Abstract

Three-dimensional (3D) concrete printing is increasingly becoming popular because it provides a powerful platform for the fabrication of structural components in freeform architectural shapes. Although manufacturing technology and material property improvement are advancing rapidly, the development of methods to predict the structural capacity of printed elements is lagging. This paper presents an experimental and numerical investigation to predict the axial load capacity of a printed concrete wall module. The module geometry contains two parallel thin wall sections connected by an internal sine wave. The thin wall section reduces the concrete consumption, and the internal sine wave provides lateral stability during printing and in the hardened state. It is a popular pattern printed by many researchers and in some real constructions. Two wall module specimens with the prescribed geometry were 3D-printed and tested under compression. The maximum loads of 2,890 and 2,924 kN were obtained for the first and second wall specimens, respectively. Additionally, samples were taken from different locations of a printed prototype to identify printed material characteristics. These experimental characteristics were then introduced to a finite-element numerical model for predicting the structural performance of the printed wall module under compression load. The results showed that the experimental maximum load and stiffness have 1% and 5% differences with numerical outputs, respectively. Based on such a validated model, the failure modes are discussed, and an analytical method is proposed for predicting the axial capacity for the prescribed geometry.

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Data Availability Statement

Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.

Acknowledgments

The authors do acknowledge the support of Ph.D. students and lab technicians of Digital Construction and Smart Structures laboratories of Swinburne University. The generous support of Kia Rasekhi as the digital construction laboratory technician and Kevin Nievaart as the smart structure laboratory technician are also acknowledged.

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Go to Journal of Structural Engineering
Journal of Structural Engineering
Volume 150Issue 8August 2024

History

Received: Oct 19, 2022
Accepted: Jan 24, 2024
Published online: May 16, 2024
Published in print: Aug 1, 2024
Discussion open until: Oct 16, 2024

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Samira Bayatkashkooli [email protected]
Ph.D. Student, Dept. of Civil and Construction Engineering, Swinburne Univ. of Technology, Melbourne, VIC 3122, Australia (corresponding author). Email: [email protected]
Research Fellow, Dept. of Civil and Construction Engineering, Swinburne Univ. of Technology, Melbourne, VIC 3122, Australia. ORCID: https://orcid.org/0000-0002-1206-770X. Email: [email protected]
Professor, Dept. of Civil and Construction Engineering, Swinburne Univ. of Technology, Melbourne, VIC 3122, Australia. ORCID: https://orcid.org/0000-0001-7731-8656. Email: [email protected]
Jay Sanjayan [email protected]
Director, Center for Sustainable Infrastructure and Digital Construction, Swinburne Univ. of Technology, Melbourne, VIC 3122, Australia. Email: [email protected]
Javad Hashemi [email protected]
Senior Lecturer, Dept. of Civil and Construction Engineering, Swinburne Univ. of Technology, Melbourne, VIC 3122, Australia. Email: [email protected]

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