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Analysis of Precursors Prior to Rock Burst in Granite Tunnel Using Acoustic Emission and Far Infrared Monitoring

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  • Zhengzhao Liang
  • Xiangxin Liu
  • Yanbo Zhang
  • Chunan Tang

Abstract

To understand the physical mechanism of the anomalous behaviors observed prior to rock burst, the acoustic emission (AE) and far infrared (FIR) techniques were applied to monitor the progressive failure of a rock tunnel model subjected to biaxial stresses. Images of fracturing process, temperature changes of the tunnel, and spatiotemporal serials of acoustic emission were simultaneously recorded during deformation of the model. The b -value derived from the amplitude distribution data of AE was calculated to predict the tunnel rock burst. The results showed that the vertical stress enhanced the stability of the tunnel, and the tunnels with higher confining pressure demonstrated a more abrupt and strong rock burst. Abnormal temperature changes around the wall were observed prior to the rock burst of the tunnel. Analysis of the AE events showed that a sudden drop and then a quiet period could be considered as the precursors to forecast the rock burst hazard. Statistical analysis indicated that rock fragment spalling occurred earlier than the abnormal temperature changes, and the abnormal temperature occurred earlier than the descent of the AE b -value. The analysis indicated that the temperature changes were more sensitive than the AE b -value changes to predict the tunnel rock bursts.

Suggested Citation

  • Zhengzhao Liang & Xiangxin Liu & Yanbo Zhang & Chunan Tang, 2013. "Analysis of Precursors Prior to Rock Burst in Granite Tunnel Using Acoustic Emission and Far Infrared Monitoring," Mathematical Problems in Engineering, Hindawi, vol. 2013, pages 1-10, December.
  • Handle: RePEc:hin:jnlmpe:214340
    DOI: 10.1155/2013/214340
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    Cited by:

    1. Yulong Chen & Junwen Zhang & Jiahao Zhang & Bin Xu & Luji Zhang & Wenxin Li, 2021. "Rockburst Precursors and the Dynamic Failure Mechanism of the Deep Tunnel: A Review," Energies, MDPI, vol. 14(22), pages 1-16, November.

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