Sort:
Issue
Experimental teaching design for generating artificial acoustic signals from gas-containing coal by mechanical vibrations
Experimental Technology and Management 2025, 42(11): 223-230
Published: 20 November 2025
Abstract PDF (1.7 MB) Collect
Downloads:1
[Objective]

Coal and gas outbursts are complex dynamic disasters that occur near coal mining faces. In recent years, coal and gas outburst accidents induced by external vibrations have become increasingly frequent. Understanding the dynamic changes in ground stress and the characteristics of gas migration near the working face during various coal mining operations is essential for predicting coal and gas outbursts and providing early warnings of potential dynamic hazards. Although various geological prediction methods, such as direct current detection, ground-penetrating radar, seismic exploration, and transient electromagnetic methods, are widely used, they still have limitations in the real-time monitoring of changes in the surrounding rock stress. To explore the qualitative and quantitative relationships between artificial acoustic signals generated by mechanical vibrations and the corresponding stress, strain, and gas pressure in coal, as well as to enhance students’ practical scientific research skills, a teaching experiment on artificial acoustic signals induced by mechanical vibrations was conducted.

[Methods]

A self-developed device for testing artificial acoustic signals based on mechanical vibrations was used to conduct acoustic signal excitation tests under varying axial loading stress and gas pressure values. The device comprised five main units: gas charging and exhaust units, a mechanical vibration unit, a vibration-force monitoring unit, an axial-pressure loading unit, and an artificial acoustic signal monitoring and acquisition unit. Standard coal samples with a diameter of 50 mm and a height of 100 mm were prepared, and uniaxial compression tests were conducted to determine their basic mechanical parameters. During the experiment, a pendulum was set to swing freely from a fixed angle of 20°, and acoustic signals were collected every 10 s under different axial stresses (10~40 kN) and gas pressures (0~1.2 MPa). The relationship between the spectral characteristics of the artificial acoustic signals and the axial loading stress and gas pressure was analyzed and fitted using the introduced relative stress coefficient K.

[Results]

Before the axial stress reached the uniaxial compressive strength of the coal sample without gas, the sample underwent compaction and elastic stages. The original cracks closed, and a few new microcracks were generated. No macroscopic cracks appeared, and the failure was not obvious. During this phase, the K value gradually increased with increasing axial loading stress, and the increasing trend gradually slowed down. Once the axial stress exceeded the peak value, cracks in the coal sample propagated, macroscopic cracks developed, and the K value began to decrease. When the gas pressure was 0.9 and 1.2 MPa, a different trend was observed: before the axial loading stress reached the uniaxial compressive strength of the gas-free coal sample, the K value showed a decreasing trend. The coefficient of determination (R2) for the fitting function relating K to the axial stress before coal body failure exceeded 98.53%. Before the instability and failure of the coal sample, as the axial stress gradually increased, the primary cracks inside the coal body closed, and only some microcracks appeared. The signal source propagated well within the coal body, eventually leading to a gradual increase in the K value with increasing axial stress. The R2 of the fitting function relating K to the gas pressure before coal body failure exceeded 98.94%.

[Conclusions]

By examining the relationship between the spectral characteristics of artificial acoustic signals and the parameters of coal and gas outbursts, this experiment enhances students’ autonomous learning and problem-solving abilities, stimulates academic interest, cultivates academic thinking, strengthens team cohesion, and establishes a solid foundation for future research.

Open Access Research Article Issue
Coal and gas outburst risk prediction based on improved DBO optimized CNN
Journal of Mining Science and Technology 2025, 10(5): 912-922
Published: 31 October 2025
Abstract PDF (7.2 MB) Collect
Downloads:2

The gradual increase in coal-mine excavation depth leads to the significant rise in the in situ stress in deep surrounding rock and escalating risks of gas desorption and accumulation, causing a higher likelihood of coal-gas outbursts. In this light, the present study develops a deep-learning-based predictive model for coal-gas outbursts. First, the collected data were preprocessed using the Local Outlier Factor (LOF) and Multiple Imputation by Chained Equations (MICE), and employed Kendall's rank correlation coefficient to select those factors exhibiting strong correlation as the predictive indicators for gas outbursts. Next, a convolutional neural network (CNN) architecture was constructed, and optimized its hyperparameters via an enhanced dung beetle optimization algorithm (MSADBO). This algorithm incorporates an improved sine-based dynamic search-step adjustment, an adaptive Gaussian-Cauchy hybrid mutation to bolster global and local search capabilities, and a Bernoulli chaotic-map strategy to increase population diversity. Finally, comparative models were established; accuracy and other evaluation metrics were compared across models, and the safety of the predictions was analyzed via confusion matrices. Results demonstrate that the MSADBO-CNN model achieved an accuracy of 98.7 % on the training set and 91.67 % on both the validation and test sets, thereby attaining the highest predictive precision while also exhibiting superior robustness, generalization ability, and operational safety.

