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Three-dimensional electrical tomography for imaging large concrete members

Three-dimensional electrical tomography for imaging large concrete members
用于大型混凝土构件成像的三维电断层扫描
批准号:
EP/V007025/1
负责人:
Danny Smyl
金额:
$52.73万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2021
资助国家:
英国
项目状态:
未结题
起止时间:
2021 至 --

项目摘要

项目成果

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中文摘要
翻译
混凝土结构无处不在,是英国和国际民用基础设施、城市景观、废物处理设施等的关键组成部分。现在,我们对混凝土结构的要求比以往任何时候都要高,从安全、耐用、经济和环境的角度来看。例如,仅在英国,就有大约67,400座承载重型货车的公路桥,其中70%以上是钢筋混凝土、预应力混凝土或混凝土涵洞桥。其中,近70%建于1960年至1990年之间。考虑到这些信息,仅在英国,更换或修复老化的国家桥梁的成本就非常巨大。例如,议会管理的(在英国)公路桥的总维修积压估计为67亿英镑。这表明英国议会管理的混凝土桥梁目前有47亿英镑的维修积压。据估计,与拆除和重建这些桥梁有关的费用大约比目前积压的维修费用高出两个数量级。因此,解决当代混凝土基础设施挑战需要的不仅仅是货币解决方案,还需要技术创新。要开始解决老化的混凝土基础设施的需求,我们必须首先能够可靠地评估混凝土结构在其使用寿命期间的状况,以便在更换之前进行修复或在故障之前停止服务。然而,目前许多无损检测/结构健康监测(NDT/SHM)成像方法对混凝土结构内部状况的信息有限。该项目通过确定一种新的3D方法(电子断层扫描)的可行性来应对这一问题,该方法用于评估混凝土结构构件(如梁、板和柱)的状况和健康状况。该项目的成果有可能实现(i)通过允许研究人员定量地“看到”暴露于极端环境和/或负载条件下的构件内部,对钢筋混凝土构件的基本行为进行实验研究;(ii)对已建成的混凝土结构进行定量的3D状态监测。从资产管理的角度来看,这种非破坏性技术将允许维护人员“看到”混凝土结构的内部。这样,维修人员可以检测到内部损坏,例如裂缝和钢筋腐蚀,并在个别构件危及安全或引起昂贵的系统问题需要更换整个结构之前修复/更换个别构件。
英文摘要
Concrete structures are ubiquitous and critical components of UK and international civil infrastructure, cityscapes, waste containment facilities, and much more. Now, more than ever, we demand more from our concrete structures, from safety, durability, economy, and environmental perspectives. For example, in the UK alone, there are approximately 67,400 highway bridges carrying heavy goods vehicles and over 70% are reinforced concrete, prestressed concrete, or concrete culvert bridges. Of these, nearly 70% were built between 1960 and 1990. Given this information, the cost of replacing or remediating ageing national bridges in the UK alone is huge. For example, the total maintenance backlog for council-managed (in Great Britain) road bridges has been estimated to be £6.7bn. This indicates that council-managed concrete bridges in Great Britain are currently in a £4.7bn maintenance backlog. The costs associated with deconstructing and reconstructing these bridges can be estimated as a figure approximately two orders of magnitude larger than the current maintenance backlog. Therefore, feasibly addressing contemporary concrete infrastructure challenges requires more than a monetary solution, it requires technical innovation. To begin addressing the demands of an ageing concrete infrastructure, we must first be able reliably assess the condition of concrete structures during their lifespan in order to, e.g., rehabilitate them before replacement or discontinuing service before failure. At present, however, many non-destructive testing/structural health monitoring (NDT/SHM) imaging methods offer limited information regarding the internal condition of concrete structures. This project responds to this issue by determining the feasibility of a new 3D approach (electrical tomography) for use in assessing the condition and health of concrete structural members, such as beams, slabs, and columns. Outcomes from the project have the potential to enable (i) experimental studies of the fundamental behaviour of reinforced concrete members by allowing researchers to quantifiably "see" inside members exposed to extreme environmental and/or loading conditions and (ii) quantitative 3D condition monitoring of constructed concrete structures. From an asset management perspective, this non-destructive technology would allow maintainers to "see" inside concrete structures. In doing this, maintainers can detect internal damage, such as cracking and reinforcement corrosion, and repair/replace individual members before they jeopardise safety or give rise to expensive systematic problems requiring replacement of the entire structure.
期刊论文(4)
专著(0)
科研奖励(0)
会议论文
DOI: 10.1177/14759217211037236
发表时间: 2021-08-10
期刊: STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL
影响因子: 6.6
作者: [Chen, Liang, Gallet, Adrien, Smyl, Danny]
通讯作者: Smyl, Danny
DOI: 10.1007/978-3-031-53389-1_28
发表时间: 2024
期刊:
影响因子: --
作者: [Basavaraj A]
通讯作者: Basavaraj A
DOI: 10.1098/rspa.2021.0526
发表时间: 2022-01
期刊: Proceedings. Mathematical, physical, and engineering sciences
影响因子: --
作者: [Gallet A, Rigby S, Tallman TN, Kong X, Hajirasouliha I, Liew A, Liu D, Chen L, Hauptmann A, Smyl D]
通讯作者: Smyl D
Cements and concretes materials characterisation using machine-learning-based reconstruction and 3D quantitative mineralogy via X-ray microscopy
通过 X 射线显微镜使用基于机器学习的重建和 3D 定量矿物学来表征水泥和混凝土材料
DOI: 10.1111/jmi.13278
发表时间: 2024
期刊: Journal of Microscopy
影响因子: 2
作者: [Mitchell R]
通讯作者: Mitchell R
国内基金
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  • 项目类别:
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    2015
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