Automated Reinforcement during Large-Scale Additive Manufacturing: Structural Assessment of a Dual Approach

Author:

Ahmed Hassan1,Giwa Ilerioluwa1ORCID,Game Daniel1ORCID,Arce Gabriel2,Noorvand Hassan1ORCID,Hassan Marwa1,Kazemian Ali13ORCID

Affiliation:

1. Bert S Turner Department of Construction Management, Louisiana State University, Baton Rouge, LA 70803, USA

2. Virginia Transportation Research Council, Charlottesville, VA 22903, USA

3. Division of Electrical and Computer Engineering, Louisiana State University, Baton Rouge, LA 70803, USA

Abstract

Automated and seamless integration of reinforcement is one of the main unresolved challenges in large-scale additive construction. This study leverages a dual-reinforcement solution consisting of high-dosage steel fiber (up to 2.5% by volume) and short vertical reinforcements as a complementary reinforcement technique for 3D-printed elements. The mechanical performance of the printing material was characterized by measuring the compressive, flexural, and uniaxial tensile strengths of mold-cast specimens. Furthermore, the flexural performance of the plain and fiber-reinforced 3D-printed beams was evaluated in the three main loading directions (X, Y, and Z-directions in-plane). In addition, short vertical threaded reinforcements were inserted into the fiber-reinforced 3D-printed beams tested in the Z-direction. The experimental results revealed the superior flexural performance of the fiber-reinforced beams loaded in the longitudinal directions (X and Y). Moreover, the threaded reinforcement significantly increases the flexural strength and ductility of beams loaded along the interface, compared to the control. Overall, the proposed dual-reinforcement approach, which exhibited notably less porosity compared to the mold-cast counterpart, holds great potential as a reinforcement solution for 3D-printed structures without the need for manual operations.

Funder

Transportation Consortium of South-Central States (TranSET) university transportation center—US Department of Transportation

Publisher

MDPI AG

Reference65 articles.

1. Seyrfar, A., Ataei, H., and Osman, I. (2022). Automation and Robotics in the Architecture, Engineering, and Construction Industry, Springer.

2. Implications of Construction 4.0 to the workforce and organizational structures;Joss;Int. J. Constr. Manag.,2019

3. Khoshnevis, B. (1997, January 24–26). Contour crafting: A new rapid prototyping process. Proceedings of the International Conference on Rapid Prototyping, Chapel Hill, NC, USA.

4. Giwa, I., Moore, D., Fiske, M., and Kazemian, A. (2023). Earth and Space 2022: Space Exploration, Utilization, Engineering, and Construction in Extreme Environments—Selected Papers from the 18th Biennial International Conference on Engineering, Science, Construction, and Operations in Challenging Environments, Available online: https://ascelibrary.org/doi/10.1061/9780784484470.069.

5. Kazemian, A., Giwa, I., and Ekenel, M. (2023). Additive Manufacturing Design and Applications, ASM International.

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