纤维增强塑料
结构工程
材料科学
岩土工程
复合材料
法律工程学
工程类
作者
Yixuan Bai,yang liu,Nanyan Hu,Xueqi Zhao,Dongdong Chen
标识
DOI:10.1088/1361-665x/adf020
摘要
Abstract To solve the problem of debonding status detection of Glass Fiber Reinforced Polymer (GFRP) rock bolt structure, the influence of different media for the detection of debonding status was explored. In view of the fact that the debonding may cause engineering safety accidents, it is important to accurately judge the debonding status of the GFRP rock bolt structure. To explore the influence of different media (air, water, seawater, ice, sand) on the debonding detection of GFRP rock bolt structures, firstly, the debonding detection model of GFRP rock bolt structures was simplified, and the influence of different debonding void media on the debonding detection was analyzed, and then the numerical simulation test of the influence of debonding void media on the debonding detection was carried out, and then the theoretical calculation and numerical simulation experiments were verified by laboratory tests, and finally water and seawater were taken as examples. To explore the influence of water content volume on the detection of the debonding status of GFRP rock bolt structure. The results show that the presence of the media in the debonding void doesn’t affect the waveform of the focused signal detected by the debonding, but will affect the amplitude of the focused signal, and the closer the wave impedance ratio of the debonding void media to the GFRP rock bolt wave impedance ratio is 1, the greater the influence of the debonding void media on the signal amplitude, and the increase of the water content volume in the debonding void leads to the increase of the wave impedance on the right side of the interface, and as the volume of water content rises, the amplitude of the focusing signal gradually decreases. This study reveals the influence of debonding void media on the detection of the debonding status of GFRP rock bolt structure, and provides a new theoretical basis for the study of the detection of the debonding status.
科研通智能强力驱动
Strongly Powered by AbleSci AI