Stage Plot Pro Mac Serial Crackl
Abele Beardsley
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Acoustic emission (AE) is the immediate release of strain energy in the form of an elastic wave during material deformation16,17,18,19,20,21,22,23,24,25,26,27. The AE parameters and AE relationship to the mechanical failure process under compression have been extensively studied by researchers. By utilizing AE techniques, significant development has been made in understanding the progressive failure process of coal and rock. Researchers investigated coal and rock AE behavior under uniaxial compression, characterization of rock crack patterns under different loading rates, and coal AE fractal characteristics28,29,30,31,32,33. Water content has a significant impact on the AE characteristics of coal and rock, resulting in a decrease in elastic energy release and a reduction in the AE signal during loading34. Studies were conducted to investigate the effect of water content on failure patterns and AE features of rock with different water content. For this, uniaxial compression tests and numerical simulations with PFC2D software were used to investigate the evolution of microcracks and failure patterns15,35,36,37,38,39,40,41,42,43. The results indicated that increasing water content within the rock significantly decreased the rock strength, Young's modulus, strain to peak strain ratio in the elastic deformation stage, the maximum energy of a single AE event, and average AE energy. Lin et al. studied the AE parameters during disc cutter-induced rock fragmentation processes under various water conditions44. Read et al. studied the evolution of microcracks in rocks under saturated conditions using AE data45. The results demonstrated that the varying characteristics of crack propagation in rocks could be characterized by the frequency of AE events combined with volume change. The AE parameters and P-wave velocity variations in the porous rock after microcrack closure were studied by Fortin et al.46. Zhou et al. have taken sandstone under different water contents as a research object, and the type I fracture mechanism and AE characteristics were investigated47. The results unveiled that increasing water content decreased fracture toughness (KIc). Zhou et al. also investigated the quasi-static fracture behavior of sandstone containing different water content. For this, notched semi-circular bending (NSCB) tests were conducted, and the cracking process and acoustic emission (AE) signals were recorded simultaneously48. Zhu et al. and Liu et al. have paid their efforts to investigate the frequency features of AE signals during loading on dry and water-saturated rocks. The outcomes revealed that the high-frequency AE signals were pointedly reduced by water content26,49,50. An Analytical damage model based on acoustic emissions was developed by Ali et al. for dry and saturated coal51. Recently, the researchers have introduced the multi-fractal theory to deconstruct the AE signals to reveal better the nonlinear and multi-scale features of the deterioration and fracture process of water-bearing rocks52,53,54. These studies have provided valuable insights into understanding rocks' AE characteristics and damage behaviors under different water conditions. Hitherto, the variation of AE, fractal characteristics, and mechanical parameters of natural and coal with different water content and soaking times is rarely reported.
This paper examines the fractal characteristics of coal with different water contents in order to evaluate the variation in AE characteristics and mechanical parameters during the failure process of the coal. Coal was taken as an example to prepare specimens with varying water contents based on different soaking times. Grassberger Procaccia (GP) algorithms were utilized to find AE fractal characteristics based on the theory of phase space reconstruction. Based on the results of the AE test, comprehensive data could then be synchronized with the results of the mechanical testing in order to determine the type and location of rupture as well as the failure process of the samples. Therefore, this technique can be successfully utilized to predict coal and rock dynamic failure and ensure safety for engineering projects.
The composition of the system is shown in Fig. 3, and the tests carried out using this system are uniaxial compression tests (Uniform loading, cyclic loading). This experimentation equipment incorporated an axial loading subsystem and data acquisition system. The loading system (including the load displacement recording system) adopts the control system of Y4306, a 3000kN pressure testing machine. The system consists of a press host, loading control system, computer and power-test V33 composition of the control program. During the experiments, the pressure and displacement generated by the pressure head of the press are respectively transmitted to the loading control system with analog electrical signals through the pressure sensor and extensometer. The control box is converted into digital signals and transmitted to the computer. The computer software automatically collects and stores these data signals, and power-test V33. The software drives the press through the control box to realize the loading process automatically according to the manual instruction. During the experiment, the data sampling rate of force and displacement can reach 100 Hz, and the experimental curves of load time, deformation time, force deformation, and force displacement can be recorded and displayed in real time.
AE System (PCI-2) with eight channels was used to monitor and record the data. A detailed description of the parameters used in this experiment can be found in Table 2. The system includes an 18 bit A/D converter module, eight digital input/output channels, and two real-time data acquisition channels. The amplifier provides three output levels: 20 dB, 40 dB, and 60 dB. AE sensors are capable of responding to frequencies between 50 and 400 kHz, and are equipped with an electronic pre-amplifier of 20 dB. AE sensor signals are amplified by the preamplifier and transmitted to the conversion module. This data and the parameters of the digital signal are then stored in a buffer and are then transferred to a computer so that they can be further processed and displayed. Prior to the start of each experiment, sensors were attached to coal samples. We applied the load in displacement control mode at a loading rate of 0.200 mm/min. The loading system was initiated simultaneously with the AE monitoring system.
Figure 6 show the relationship of water content with wave velocity, UCS and elastic modulus (EM) respectively. Figure 6a show the linear fitting of wave velocity of coal with moisture content. The fitting curve show a good correlation with R2 value of 0.903. This demonstrate that the wave velocity in the coal mass gradually increases as the water content of the coal mass increases. The reason for this is that sound waves travel faster in water than in air and in coal masses with increased moisture content, water occupies a greater volume in the mass, while air occupies a smaller volume. Figure 6b show that the peak stress (UCS) of coal with varying water content is negatively correlated with water content with R2 value of 0.94. This indicate that the UCS of coal greatly influenced by water content and decreased with increasing water content. The reason for this is that water molecules gradually intrude into the coal samples, filling pores, and tend to provide, softening, and disintegrating effects, which eventually lead to destruction when comes under external load. The peak stress has a minimum value at maximum water content as shown in Fig. 6b. The EM value of a water-containing coal sample is less than that of a natural coal sample, showing that the presence of water in the coal sample can diminish the EM value. According to the fitting curve depicted in Fig. 6c, the values of EM declines linearly with the soaking time indicating a good negative correlation with R2 value of 0.97. Compared to the samples containing water content, the EM of natural samples is the greatest indicating their strength and resistance to deformation. Additionally, while there is some inaccuracy amongst samples with the same soaking period and water content, the average value of EM decrease progressively as the water content increases.
Energy dissipation is the most fundamental aspect of rock deformation and failure, reflecting the resulting development of new internal cracks, which weaken and ultimately disappear the strength of the material. According to the viewpoint of energy, the essence of the change of the physical state of matter is the conversion of energy, so rock failure can be regarded as state instability driven by energy.
In this study, the AE energy, AE cumulative energy, and dissipation energy of coal samples with different water content were analyzed. Figure 8. illustrates that coal samples with varying water content and soaking time under uniaxial compression have different AE energy, AE cumulative energy, dissipation energy, and stress time curves.
The findings indicate that AE energy and AE cumulative energy characteristics vary depending on the stage under stress, as well as AE characteristics that vary based on the water content of coal samples. Figure 8. illustrates a good correlation between AE energy and stress at all stages of the process. The loading process has five stages based on stress/strain curve. In order to determine the variation law of AE at different stages, the features of AE are examined. As can be seen in Fig. 8, all samples exhibit almost similar trends in AE under loading conditions.
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