Differences in the dynamic evolution of surface crack widths at different locations in the trench slope area and the mechanisms: a case study.

Coal seams were buried extremely shallowly in the trench slope area, which is prone to inducing surface cracks, seriously threatening the surface environment and mine safety production. The development of surface mining cracks varies at different locations in the trench slope area. In this research, we aimed to study the dynamic characteristics and laws of surface crack widths at different mining locations in the trench slope area and reveal the evolution mechanism of surface crack widths. Taking the 125,203 working face in Anshan Coal Mine in Shaanxi Province, China, as the geological prototype, we analyzed the full-cycle dynamic change law and planar distribution law of the surface crack widths in the trench slope area by combining the unmanned aerial vehicle remote sensing technology and field actual measurements and revealed the dynamic evolution mechanism of surface mining cracks in the trench area. The research results showed that the dynamic changes of surface crack widths varied at different locations of the slope. The surface crack width in the downslope area increased first and then stabilized with the advance of the working surface; the crack width at the bottom of the trench shows the dynamic change characteristic of increasing-decreasing-slightly increasing-stabilizing with the continuous advance of the working surface. The surface crack width in the upslope area showed the dynamic change of increasing-decreasing-stabilizing with the continuous advance of the working surface. Influenced by the surface morphology, the development mechanisms of surface mining cracks were different. The research results can provide practical guidance for selecting the best treatment time for surface cracks in different areas.

Study on the damage characteristics of overburden of mining roof in deeply buried coal seam.

The study of water-conducting fracture zone development height is key to the scientific prevention and control of water damage in mines. Based on the geological conditions of the Wenjiapo coal mine in Binchang, China, this paper investigates the development of water-conducting fracture zone in overlying bedrock during mining under large buried depth and huge thick aquifer by combining on-site well-location microseismic monitoring and laboratory similar material simulation. To overcome the limitation of the " limited outlook " of water-conducting fracture zone investigation, the spatial development characteristics of roof fissures in coal seam mining were determined by on-site " the underground - ground" combined microseismic monitoring and follow-up monitoring, and the development of overlying rock fracture under the large depth of burial was concluded. The fractures were mainly distributed in the upper part of the protective coal pillar on both sides of the working face, but less in the upper part of the working face, and primarily distributed in the protective coal pillar on the side of the working face and the adjacent mining area. To verify the accuracy of the conclusion, the overlying bedrock movement and deformation characteristics and the development process of the hydraulic fracture zone during coal seam mining were analyzed by simulating similar materials in the laboratory, using the monitored area as a prototype. The results show that the development height of the mining fracture zone obtained from microseismic monitoring is basically consistent with the simulation results of similar materials. The research finding have significant implications for the study of fracture distribution characteristics and the evolution law of mining overburden, and provide a foundation for scientific prevention and control of water damage on the roof.

GIS-based groundwater potential analysis using novel ensemble weights-of-evidence with logistic regression and functional tree models.

The aim of the current study was to produce groundwater spring potential maps using novel ensemble weights-of-evidence (WoE) with logistic regression (LR) and functional tree (FT) models. First, a total of 66 springs were identified by field surveys, out of which 70% of the spring locations were used for training the models and 30% of the spring locations were employed for the validation process. Second, a total of 14 affecting factors including aspect, altitude, slope, plan curvature, profile curvature, stream power index (SPI), topographic wetness index (TWI), sediment transport index (STI), lithology, normalized difference vegetation index (NDVI), land use, soil, distance to roads, and distance to streams was used to analyze the spatial relationship between these affecting factors and spring occurrences. Multicollinearity analysis and feature selection of the correlation attribute evaluation (CAE) method were employed to optimize the affecting factors. Subsequently, the novel ensembles of the WoE, LR, and FT models were constructed using the training dataset. Finally, the receiver operating characteristic (ROC) curves, standard error, confidence interval (CI) at 95%, and significance level P were employed to validate and compare the performance of three models. Overall, all three models performed well for groundwater spring potential evaluation. The prediction capability of the FT model, with the highest AUC values, the smallest standard errors, the narrowest CIs, and the smallest P values for the training and validation datasets, is better compared to those of other models. The groundwater spring potential maps can be adopted for the management of water resources and land use by planners and engineers.