Open Access Research Article Issue
Study on the ramifications of small molecule organic matter within the kinetic behavior of CH4 and CO2 adsorption
Journal of Mining Science and Technology 2025, 10(5): 808-820
Published: 31 October 2025
Abstract PDF (21.5 MB) Collect
Downloads:2

The complex pore structure and organic matter composition of coal significantly affect the storage and transportation characteristics of gas, and the role of soluble organic matter is still lacking in in-depth research. This study, represented by tetrahydrofuran-2-ol (C4H8O2), explores the effect of small molecule organic compounds on coal adsorption of CH4 and CO2 through quantum chemical simulations. The static potential of a single molecule was determined through quantum chemistry calculations. Detailed analysis was conducted on the adsorption heat, mean square displacement, radial distribution function, and adsorption energy distribution during the adsorption process. The results indicate that the excessive adsorption capacity of coal for CO2 is always higher than that for CH4. Organic small molecules significantly reduce the gas adsorption capacity and adsorption heat of coal, weaken the interaction between heteroatoms and adsorbate molecules, and have a significant impact on CO2 adsorption, thereby significantly reducing the interaction between CO2 and coal molecules and weakening the displacement effect of CO2 on methane. At 6 MPa, its impact on CO2 adsorption is minimal. The results of this study contribute to a better understanding of the occurrence mechanism of coalbed methane, providing theoretical support for optimizing pre extraction gas technology and assisting in coal mine safety and efficient production.

Open Access Original Article Issue
Methane hydrate formation characteristics under different initial conditions and their impact on coal seam properties
Advances in Geo-Energy Research 2025, 16(3): 229-243
Published: 16 April 2025
Abstract PDF (1.6 MB) Collect
Downloads:70

Due to the unique structural characteristics of hydrate, it has a potential application value in coal and gas outburst prevention in coal mines. Given the complexity of subsurface environments, it is essential to investigate the hydrate formation kinetics under varied initial conditions, as well as the subsequent impacts of hydrate formation on coal seam properties. This research mainly focuses on the hydrate formation process in coal samples with different coalification degrees under different initial pressure and water saturation conditions by using the designed hydrate formation system. The results show that gas consumption and hydrate saturation can be greatly enhanced by increasing the initial water saturation and pressure, which is favorable to reduce the coal seam gas pressure and improve the coal seam peak strength. The calculation results suggest that hydrate formation at varying saturation reduces the gas pressure by 53.05% ~ 91.33% and increases the peak strength of coal across the tested confining pressure by 36.45% ~ 59%. Furthermore, this study found that hydrate formation kinetics are significantly enhanced in lignite compared to that in anthracite, which may be attributed to structural variations associated with the coalification degree. The underlying mechanism requires further research in the future. The data obtained in this study regarding the effect of hydrate formation under different initial conditions on coal seam properties demonstrate the feasibility of preventing gas disasters in coal via controlling the initial conditions.

Open Access Issue
Prediction of coal-gas compound dynamic disaster based on convolutional neural network
Journal of Mining Science and Technology 2023, 8(5): 613-622
Published: 31 October 2023
Abstract PDF (4.6 MB) Collect
Downloads:3

As deep mining becomes prevalent in China's coal mining industry, coal-gas compound dynamic disasters pose increasing threat to the safety production of coal mines. This paper adopts the field data of Pingmei No. 8 coal mine for analysis, with the attempt to predict coal-gas compound dynamic disaster through convolutional neural network. Following the routine of the big data processing, we first employed Box-plot analysis and multiple interpolation method(MI)to clean the data. Combined with grey relation analysis(GRA), we established a coal-gas compound dynamic disaster index system. Then, principal component analysis(PCA)is used for dimensionality reduction of the data. Combined with the convolution neural network(CNN)in deep learning, we established the coal-gas compound dynamic disaster prediction model based on BMGP-CNN. The field data is used to compare and verify this model with BP, random forest(RF), support vector machine(SVM)and artificial neural network(ANN). It is found that BMGP-CNN model yields prediction results with satisfactory accuracy and quick convergence. The results offer implications for the prediction and prevention of coal-gas compound dynamic disasters.

