4.7 Article

Identification of the structural damage mechanism of BFRP bars reinforced concrete beams using smart transducers based on time reversal method

期刊

CONSTRUCTION AND BUILDING MATERIALS
卷 220, 期 -, 页码 615-627

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.conbuildmat.2019.06.056

关键词

Basalt fiber reinforced polymer (BFRP) bars; Smart aggregate (SA) transducers; Time reversal method; Structural damage mechanism

资金

  1. Natural Science Foundation of China [51678149]
  2. Guangdong Science and Technology Planning, China [2016A010103045]
  3. Key Research Project by Department of Education of Guangdong Province, China [2018KZDXM068]
  4. Guangdong Natural Science Foundation, China [2018A030313864]

向作者/读者索取更多资源

Fiber reinforced polymer (FRP) bars, as alternatives of steel bars, are encouraged to be utilized in concrete construction due to the properties of both corrosion resistance and high tensile strength. In this paper, smart aggregate (SA) transducers, which can be used as both actuator and sensor, are employed to identify the structural damage mechanism of basalt-FRP (BFRP) bars reinforced concrete beams. Time reversal method is adopted for increasing the signal-to-noise ratio (SNR), which is aimed at obtaining clear amplitude of focused signal. Those methodologies are applied to conduct a further study of the structural mechanism of BFRP reinforced concrete flexural components. The experimental results reveal that the cracking and failure position of the concrete beam reinforced with BFRP bars can be located and the corresponding loads can be identified according to signal change when different crack appears. The stiffness degradation of BFRP bars reinforced concrete beams can be effectively expressed and the deflection can be accurately predicted by acquiring amplitude of focused signals in the overall zone. Additionally, it has been recognized that the damage process and mechanism of BFRP reinforced concrete beams can be accurately evaluated using those SA transducers and the status of those structural components also can be monitored effectively. (C) 2019 Elsevier Ltd. All rights reserved.

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