The Electrical Resistivity and Acoustic Emission Response Law and Damage Evolution of Limestone in Brazilian Split Test

Xu, Xinji; Liu, Bin; Li, Shucai; Song, Jie; Li, Ming; Mei, Jie

doi:10.1155/2016/8052972

Cited by 11 publications

(7 citation statements)

References 10 publications

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“…In the existing research, it has been proved that using AE parameters to define damage variables and perform damage analysis is scientific [15,[34][35][36].…”

Section: Damage Eory Based On Aementioning

confidence: 99%

Research on Stress Threshold of Deep Buried Coal Rock under Quasi‐Static Strain Rate Based on Acoustic Emission

Hao

Liu

et al. 2020

Advances in Civil Engineering

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The deformation and failure process of coal rock under different strain rates is a significant challenge which must be solved in dynamic excavation. It is important to study the influence of strain rate on the evolution of coal rock crack. The triaxial compression tests and acoustic emission tests under the strain rate of 10−5 s−1 to 10−3 s−1 were conducted on coal rock using MTS 815 hydraulic servo-control testing machine. During the loading process, acoustic emission energy and spatial distribution have obvious stage characteristics. The damage variable is defined by acoustic emission energy, and the rate of damage evolution is obviously affected by the strain rate. Based on stage characteristics of acoustic emission energy, spatial distribution, and damage evolution, the use of damage evolution curve to determine stress threshold is proposed. In order to verify the rationality of the damage evolution method, the stress threshold values determined by damage evolution method and existing method are compared and analyzed. In order to study the effect of strain rate and confining pressure on the stress threshold, the stress thresholds under uniaxial and triaxial stress states at different strain rates were analyzed.

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“…In the existing research, it has been proved that using AE parameters to define damage variables and perform damage analysis is scientific [15,[34][35][36].…”

Section: Damage Eory Based On Aementioning

confidence: 99%

Research on Stress Threshold of Deep Buried Coal Rock under Quasi‐Static Strain Rate Based on Acoustic Emission

Hao

Liu

et al. 2020

Advances in Civil Engineering

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“…Li [25] investigated the mechanical behaviors and the variations in acoustic emission characteristic parameters, including event counts, cumulative counts, and energy, during the uniaxial compression failure process of sandstone. Xu [26] studied the variations in acoustic emission event counts and duration during the fracture failure process of limestone specimens. Wang [27] investigated the frequency-domain variations in acoustic emission energy during the failure process of limestone under Brazilian splitting loading conditions.…”

Section: Introductionmentioning

confidence: 99%

Classification of Microseismic Signals Using Machine Learning

Chen,

Cui,

et al. 2024

Processes

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The classification of microseismic signals represents a fundamental preprocessing step in microseismic monitoring and early warning. A microseismic signal source rock classification method based on a convolutional neural network is proposed. First, the characteristic parameters of the microseismic signals are extracted, and a convolutional neural network is constructed for the analysis of these parameters; then, the mapping relationship model between the characteristic parameters of the microseismic signals and the rock class is established. The feasibility of the proposed method in differentiating acoustic emission signals under different load conditions is verified by using acoustic emission data from laboratory uniaxial compression tests, Brazilian splitting tests, and shear tests. In the three distinct laboratory experiments, the proposed method achieved a source rock classification accuracy of greater than 90% for acoustic emission signals. The proposed and verified method provides a new basis for the preprocessing of microseismic signals.

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“…Failure of brittle rock normally initiates from tensile fracture due to its extraordinary lower resistance to tension rather than to compression [2]. In many engineering applications, parameters such as the stability of the chamber excavation and hydraulic fracturing largely depend on the tensile strength of the rock [3,4]. erefore, it is necessary to accurately determine the tensile properties of the layered rock mass.…”

Section: Introductionmentioning

confidence: 99%

Static and Dynamic Brazilian Tests on Layered Slate considering the Bedding Directivity

Zhang

Feng

et al. 2020

Advances in Civil Engineering

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A layered rock usually exhibits strong anisotropy due to its layered structure. In order to study the anisotropic effect on its static and dynamic tensile properties, a medium strength anisotropy slate is chosen and tested in five groups of bedding plane dip angles. The dynamic tests were carried out by a split Hopkinson pressure bar (SHPB), and the failure process of rock samples is recorded by a high-speed camera. The failure mode and strength characteristic of the slate are analyzed. The static test results show that layered structure significantly affects the failure mode, and the influence of the bedding plane depends on the degree of anisotropy. The static and dynamic “tensile strength” exhibit the “U” type strength anisotropy. For samples in the same dip angle group, the “tensile strength” shows clear dynamic strengthening effect, and the growth rate is most significant at θ = 45°.

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The Electrical Resistivity and Acoustic Emission Response Law and Damage Evolution of Limestone in Brazilian Split Test

Cited by 11 publications

References 10 publications

Research on Stress Threshold of Deep Buried Coal Rock under Quasi‐Static Strain Rate Based on Acoustic Emission

Research on Stress Threshold of Deep Buried Coal Rock under Quasi‐Static Strain Rate Based on Acoustic Emission

Classification of Microseismic Signals Using Machine Learning

Static and Dynamic Brazilian Tests on Layered Slate considering the Bedding Directivity

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