Monitoring Strain Using Digital Image Correlation During Compressive and Tensile Loading (2022-06)¶
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Contribution - Proceedings of the 3rd RILEM International Conference on Concrete and Digital Fabrication, pp. 324-329
Abstract
3D concrete printing sparks over the past few years the interest of researchers invested in concrete Digital Fabrication. Whilemany processing issues have already been overcome to a large extent, in-depth understanding of the materials behaviour remains a challenge, especially for high yield stress materials deposited using the so-called infinite brick strategy. The highly non-linear behaviour of this kind of material enforces the need to describe the mechanical behaviour for large deformation analysis, especially because this ability to be deformed is often overcome during the printing process leading to cracks initiation and growth. This study proposes to focus on the assessment of critical strain of fresh material undergoing compression and tension. It is crucial to keep compressive and tensile strain under critical values in order to avoid possible buildability and filament tearing issues (low radius of curvature along the printing path, bending induced by deposition, control of printing speed…). Considering the inability of most of firm printable cement-based mix designs to be plastically deformed without cracking, this work proposes to monitor material deformation for large deformation using Digital Image Correlation (DIC) during mechanical testing. Such investigation is required to fully and accurately describe the elasto-viscoplastic behaviour of the material. A comparison of strain, engineering strain and DIC computed strain is proposed and the limit of validity ofcommon assumptions used for tests data analysis will be discussed. Finally, effects of Viscosity Modifying Admixtures (VMA) on critical shear strain will be investigated to assess to what extent this one could be increased by VMA addition: the improvement of the material ability to be deformed before breaking will allow to compute influence of viscous properties of high yield stress materials more accurately.
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3 References
- Jacquet Yohan, Perrot Arnaud, Picandet Vincent (2020-11)
Assessment of Asymmetrical Rheological Behavior of Cementitious Material for 3D Printing Application - Jacquet Yohan, Picandet Vincent, Rangeard Damien, Perrot Arnaud (2020-12)
Gravity-Induced Flow to Characterize Rheological Properties of Printable Cement-Based Materials - Mechtcherine Viktor, Bos Freek, Perrot Arnaud, Silva Wilson et al. (2020-03)
Extrusion-Based Additive Manufacturing with Cement-Based Materials:
Production Steps, Processes, and Their Underlying Physics
1 Citations
BibTeX
@inproceedings{jacq_perr_pica.2022.MSUDICDCaTL,
author = "Yohan Jacquet and Arnaud Perrot and Vincent Picandet",
title = "Monitoring Strain Using Digital Image Correlation During Compressive and Tensile Loading: Assessment of Critical Strain of Cement-Based Materials Containing VMA",
doi = "10.1007/978-3-031-06116-5_48",
year = "2022",
volume = "37",
pages = "324--329",
booktitle = "Proceedings of the 3rd RILEM International Conference on Concrete and Digital Fabrication: Digital Concrete 2022",
editor = "Richard A. Buswell and Ana Blanco and Sergio Cavalaro and Peter Kinnell",
}
Formatted Citation
Y. Jacquet, A. Perrot and V. Picandet, “Monitoring Strain Using Digital Image Correlation During Compressive and Tensile Loading: Assessment of Critical Strain of Cement-Based Materials Containing VMA”, in Proceedings of the 3rd RILEM International Conference on Concrete and Digital Fabrication: Digital Concrete 2022, 2022, vol. 37, pp. 324–329. doi: 10.1007/978-3-031-06116-5_48.
Jacquet, Yohan, Arnaud Perrot, and Vincent Picandet. “Monitoring Strain Using Digital Image Correlation During Compressive and Tensile Loading: Assessment of Critical Strain of Cement-Based Materials Containing VMA”. In Proceedings of the 3rd RILEM International Conference on Concrete and Digital Fabrication: Digital Concrete 2022, edited by Richard A. Buswell, Ana Blanco, Sergio Cavalaro, and Peter Kinnell, 37:324–29, 2022. https://doi.org/10.1007/978-3-031-06116-5_48.