This study employs similar simulation testing and discrete element simulation coupling to analyze the failure and deformation processes of a model coal seam's roof. The caving area of the overburden rock is divided into three zones: the delamination fracture zone, broken fracture zone, and compaction zone. The caving and fracture zones' heights are approximately 110 m above the coal seam, with a maximum subsidence of 11 m. The delamination fracture zone's porosity range is between 0.2 and 0.3, while the remainder of the roof predominantly exhibits a porosity of less than 0.1. In addition, the numerical model's stress analysis revealed that the overburden rock's displacement zone forms an 'arch-beam' structure starting from 160 m, with the maximum and minimum stress values decreasing as the distance of advancement increases. In the stress beam interval of the overburden rock, the maximum value changes periodically as the advancement distance increases. Based on a comparative analysis between observable data from on-site work and numerical simulation results, the stress data from the numerical simulation are essentially consistent with the actual results detected on-site, indicating the validity of the numerical simulation results.

Various methods of longwall full mining with partial filling have been extensively researched to satisfy the specific mining needs of pressurized-coal and residual-coal resources. This study introduces three longwall partial-filling-mining techniques: room–pillar filling mining, parallel-strip filling mining, and vertical-strip filling mining. Numerical simulations are employed to evaluate the efficacy of these methods. The findings indicate that vertical-strip filling mining results in minimal surface deformation and a more uniform distribution of displacements. In practical operations, the effectiveness of filling largely depends on the choice of filling technology and materials. The research further includes an optimization analysis of the filling technology, emphasizing the composition of the coal-gangue-paste filling system and the refinement of its components. Additionally, the study aims to explore the optimization analysis of filling materials, specifically focusing on performance-optimization methods. The experimental results illustrate that optimizing the filling materials can enhance the performance of filling paste, improving both early-stage and long-term compressive strength. Moreover, the paper examines the quantitative characterization of paste-filling-mining subsidence at various stages in conjunction with theoretical knowledge. Subsequently, mining-subsidence-control measures are recommended to address the primary deformation factors across different stages. Through an in-depth examination of filling-method designs, enhancements in filling technology, and predictions regarding filling-mining subsidence, this research offers valuable insights for optimizing longwall partial-filling-mining methods.

The research in this paper relies on the Baochang shield construction section of Jinan Metro Line R2 and uses MIDAS GTS and MIDAS GEN to construct a three-dimensional calculation model to numerically simulate the process of shield tunneling through abrupt geology. The main research focuses on surface settlement and building deformation during excavation, as well as monitoring of building deformation and surface settlement after adopting settlement control measures. The research results are as follows: The maximum settlement of tunnel excavation from hard rock to soft rock and from soft rock to hard rock occurs at the longitudinal center of the tunnel, with values of 1.66 mm and 4.82 mm. The excavation direction has a significant impact on surface deformation. The tunnel is excavated from hard rock to soft rock and the maximum deformation values in the vertical and horizontal directions of the building are 2.04 mm and 1.92 mm. After adopting settlement control measures, surface settlement and deformation of buildings were monitored. The monitoring results showed that the deformation monitoring values of the surface and buildings, after adopting engineering measurements, were lower than the values of numerical simulation. This indicates that the engineering control measures adopted can effectively constrain surface settlement and the deformation of buildings.

Surrounding rock pressure, water pressure, and joint roughness are the important factors that affect the fractured rock mass seepage. It is of great significance to quantify the influence of these factors through experiments. In this study, rock fracture joint surfaces were measured. Next, 3D coordinates of joint surfaces were extracted with using the Geomagic software, and joint roughness was described using the mean variance of protrusion height and equidistant fluctuation angle, which were acquired through calculation. Stress-seepage coupling test was then conducted on the samples on a triaxial apparatus, and the effects of confining stress and water pressure on the permeability of single-fracture rock were investigated. On the basis of the relationship between the parameters in data fitting expression and the mean variance of protrusion height and equidistant fluctuation angle, the calculation formula of the permeability coefficient including joint roughness, confining pressure, and seepage pressure difference was derived.

Accurately predicting the height of water flowing fractured zone is of great significance to coal mine safety mining. In recent years, most mines in China have entered deep mining. Aiming at the problem that it is difficult to accurately predict the height of water flowing fractured zone under the condition of large mining depth, the mining depth, height mining, inclined length of working face and coefficient of hard rock lithology ratio are selected as the main influencing factors of the height of water flowing fractured zone. The relationship between various factors and the height of water flowing fractured zone is analyzed by SPSS software. Based on the data mining tool Weka platform, Bayesian classifier, artificial neural network and support vector machine model are used to mine and analyze the measured data of water flowing fractured zone, and the detailed accuracy, confusion matrix and node error rate are compared. The results show that, the accuracy rate of instance classification of the three models is greater than 60%. The accuracy of the artificial neural network model is the highest and the node error rate is the lowest. In general, the training effect of the artificial neural network model is the best. By predicting engineering examples, the prediction accuracy of the model reaches 80%, and a good prediction effect is obtained. The height prediction system of water flowing fractured zone is developed based on VB language, which can provide a reference for the prediction of the height failure grade of water flowing fractured zone.