Investigation on Prediction of Sandstone Failure Under Uniaxial Compression Based on Supervised Deep Learning

Wang, Shirui; Zhao, Yixin; Guo, Jihong; Liu, Bin

doi:10.1007/s00603-023-03435-8

Rock Mech Rock Eng

2023

DOI: 10.1007/s00603-023-03435-8

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Investigation on Prediction of Sandstone Failure Under Uniaxial Compression Based on Supervised Deep Learning

Shirui Wang,

Yixin Zhao,

Jihong Guo

et al.

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Cited by 2 publications

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Identification of damage states of load-bearing rocks using infrared radiation monitoring methods

Gao,

Ma,

Liu

et al. 2025

Measurement

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Identification of damage states of load-bearing rocks using infrared radiation monitoring methods

Gao,

Ma,

Liu

et al. 2025

Measurement

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Deformation Behaviors and Failure Mechanism of Coal Under Various Loading Rates Using Acoustic Emission and Digital Image Correlation

Zou,

Li,

Liu

et al. 2024

Buildings

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Coal pillar dams are affected by mining disturbance, which threatens the efficient operation of the underground reservoir. To study the deformation behaviors and failure mechanism of coal pillars under mining disturbance, an acoustic emission (AE) system and a deformation field system were applied to conduct uniaxial compression tests at various displacement rates. The AE characteristics and deformation field evolution of coal were investigated, and the microfailure mechanism was identified. The result shows that the deformation field evolutions are the same under various displacement rates. The increment of accumulated absolute energy near the peak stress rises with the displacement rates. The increase rate of the mean vertical displacement is positively correlated with the displacement rate. The coefficient of variation (CV) of the deformation field can be applied to identify the deformation behaviors of coal and shows the fluctuate–slow increase–rapid increase trend. The distribution ranges of AF (count/duration) and RA (rise time/amplitude) are mainly 0–750 kHz and 0–700 μs/dB. The microfailure mechanism is mainly tensile failure and is accompanied by some shear failure. The percentage of shear failure increases with the increase in the displacement rate. The result provides a reference for the design and stability evaluation of the underground reservoir.

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Investigation on Prediction of Sandstone Failure Under Uniaxial Compression Based on Supervised Deep Learning

Cited by 2 publications

References 55 publications

Identification of damage states of load-bearing rocks using infrared radiation monitoring methods

Identification of damage states of load-bearing rocks using infrared radiation monitoring methods

Deformation Behaviors and Failure Mechanism of Coal Under Various Loading Rates Using Acoustic Emission and Digital Image Correlation

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