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    Acoustic Emission Wavelet Analysis and Damage Stage Identification of Basalt Fiber-Reinforced Concrete under Dynamic Splitting Tensile Loads

    Source: Journal of Materials in Civil Engineering:;2023:;Volume ( 035 ):;issue: 006::page 04023147-1
    Author:
    Hua Zhang
    ,
    Chuanjun Jin
    ,
    Xiaoyu Zhang
    ,
    Shanshan Ji
    ,
    Xinyue Liu
    ,
    Xuechen Li
    DOI: 10.1061/JMCEE7.MTENG-14756
    Publisher: American Society of Civil Engineers
    Abstract: This paper aims to study the strength and damage characteristics of basalt fiber-reinforced concrete (BFRC) under dynamic splitting tensile loads. Brazilian disk splitting tests and acoustic emission (AE) tests were carried out on BFRC herein. The improvement effects of loading rate and fiber content on the dynamic splitting tensile strength of BFRC were studied. Then, AE wavelet analysis methods (wavelet energy spectrum coefficient and maximum wavelet energy value) were employed to analyze the AE signals generated by BFRC. Additionally, a back-propagation (BP) artificial neural network was established to identify the damage stage of BFRC under dynamic splitting tensile loads. The test results showed that the improvement effect of the loading rate on the dynamic splitting tensile strength was enhanced with an increasing loading rate, and the enhancing effect of basalt fiber in the cases of 0.1% or 0.15% fiber dosages was better than that of the others. Most of the AE signals generated by BFRC were low frequency. Furthermore, the loading rate and the addition of fibers had a considerable impact on the wavelet energy spectrum coefficients corresponding to different bands and the distribution of maximum wavelet energy values of BFRC. Finally, the recognition rate of this BP neural network increased with the increment of the number of AE samples with the progress of loading.
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      Acoustic Emission Wavelet Analysis and Damage Stage Identification of Basalt Fiber-Reinforced Concrete under Dynamic Splitting Tensile Loads

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    http://yetl.yabesh.ir/yetl1/handle/yetl/4292973
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    contributor authorHua Zhang
    contributor authorChuanjun Jin
    contributor authorXiaoyu Zhang
    contributor authorShanshan Ji
    contributor authorXinyue Liu
    contributor authorXuechen Li
    date accessioned2023-08-16T19:14:10Z
    date available2023-08-16T19:14:10Z
    date issued2023/06/01
    identifier otherJMCEE7.MTENG-14756.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4292973
    description abstractThis paper aims to study the strength and damage characteristics of basalt fiber-reinforced concrete (BFRC) under dynamic splitting tensile loads. Brazilian disk splitting tests and acoustic emission (AE) tests were carried out on BFRC herein. The improvement effects of loading rate and fiber content on the dynamic splitting tensile strength of BFRC were studied. Then, AE wavelet analysis methods (wavelet energy spectrum coefficient and maximum wavelet energy value) were employed to analyze the AE signals generated by BFRC. Additionally, a back-propagation (BP) artificial neural network was established to identify the damage stage of BFRC under dynamic splitting tensile loads. The test results showed that the improvement effect of the loading rate on the dynamic splitting tensile strength was enhanced with an increasing loading rate, and the enhancing effect of basalt fiber in the cases of 0.1% or 0.15% fiber dosages was better than that of the others. Most of the AE signals generated by BFRC were low frequency. Furthermore, the loading rate and the addition of fibers had a considerable impact on the wavelet energy spectrum coefficients corresponding to different bands and the distribution of maximum wavelet energy values of BFRC. Finally, the recognition rate of this BP neural network increased with the increment of the number of AE samples with the progress of loading.
    publisherAmerican Society of Civil Engineers
    titleAcoustic Emission Wavelet Analysis and Damage Stage Identification of Basalt Fiber-Reinforced Concrete under Dynamic Splitting Tensile Loads
    typeJournal Article
    journal volume35
    journal issue6
    journal titleJournal of Materials in Civil Engineering
    identifier doi10.1061/JMCEE7.MTENG-14756
    journal fristpage04023147-1
    journal lastpage04023147-17
    page17
    treeJournal of Materials in Civil Engineering:;2023:;Volume ( 035 ):;issue: 006
    contenttypeFulltext
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