Analysis of the Pore Structure and Fractal Characteristics of Coal and Gas Outburst Coal Seams Based on Matrix Compression Correction

Gao, Yabin; Cao, Jing; Zhang, Shaoqi; Li, Ziwen

doi:10.3390/su151712670

Cited by 3 publications

(1 citation statement)

References 19 publications

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“…As research continues to deepen, researchers increasingly adopt a quantitative approach to studying fractal features. Gao et al [19] calculated the fractal dimension of the pore structure according to the solid mass fractal model and statistically analyzed the change in pore volume. They then analyzed the fractal characteristics of the pore structure of the coal body.…”

Section: Introductionmentioning

confidence: 99%

The Fractal Characteristics of Ground Subsidence Caused by Subway Excavation

Qin,

He,

Zhang

et al. 2024

Applied Sciences

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The issue of uneven ground settlement caused by the excavation of subway tunnels represents a significant challenge in the design and construction of subway projects. This paper examined the fractal characteristics of surface settlement caused by subway excavation, employing wavelet transform and fractal theory. Firstly, the noise reduction effects of different wavelet functions, decomposition levels, threshold functions, and threshold selection rules were evaluated using the SNR and RMSE. Subsequently, 291 data points were derived from 18 interpolation points through fractal interpolation, representing a utilization of only 18% of the original data, to enhance the original monitoring data information by a factor of 2.94. The average relative error between the fractal interpolation results and the monitoring data was approximately 13%, which was indicative of a high degree of accuracy. Finally, the fractal dimension of the monitoring curves under different monitoring frequencies was calculated using the box-counting method. The denoising effect of the dbN wavelet function was found to be superior to that of the symN wavelet function in the denoising process of subway construction surface deformation monitoring data. Furthermore, the hard threshold method was observed to be more effective than the soft threshold method. As the monitoring frequency decreased, the fractal dimension of the deformation curves showed an overall decreasing trend. This indicated that high-frequency monitoring could capture more details and complexity of the surface settlement, while low-frequency monitoring led to a gradual flattening of the curves and a decrease in details.

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Section: Introductionmentioning

confidence: 99%

The Fractal Characteristics of Ground Subsidence Caused by Subway Excavation

Qin,

He,

Zhang

et al. 2024

Applied Sciences

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Will greenhouse gas emissions increase with mining depth in coal mines? An analysis of gas occurrence under varying in-situ stress conditions

Zhao,

Wang

et al. 2024

Science of The Total Environment

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Research on an Equivalent Algorithm for Predicting Gas Content in Deep Coal Seams

Chai,

Wu,

Zhang

et al. 2024

Applied Sciences

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This document introduces a novel equivalent algorithm for forecasting gas content within deep coal seams, which is subject to constraints stemming from the advancements and precision achieved in well and roadway engineering endeavors. This algorithm meticulously acknowledges that coal seam gas content comprises three fundamental components: the inherent gas emission rate of the equivalent stratum, the residual gas content retained within the coal seam itself, and the influence imparted by the gas content within the coal seam. Furthermore, the approach thoroughly considers variations in the level of porosity development within the coal seam and its surrounding rock formations, as well as the occurrence of gas within these structures. The equivalent layer is classified into two distinct groups: the sandstone zone and the clay zone. The sandstone zone utilizes pertinent parameters pertaining to fine sandstone, whereas the clay zone distinguishes between clay rock and thick mudstone. The influencing factor considerations solely encompass natural elements, such as the coal seam’s occurrence and geological structure. The residual gas content employs either existing measured parameters or acknowledged experimental parameters specific to the coal seam. Based on this predictive approach, an intelligent auxiliary software (V1.0) for mine gas forecasting was devised. The software calculates the gas content of deep coal seams within the mine at intervals of 100 m × 100 m, subsequently fitting the contour lines of gas content across the entire area. The gas content predictions derived from this equivalent algorithm demonstrate robust adaptability to variations in gas content caused by construction activities, and the prediction results exhibit an acceptable level of error on-site. Notably, the prediction process is not constrained by the progress of tunnel engineering, ensuring that the prediction outcomes can accurately represent the distribution characteristics of deep coal seam gas content. After a year of application, the prediction results have consistently met on-site requirements, providing a scientific foundation for the implementation of effective gas prevention and control measures in the mining area. Furthermore, this approach can effectively guide the formulation of medium- and long-term gas prevention and control plans for mines.

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Analysis of the Pore Structure and Fractal Characteristics of Coal and Gas Outburst Coal Seams Based on Matrix Compression Correction

Cited by 3 publications

References 19 publications

The Fractal Characteristics of Ground Subsidence Caused by Subway Excavation

The Fractal Characteristics of Ground Subsidence Caused by Subway Excavation

Will greenhouse gas emissions increase with mining depth in coal mines? An analysis of gas occurrence under varying in-situ stress conditions

Research on an Equivalent Algorithm for Predicting Gas Content in Deep Coal Seams

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