Open Access Issue
Deformation, seepage and energy evolution characteristics of gas-bearing coal-rock under intermediate principal stress
Journal of Mining Science and Technology 2023, 8(1): 74-82
Published: 28 February 2023
Abstract PDF (6.9 MB) Collect
Downloads:7

In deep mining, coal-rock is in a state of three unequal forces, and the intermediate principal stress has the influence on the deformation and strength characteristics of coal-rock. This study studied the deformation and seepage characteristics of gas-bearing composite coal-rock under different intermediate principal stresses by using true triaxial gas-solid coupling seepage test device for coal and rock. The results show : ① With the increase of intermediate principal stress, the strain in the direction of maximum principal stress first increases and then decreases when the peak strength is reached, and there is widening gap between the strain in the direction of intermediate principal stress and the strain in the direction of minimum principal stress.② Under low intermediate principal stress, the strain in the intermediate principal stress direction shows expansion and deformation, and when there is relatively high intermediate principal stress, the ε2σ curve reaches the peak and then bounces back, and the strain in the intermediate principal stress direction finally shows compression and deformation.③ With the increase of intermediate principal stress, the trough value of relative permeability coefficient decreases, and the peak inflection point of relative permeability coefficient curve is consistent with the inflection point of ε1σ curve.④ When the stress peak is reached, the total input energy of the specimen first increases and then decreases, which is similar to the changes of the specimen strength: The elastic strain energy first increases and then decreases, the dissipative energy continues to increase, Ue/U first increases and then decreases, and Ud/U first decreases and then increases.

Issue
Experimental teaching design of safety big data technology course based on machine learning
Experimental Technology and Management 2023, 40(4): 181-186
Published: 20 April 2023
Abstract PDF (552.1 KB) Collect
Downloads:5

The teaching experiment design takes Python’s machine learning integration package as the core, takes coal, rock and gas composite dynamic disaster prediction as the background, and is written in Python language, which facilitates students to realize the programming task of machine learning and mining data in limited teaching and experiment courses. The experiment contents include data set construction, Apis call, data set reading, data normalization processing, model training and export, sample set prediction, model accuracy test and other links. This teaching experiment involves interdisciplinary subjects and has strong practicability, which can improve students’ ability to use appropriate modern analysis technology and tools.

Open Access Article Issue
Study on crowd evacuation in subway transfer station fires based on numerical simulation
Emergency Management Science and Technology 2022, 2: 16
Published: 30 December 2022
Abstract PDF (876.5 KB) Collect
Downloads:6

In order to study the influencing factors of fire evacuation bottlenecks and evacuation time in subway transfer stations, a subway transfer station model was built using Pathfinder to simulate the emergency evacuation of passengers in a fire. Using the control variable method, the evacuation under different conditions is simulated by changing the parameters. The effects of the use of escalators, the speed of escalators, preference for stairs and escalators, the use of escalators, the familiarity of exits, the speed of personnel movement and the width of stairs on evacuation time are discussed and analyzed. The results show that the fire evacuation bottlenecks of subway transfer stations is each stair entrance. Evacuation time can be shortened by increasing the speed of escalators, increasing the proportion of escalator walkers, reducing the proportion of passengers who choose familiar exits to escape, increasing the speed of passengers and increasing the width of stairs.

Open Access Article Issue
Influence of open and closed windows on the vertical spread characteristics of fire
Emergency Management Science and Technology 2022, 2: 1
Published: 24 March 2022
Abstract PDF (1.7 MB) Collect
Downloads:4

In order to systematically explain the spreading mechanism of vertical fire, Pyrosim software with fire dynamic modules is used to simulate the fire spreading characteristics in a five-storey residential apartment building. The vertical spread characteristics of fire, high-temperature smoke, and leap-frog behavior are analyzed by evaluating the distribution of pressure, temperature, and gas flow velocity in the studied numerical fire field. In addition, considering the possible cases of high-rise building fire in reality, the fire spreading characteristics of three different opening sequences of glass windows are given: (i) only the windows on the first floor are open; (ii) the windows are randomly opened by the high temperature of the glass; (iii) all glass windows from the first to the fifth floors are open. The simulation results show that an appropriate increase of turbulent flow in the low-level area can greatly reduce the fire temperature in the high-level area, which can provide a certain reference for the safety and design of building fire protection in the future.

Total 9