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Experimental tests for study of failure process of soils with different clay content filled in fractures and faults

Author

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  • Zongqing Zhou

    (Army Logistics Academy of PLA
    Shandong University
    Monash University)

  • Gaohan Jin

    (Shandong University)

  • Pathegama Gamage Ranjith

    (Monash University)

  • Cheche Wei

    (Shandong University)

Abstract

The process of permeation damage of the filling medium in the fracture is critical to the stability of the fractured rock mass. This study focused on the seepage failure process of filling materials in fractures and faults. To investigate the effects of axial stress and clay content, a series of experimental tests were conducted on internally unstable granular soil specimens with different clay contents under different axial stresses. The variations of flow rate and hydraulic conductivity were recorded and analyzed during the tests, and the typical process of seepage failure was summarized. The flow rate, hydraulic conductivity, and their growth rates were found to be smaller under high axial stress compared to low axial stress, and the flow rate of samples with higher clay content was smaller than those with lower clay content. Initially, the hydraulic conductivity decreased slightly due to clay and fine particle rearrangement, and remained nearly constant when the hydraulic gradient was small. However, as the hydraulic gradient increased, the hydraulic conductivity began to increase in response to the loss of clay and fine particles.

Suggested Citation

  • Zongqing Zhou & Gaohan Jin & Pathegama Gamage Ranjith & Cheche Wei, 2024. "Experimental tests for study of failure process of soils with different clay content filled in fractures and faults," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 120(14), pages 13369-13383, November.
  • Handle: RePEc:spr:nathaz:v:120:y:2024:i:14:d:10.1007_s11069-024-06713-y
    DOI: 10.1007/s11069-024-06713-y
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    References listed on IDEAS

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    1. Zhang Ye & Tang Shoufeng & Shi Ke & Tong Xiamin, 2023. "An evaluation of the mine water inrush based on the deep learning of ISMOTE," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 117(2), pages 1475-1491, June.
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