Identification of crack development in granite under triaxial compression based on the acoustic emission signal

Wang, Tianzuo; Wang, Linxiang; Xue, Fei; Xue, Mengya

doi:10.1177/1550147720986116

Cited by 21 publications

(4 citation statements)

References 36 publications

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“…Final failure patterns of granite samples subjected to different thermal shock treatments under triaxial compression are presented in Figure 11. When the temperature is at 25 °C, the angle of the main macroscopic fracture with respect to the horizontal direction is about 60 °, as shown in Figures 11(a Water cooling (5 Mpa) Yan Qin et al [34] Naturally cooling (10 Mpa) Xu et al [35] Fitting curve 8 Geofluids heterogeneous distribution and the thermal stress in minerals (tensile) under rapid quenching. At failure, there are many large-angle macroscopic tensile fractures, which is due to the decrease of tensile resistance with the increase of temperature [37].…”

Section: Failure Patternmentioning

confidence: 99%

Investigation of the Mechanical and Permeability Evolution Effects of High-Temperature Granite Exposed to a Rapid Cooling Shock with Liquid Nitrogen

Wang

Xue

et al. 2021

Geofluids

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Liquid nitrogen (LN2), which can greatly improve the efficiency of hot dry rock (HDR) mining, is commonly used as a cooling material in the enhanced geothermal system (EGS). Physical property, triaxial compression, and permeability tests were undertaken on treated granite samples, for a better scientific understanding of the effect of the LN2 cooling method on the mechanical and permeability properties of the rocks after heat treatment. The experimental results indicated that the physical properties of the treated granite change significantly, such as the density and wave velocity are substantially reduced. Meanwhile, with the increase of treatment temperature, the macroscopic cracks on its surface are gradually generated and the volume is expanded clearly. In addition, the surface wettability of granite gradually increases with increasing temperature. Compared with the air/water cooling methods, under LN2 cooling condition, the mechanical properties decrease markedly. When the temperature exceeds 600°C, the granite strength decreases significantly to only 56.16% of the reference value. The deformation properties also change significantly, with a final strain of about 3% at failure for a sample at 800°C, showing an obvious ductile deformation characteristic. Further, an appreciable correlation also exists between the initial permeability of granite and temperature. Once the temperature exceeds 200°C, the increase in temperature contributes to the increase in initial permeability. In addition to the effect of temperature, the increase in load also leads to a change in the permeability coefficient. When the temperature reaches 600°C, the permeability of granite first decreases and then increases with the increases in axial stress. The results of this paper are valuable in understanding the effect of thermal shock by LN2 on the fracturing efficiency and permeability characteristics of dry hot rocks.

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Section: Failure Patternmentioning

confidence: 99%

Investigation of the Mechanical and Permeability Evolution Effects of High-Temperature Granite Exposed to a Rapid Cooling Shock with Liquid Nitrogen

Wang

Xue

et al. 2021

Geofluids

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“…Damaskinskaya et al [10] analyzed the spatial distribution of hypocenters of AE signal sources, and revealed that the transition to correlated defect formation occurs in some regions in the case of continuous electrical exposure, despite the accumulation of almost uniform spatial defect. Wang et al [11] explored the development mechanism of cracks in the process of rock failure using AE and found that by fully analyzing the characteristics of AE signals in the time and frequency domain, the time and conditions of producing large cracks can be accurately and efficiently determined. Although extensive research has been conducted on the evolution characteristics of spatial fractures based on AE, all fractures are considered as a whole, and there is little research on fracture clusters.…”

Section: Introductionmentioning

confidence: 99%

Identification and Evolutionary Characteristics of Major Fractures in Beishan Granite

Wang,

Wan,

Ren

et al. 2023

Applied Sciences

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Identification of major fractures is a common problem in underground engineering. Research on the identification and evolutionary characteristics of major fractures are mainly based on high-level waste underground repositories. In this paper, a triaxial acoustic emission (AE) experiment was carried out, and methods such as fractal theory and machine learning were utilized to analyze the AE characteristics during rock failure. The evolution of fracture clusters within the rock was studied, and the AE characteristics of different fracture clusters were analyzed. The results show that as the confining pressure increases, fracture categories reduce, the proportions of major and non-major fractures decrease, and the proportion of outlier fractures increases. During the initial phase of AE, the proportion of major fractures significantly fluctuates, while during the active phase of AE, the proportion of major fracture acoustic emissions generally increases. The proportion of major fracture acoustic emissions remains relatively constant during the calm phase, and in the destructive phase, the proportion of major fractures slightly decreases. The variations in the b-value can be divided into three stages: increase, decrease, and secondary increase. A rock major fracture identification model was established based on BP neural network, and the model’s accuracy rate of major fracture identification was 87.22%.

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“…The characteristic of the quiet period was that only a small amount of acoustic emission signals are distributed in the specimens at this stage. Wang et al [3] carried out triaxial compression tests on granite samples under real-time AE monitoring. It was found that the AE signals of granite samples under triaxial compression can be divided into four stages: quiet period 1, active stage 1, quiet period 2, and active stage 2.…”

Section: Introductionmentioning

confidence: 99%

Research on Recognition of Quiet Period of Sandstone Acoustic Emission Based on Four Machine Learning Algorithms

et al. 2022

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Aiming at solving the problem that it is difficult to recognize the quiet period of acoustic emission in rocks, four machine learning algorithms were adopted to develop and improve the recognition method of the quiet period of acoustic emission. In the process of establishing the model, the time domain data of acoustic emission were standardized and processed by box diagram method, so as to clean the abnormal data and reduce the dimension, and the frequency domain data were denoised by wavelet four-layer transform and wavelet packet three-layer energy decomposition, and a group of 8 wavelet packet energy parameters were established as frequency domain characteristic parameters. Based on AE time domain data, frequency domain data, and composite data (time-frequency domain data sets), the grid search traversal parameter technique was used to obtain the optimal parameters of four machine learning models. The accuracy, precision, recall, and F 1 score were used to verify and evaluate the recognition performance of the models. The study results show that the recognition effects of the models are good, the model accuracy of the frequency domain data set is the lowest, and the model accuracy of the composite data set is the highest, with an accuracy of more than 90%. The kernel support vector machine model has the best performance, and its average precision is 0.87. The random forest (RF) model is the best model for recognizing quiet period of acoustic emission.

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Identification of crack development in granite under triaxial compression based on the acoustic emission signal

Cited by 21 publications

References 36 publications

Investigation of the Mechanical and Permeability Evolution Effects of High-Temperature Granite Exposed to a Rapid Cooling Shock with Liquid Nitrogen

Investigation of the Mechanical and Permeability Evolution Effects of High-Temperature Granite Exposed to a Rapid Cooling Shock with Liquid Nitrogen

Identification and Evolutionary Characteristics of Major Fractures in Beishan Granite

Research on Recognition of Quiet Period of Sandstone Acoustic Emission Based on Four Machine Learning Algorithms

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