Strain rate effect on the acoustic emission characteristics of concrete under uniaxial tension

Yan Wang; Na Wang; Chao Yan; Tingting Zhang; Lijun Chen; Jie Gu

doi:10.3139/120.111445

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Strain rate effect on the acoustic emission characteristics of concrete under uniaxial tension

Yan Wang , Na Wang , Chao Yan , Tingting Zhang , Lijun Chen und Jie Gu

Veröffentlicht/Copyright: 20. Dezember 2019

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Abstract

Concrete is an important engineering material whose tensile property plays an important role in structural safety. Thus, the effect of strain rate on crack evolution in concrete during tension cracking cannot be neglected. Within a strain rate range of 10⁻⁶ to 10⁻⁴ s⁻¹, an acoustic emission monitoring test for the whole process of concrete under uniaxial tension including the post-peak softening stage was conducted. Moreover, damage evolution, along with the cracking mechanism of concrete at various strain rates was discussed with respect to the effect of strain rate on acoustic emission. The results show that the acoustic emission activity of concrete is delayed due to an increase in strain rate. This indicates that the hysteresis of deformation and cracking can be observed in a uniaxial tension test of concrete. During the whole loading process, as the strain rate increased, the average level of the acoustic emission hit rate increased significantly, indicating that an increase in strain rate accelerates crack initiation and propagation in concrete. Average acoustic emission values, duration and energy also show an increasing trend, and the scatter distribution range between them and the acoustic emission amplitude changes significantly, a fact that can be used to identify the damage degree of concrete under different strain rates. A peak frequency and cd4 band wavelet energy spectrum coefficient tends to decrease, while the ca8 band wavelet energy spectrum coefficient increases. In other words, the proportion of low frequency acoustic emission signals increases, indicating that an increase in strain rate increases the proportion of macroscopic cracks in concrete. At various strain rates, the average level of acoustic emission characteristic parameters and the proportion of high frequency signals at the post-peak stage in concrete are higher than those at the pre-peak stage, indicating that the development of microcracks in concrete mainly concentrates during the post-peak softening stage.

∗Correspondence Address, Associate Prof. Dr. Yan Wang, College of Civil and Transportation Engineering, Hohai University, Nanjing, 210024, China, E-mail: drwanghhu@126.com

Associate Prof. Dr. Wang Yan, born in 1980, studied Civil Engineering at Hohai University, China, from 2000 till 2009. There, he finished his PhD on the damage assessment and damage mechanism of concrete based on acoustic emission technology in 2009 and and began teaching at the university in the same year. The focus of his research lies on the damage study of concrete based on acoustic emission and ultrasonic technique.

MEng Wang Na, born in 1995, has been studying Civil Engineering at Hohai University, China, since 2017. Her research focuses on the damage process of concrete and reinforced concrete based on acoustic emission analysis technique and method.

MEng Yan Chao, born in 1994, has been studying Civil Engineering at Hohai University, China, since 2017. Her research focuses on the damage process of concrete based on acoustic emission wavelet analysis technique.

MEng Zhang Ting Ting, born in 1993, has been studying Civil Engineering at Hohai University, China, since 2016. Her research focuses on the whole damage process of concrete based on acoustic emission fractal theory.

MEng Chen Li Jun, born in 1996, has been studying Civil Engineering at Hohai University, China, since 2018. Her research focuses on the damage characteristics of reinforced concrete based on the acoustic emission analysis technique.

MEng Gu Jie, born in 1995, has been studying Civil Engineering at Hohai University, China, since 2018. Her research focuses on the damage characteristics of concrete based on acoustic emission and neural networks.

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Published Online: 2019-12-20

Published in Print: 2020-01-07

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https://doi.org/10.3139/120.111445