Yidong Chen (1) (2), Yunsheng Zhang (1) (2) (3), Bo Pang (4), Dafu Wang (1) (2), Zhiyong Liu (1) (2), Guojian Liu (5)
Materials and Structures. (5 April 2022). DOI: https://doi.org/10.1617/s11527-022-01943-7

Keywords

3D concrete printing, fresh properties, mechanical performance, fiber orientation, anisotropy

Abstract

In this study, the first insight into the extrusion-based 3D printed steel fiber reinforced concrete with 5–20 mm coarse aggregate (3DPSFRC) is presented. The fresh properties and mechanical performance of 0%, 1% and 2% fiber content 3DPSFRC were investigated and compared with those of the cast. Through the deep-learning segmentation method, the centerlines of steel fibers in the X-ray micro-computed tomography image sequence are extracted and 3D analyzed. The orientational distribution coefficients were introduced to quantitatively indicate the degree of steel fiber inclination in the printing (θ) and stacking directions (γ) inside the 3DPSFRC. Results indicate that the flowability of 3DPSFRC was decreased due to the presence of steel fibers compared with plain concrete. The enhancement effect of steel fiber on the compressive, flexural, and axial tensile strength (up to 73.24 MPa, 8.71 MPa, and 7.58 MPa, respectively) and post-peak toughness of 3DPSFRC is remarkable. The weakening of orientational distribution coefficients and the partial divergence distribution of steel fibers are related to the presence of coarse aggregate. Further, the anisotropy of 3DPSFRC in the compressive and flexural tests is weakened owing to the changes in the fiber orientational distribution after the steel fiber content increases.

How Our Software Was Used

The centerlines of steel fibers in the X-CT image sequence were extracted using Dragonfly’s Deep Learning Tool and then three-dimensional orientational distribution statistics and coefficients were analyzed. The quantitative analysis of steel fiber orientation was processed by the statistical properties of phi (φ) and theta (θ) angles of individual steel fibers in the multi-ROI.

Author Affiliation

(1) School of Materials Science and Engineering, Southeast University, Nanjing, 211189, China
(2) Collaborative Innovation Center for Advanced Civil Engineering Materials, Nanjing, 211189, China
(3) School of Civil Engineering, Lanzhou University of Technology, Lanzhou, 730050, China
(4) Department of Civil Engineering, Qingdao University of Technology, Qingdao, 266033, China
(5) School of Civil Engineering, Suzhou University of Science and Technology, Suzhou, 215011, China