Carbon-Based Nanomaterial Embedded Self-Sensing Cement Composite for Structural Health Monitoring of Concrete Beams - A Extensive Review

A. Dinesh
{"title":"Carbon-Based Nanomaterial Embedded Self-Sensing Cement Composite for Structural Health Monitoring of Concrete Beams - A Extensive Review","authors":"A. Dinesh","doi":"10.21741/9781644901953-25","DOIUrl":null,"url":null,"abstract":"Abstract. Structural health monitoring has proven to be a dependable source for ensuring the integrity of the structure. It also aids in detecting and estimating the progression of cracks and the loss of structural performance. The most compelling components in the structural health monitoring system are sensing material and sensor technology. In health monitoring systems, fiber optic sensors, strain gauges, temperature sensors, shape memory alloys, and other types of sensors are commonly used. Even though the sensors bring monetary value to the system, they have some apparent drawbacks. As a result, self-sensing cement composite was established as a sensor alternative with better endurance and compatibility than sensors. Carbon nanotubes, nanofibers, graphene nanoplates, and graphene oxide are carbon-based nanomaterials with unique mechanical and electrical properties. As a result, this review comprises a complete assessment of the fresh, mechanical, and electrical properties of self-sensing cement composite developed using carbon-based nanoparticles. The research also focuses on the self-monitoring performance of cement composite in concrete beams, both bulk and embedded, by graphing the deviation of fractional change in resistivity with strain. The network channel development of carbon-based nanomaterials in cement composites and their characterization acquired using scanning electron microscopy (SEM), and X-Ray diffraction spectroscopy (XRD) research are also comprehensively discussed. According to the study, increasing carbon-based embedment decreased the relative slump and flowability while increasing the composite's compressive, split tensile, flexural, and post-peak performance. Also, the amount of carbon in the carbon-based nanomaterial directly relates to the composite's conductivity. As a result, the development of piezoresistive and sensing capabilities in carbon-based self-sensing cement composites not only improves mechanical and conductive properties but also serves as a sensor in structural health monitoring of flexural members.","PeriodicalId":135346,"journal":{"name":"Sustainable Materials and Smart Practices","volume":"50 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sustainable Materials and Smart Practices","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.21741/9781644901953-25","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8

Abstract

Abstract. Structural health monitoring has proven to be a dependable source for ensuring the integrity of the structure. It also aids in detecting and estimating the progression of cracks and the loss of structural performance. The most compelling components in the structural health monitoring system are sensing material and sensor technology. In health monitoring systems, fiber optic sensors, strain gauges, temperature sensors, shape memory alloys, and other types of sensors are commonly used. Even though the sensors bring monetary value to the system, they have some apparent drawbacks. As a result, self-sensing cement composite was established as a sensor alternative with better endurance and compatibility than sensors. Carbon nanotubes, nanofibers, graphene nanoplates, and graphene oxide are carbon-based nanomaterials with unique mechanical and electrical properties. As a result, this review comprises a complete assessment of the fresh, mechanical, and electrical properties of self-sensing cement composite developed using carbon-based nanoparticles. The research also focuses on the self-monitoring performance of cement composite in concrete beams, both bulk and embedded, by graphing the deviation of fractional change in resistivity with strain. The network channel development of carbon-based nanomaterials in cement composites and their characterization acquired using scanning electron microscopy (SEM), and X-Ray diffraction spectroscopy (XRD) research are also comprehensively discussed. According to the study, increasing carbon-based embedment decreased the relative slump and flowability while increasing the composite's compressive, split tensile, flexural, and post-peak performance. Also, the amount of carbon in the carbon-based nanomaterial directly relates to the composite's conductivity. As a result, the development of piezoresistive and sensing capabilities in carbon-based self-sensing cement composites not only improves mechanical and conductive properties but also serves as a sensor in structural health monitoring of flexural members.
碳基纳米材料嵌入自传感水泥复合材料在混凝土梁结构健康监测中的应用综述
摘要结构健康监测已被证明是保证结构完整性的可靠来源。它还有助于检测和估计裂缝的进展和结构性能的损失。结构健康监测系统中最引人注目的组件是传感材料和传感器技术。在健康监测系统中,光纤传感器、应变计、温度传感器、形状记忆合金和其他类型的传感器是常用的。尽管传感器为系统带来了金钱价值,但它们也有一些明显的缺点。结果表明,自传感水泥复合材料具有比传感器更好的耐久性和相容性。碳纳米管、纳米纤维、石墨烯纳米板和氧化石墨烯是具有独特力学和电学性能的碳基纳米材料。因此,本综述对碳基纳米颗粒开发的自传感水泥复合材料的新鲜、机械和电学性能进行了全面评估。通过绘制电阻率分数变化随应变的偏差图,研究了混凝土梁中水泥复合材料的自监测性能,包括散装和嵌入式。本文还全面讨论了碳基纳米材料在水泥复合材料中网状通道的形成及其扫描电子显微镜(SEM)和x射线衍射光谱(XRD)的表征。研究表明,增加碳基嵌入降低了相对坍落度和流动性,同时提高了复合材料的压缩、劈裂拉伸、弯曲和峰后性能。此外,碳基纳米材料中碳的含量直接关系到复合材料的导电性。因此,碳基自传感水泥复合材料的压阻和传感能力的发展不仅提高了机械性能和导电性能,而且还可以作为受弯构件结构健康监测的传感器。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信