Development of robotic sprayable self-sensing cementitious material for smart structural health monitoring
Self-sensing cementitious materials are critical to smart structural health monitoring with the piezoresistivity as an indicator for internal stress and cracks in the structure, which have been frequently utilized as functional coatings in engineering practices. To facilitate the automatic deploymen...
| Main Authors: | , , , , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/179449 |
| _version_ | 1826117220907876352 |
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| author | Lu, Bing Wang, Lining Wang, Xiangyu Tan, Ming Jen Li, Holden King Ho Wong, Teck Neng |
| author2 | School of Mechanical and Aerospace Engineering |
| author_facet | School of Mechanical and Aerospace Engineering Lu, Bing Wang, Lining Wang, Xiangyu Tan, Ming Jen Li, Holden King Ho Wong, Teck Neng |
| author_sort | Lu, Bing |
| collection | NTU |
| description | Self-sensing cementitious materials are critical to smart structural health monitoring with the piezoresistivity as an indicator for internal stress and cracks in the structure, which have been frequently utilized as functional coatings in engineering practices. To facilitate the automatic deployment of self-sensing cementitious materials, the compatibility with robotic spraying has been systematically investigated in this study. Pre- and post-spraying evaluations have been conducted for the mixtures with carbon fibers at different dosages, including rheology, tackiness, compressive strengths, and electromechanical responses. On this basis, the addition of 0.4 vol.% carbon fiber was confirmed as the optimal dosage with both competent spraying performance and self-sensing function in the corresponding mixture. Furthermore, the porosity characteristics and fiber agglomeration of the designed mixtures were quantitatively assessed by micro computed tomography (micro-CT), which suggested their relationship to the mechanical and self-sensing properties. Apart from the structural application potential of the developed self-sensing mixture, this study also provides detailed guidance for the optimization of other value-added robotic sprayable cementitious materials. |
| first_indexed | 2024-10-01T04:23:44Z |
| format | Journal Article |
| id | ntu-10356/179449 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T04:23:44Z |
| publishDate | 2024 |
| record_format | dspace |
| spelling | ntu-10356/1794492024-07-31T07:35:24Z Development of robotic sprayable self-sensing cementitious material for smart structural health monitoring Lu, Bing Wang, Lining Wang, Xiangyu Tan, Ming Jen Li, Holden King Ho Wong, Teck Neng School of Mechanical and Aerospace Engineering Singapore Centre for 3D Printing Engineering Robotic spraying Self-sensing Self-sensing cementitious materials are critical to smart structural health monitoring with the piezoresistivity as an indicator for internal stress and cracks in the structure, which have been frequently utilized as functional coatings in engineering practices. To facilitate the automatic deployment of self-sensing cementitious materials, the compatibility with robotic spraying has been systematically investigated in this study. Pre- and post-spraying evaluations have been conducted for the mixtures with carbon fibers at different dosages, including rheology, tackiness, compressive strengths, and electromechanical responses. On this basis, the addition of 0.4 vol.% carbon fiber was confirmed as the optimal dosage with both competent spraying performance and self-sensing function in the corresponding mixture. Furthermore, the porosity characteristics and fiber agglomeration of the designed mixtures were quantitatively assessed by micro computed tomography (micro-CT), which suggested their relationship to the mechanical and self-sensing properties. Apart from the structural application potential of the developed self-sensing mixture, this study also provides detailed guidance for the optimization of other value-added robotic sprayable cementitious materials. National Research Foundation (NRF) This research is supported by the National Research Foundation, Prime Minister’s Office, Singapore under its Medium-Sized Centre funding scheme, CES_SDC Pte Ltd, and Chip Eng Seng Corporation Ltd. 2024-07-31T07:35:24Z 2024-07-31T07:35:24Z 2024 Journal Article Lu, B., Wang, L., Wang, X., Tan, M. J., Li, H. K. H. & Wong, T. N. (2024). Development of robotic sprayable self-sensing cementitious material for smart structural health monitoring. Additive Manufacturing, 85, 104161-. https://dx.doi.org/10.1016/j.addma.2024.104161 2214-7810 https://hdl.handle.net/10356/179449 10.1016/j.addma.2024.104161 2-s2.0-85191321398 85 104161 en Additive Manufacturing © 2024 Elsevier B.V. All rights reserved. |
| spellingShingle | Engineering Robotic spraying Self-sensing Lu, Bing Wang, Lining Wang, Xiangyu Tan, Ming Jen Li, Holden King Ho Wong, Teck Neng Development of robotic sprayable self-sensing cementitious material for smart structural health monitoring |
| title | Development of robotic sprayable self-sensing cementitious material for smart structural health monitoring |
| title_full | Development of robotic sprayable self-sensing cementitious material for smart structural health monitoring |
| title_fullStr | Development of robotic sprayable self-sensing cementitious material for smart structural health monitoring |
| title_full_unstemmed | Development of robotic sprayable self-sensing cementitious material for smart structural health monitoring |
| title_short | Development of robotic sprayable self-sensing cementitious material for smart structural health monitoring |
| title_sort | development of robotic sprayable self sensing cementitious material for smart structural health monitoring |
| topic | Engineering Robotic spraying Self-sensing |
| url | https://hdl.handle.net/10356/179449 |
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