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University of Technology Sydney

Design and Performance of Intrinsic Self-sensing Cementitious Composites for Smart Structural Health Monitoring of Civil Infrastructure

Abstract

dc:description.abstract

Intrinsic self-sensing cementitious composites which simultaneously own the load bearing capacity and self-sensing capacity, have attracted increasing research interests in recent years to fulfil the multifunctional requirements for the next generation of biomimetic, intelligent and resilient cement-based materials. With the inclusion of conductive/functional fillers, the ordinary cementitious composites can intrinsically sense the strain, stress and damage by calibrating the variations of the electrical signal, and often possess other functionalities (i.e. electromagnetic interference shielding and self-heating) with brilliant application prospects such as structural health monitoring, antistatic flooring, road de-icing and traffic detection. Despite the extensive investigations and many positive developments on fibrous carbon materials filled self-sensing cementitious composites, the development and application of self-sensing cementitious composites filled with carbon black are still limited either by the low sensing effectiveness or the inferior mechanical properties. Although carbon black is much cheaper than other carbon-based fibrous nanoreinforcements, the utilization of carbon black alone can hardly achieve effective percolating and sensing behaviours. Different dosages of carbon black (CB) and the fixed dosage of polypropylene (PP) fibres were used to manufacture the cost-effective and highly sensitive cement-based sensor in this study. The distribution of conductive phases and static electrical resistivity were firstly investigated through microcharacterisation and the static resistivity test. Then the self-sensing performance of CB/PP fibres cementitious composites in response to different loading scenarios was comprehensively assessed by cyclic compression, notched bending and splitting tension. The results indicate that the improvement of PP fibres on conductivity and self-sensing performance is heavily dependent on the coating efficiency of CB nanoparticles on the surface of PP fibres; better self-sensing performance is achieved for composites with excellent CB coating efficiency. In particular, composites with excellent CB coating efficiency demonstrate promising pre-crack flexural sensing capacity. Additionally, the strain hardening characteristic and damage sensing ability for the developed cement-based sensors are explored by the splitting tensile test in conjunction with digital image correlation (DIC) tracking. Apart from a strong linear correlation between fractional change of resistivity (FCR) and the tensile strain in the strain hardening stage, the distinct sensing characteristics between the strain hardening stage and softening stage allow the diagnosis of the damage stage (strain hardening stage or softening stage) and crack size (microcracking or macrocracking). Therefore, the cost-effective CB/PP fibres reinforced cementitious composites depict great potential as a robust cement-based sensor capable of sensing various loading conditions with both stress and damage detection properties.

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Guo, Yipu

Rights

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Statement dc:rights
  • The author owns the copyright in this thesis including all reproduction and reuse rights for the work. The work may not be altered without the permission of the copyright owner. Attribution is essential when quoting or paraphrasing from this thesis.
  • au.edu.uts.lib/ppc
  • info:eu-repo/semantics/openAccess
Language dc:language.iso
en_US

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/10453/164294
OAI identifier oai:identifier
oai:opus.lib.uts.edu.au:10453/164294

Chain of custody

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University of Technology Sydney
Base URL
opus.lib.uts.edu.au/oai/request
Last updated
2026-07-24
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OAI-PMH GetRecord
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citation

Guo, Yipu. Design and Performance of Intrinsic Self-sensing Cementitious Composites for Smart Structural Health Monitoring of Civil Infrastructure. 2022. http://hdl.handle.net/10453/164294