high strength, low cost and shrinkage. In this study, an extrusion-based 3D printer was designed and utilized to print concrete with the largest aggregate size of 20 mm. Printable concrete with coarse aggregate was designed by different volume ratios of cement to aggregate (C/A). Then the effect of C/A on the printability and direction-dependent mechanical performance was investigated. X-ray micro-computed tomography (X-CT) was used to detect and analyze the voids distribution characteristics of printed specimens. Scanning electron microscope (SEM) investigations of microstructure at the interlayer area were conducted. Results indicated that the initial flowability of printable concrete should be within 178–200 mm, and the recommended printable C/A was within 0.35–0.60. The decrease of C/A improved the maximum printing height and mechanical performance but weakened the shape-stability of the multi-layer structure. X-CT results indicated that reducing excess slurry content caused by the decline of C/A decreased the compactness of the printed structure. The compressive strength and flexural strength of 3D printed specimens showed a direction-dependent characteristic, mainly related to the non-uniform distribution of voids revealed by X-CT. SEM images revealed the “micro-bridging” morphology in the interlayer area and proved that there were carbonation and structural weakening problems at the surface and surrounding of this area.

How Our Software Was Used

Dragonfly was used for image reconstruction and statistical analysis.

Author Affiliation

(1) School of Materials Science and Engineering, Southeast University, Nanjing 211189, China.
(2) School of Civil Engineering, Lanzhou University of Technology, Lanzhou 730050, China.
(3) School of Civil Engineering, Suzhou University of Science and Technology, Suzhou 215011, China.

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