Strengthening Concrete Structures with Smart Materials
用智能材料加固混凝土结构
基本信息
- 批准号:RGPIN-2015-05987
- 负责人:
- 金额:$ 1.6万
- 依托单位:
- 依托单位国家:加拿大
- 项目类别:Discovery Grants Program - Individual
- 财政年份:2020
- 资助国家:加拿大
- 起止时间:2020-01-01 至 2021-12-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Deterioration of Reinforced Concrete (RC) structures is a never-ending problem that incites civil engineers around the world to seek innovative durable strengthening techniques and high performance advanced materials. Recently, a new class of smart materials called Shape Memory Alloys (SMA) has been attracting the attention of researchers from different fields due to their superior properties. The SMA is a unique class of alloy with the ability to undergo large deformations and return to its original shape through stress removal. Besides their super-elasticity, corrosion and fatigue resistivity, SMAs are mainly characterized by the Shape Memory Effect (SME) phenomenon that is inherited through their unique thermo-mechanical properties. The SME represents the ability of the SMAs to recover their original shape after being deformed beyond the elastic limits upon heating. SMAs with the SME property can be used as external prestressed reinforcement by providing active strengthening to RC members.
The most common SMA is made of Nickel and Titanium (NiTi). The use of NiTi-SMAs in civil engineering applications was limited due to their relatively higher cost. However, the recent development of corrosion resistant iron-based Fe-SMA with considerably lower cost and high recovery stress, have made it to be the choice for structural applications. The motivation of this research is driven by the fact that Fe-SMA in strengthening RC beams and columns has not yet been addressed.
The main objective of this research is to investigate experimentally and analytically the effectiveness and feasibility of two active strengthening techniques without the need of any mechanical anchorage/jacking systems for the prestressing operation. The proposed two techniques are: one for confining RC columns using Fe-SMA wires and one for flexural strengthening of RC beams using Fe-SMA bars. Both techniques rely on the recovery stress generated as the Fe-SMA transforms to its recovery (un-deformed) state upon heating. The SMA is temperature sensitive, and thus, it is important to investigate the environmental exposure effect on the performance of RC members strengthened with SMA. The effect of cyclic loading and unloading is also important to investigate if it affects the active stress in the SMA. With the unique properties of Fe-SMA, actively confining RC columns using Fe-SMA wires and actively strengthening RC beams in flexure using Fe-SMA bars is expected to produce a significantly ductile structural member.
The findings of this research are expected to add valuable knowledge to the field and widen the potential applications of the Fe-SMA in strengthening RC structures.
My research gives explicit priority to the education/training of HQP, seeks to promote increased network interactions/collaborations, and has the potential for technological impact for both immediate and long-term benefits to the research community.
钢筋混凝土(RC)结构的恶化是一个永无止境的问题,激励着世界各地的土木工程师寻求创新的耐用加固技术和高性能的先进材料。最近,一类新的智能材料形状记忆合金(SMA)因其优异的性能而引起了不同领域研究人员的关注。SMA是一类独特的合金,具有承受大变形并通过消除应力恢复其原始形状的能力。除了具有超弹性、耐蚀性和疲劳电阻性外,sma的主要特点是其独特的热机械性能所继承的形状记忆效应(SME)现象。SME表示sma在加热后变形超过弹性极限后恢复其原始形状的能力。具有SME特性的sma可以作为外部预应力钢筋,为RC构件提供主动加固。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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ELHACHA, Raafat其他文献
ELHACHA, Raafat的其他文献
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{{ truncateString('ELHACHA, Raafat', 18)}}的其他基金
Smart Structures using Shape Memory Alloy and Carbon Nanofibers Ultra-High Performance Concrete
使用形状记忆合金和碳纳米纤维超高性能混凝土的智能结构
- 批准号:
RGPIN-2021-02800 - 财政年份:2022
- 资助金额:
$ 1.6万 - 项目类别:
Discovery Grants Program - Individual
Smart Structures using Shape Memory Alloy and Carbon Nanofibers Ultra-High Performance Concrete
使用形状记忆合金和碳纳米纤维超高性能混凝土的智能结构
- 批准号:
RGPIN-2021-02800 - 财政年份:2021
- 资助金额:
$ 1.6万 - 项目类别:
Discovery Grants Program - Individual
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用智能材料加固混凝土结构
- 批准号:
RGPIN-2015-05987 - 财政年份:2019
- 资助金额:
$ 1.6万 - 项目类别:
Discovery Grants Program - Individual
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