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Automatic roadway formation by roof cutting is a sustainable nonpillar mining method that has the potential to increase coal recovery, reduce roadway excavation and improve mining safety. In this method, roof cutting is the key process for stress relief, which significantly affects the stability of the formed roadway. This paper presents a directionally single cracking (DSC) technique for roof cutting with considerations of rock properties. The mechanism of the DSC technique was investigated by explicit finite element analyses. The DSC technique and roof cutting parameters were evaluated by discrete element simulation and field experiment. On this basis, the optimized DSC technique was tested in the field. The results indicate that the DSC technique could effectively control the blast-induced stress distribution and crack propagation in the roof rock, thus, achieve directionally single cracking on the roadway roof. The DSC technique for roof cutting with optimized parameters could effectively reduce the deformation and improve the stability of the formed roadway. Field engineering application verified the feasibility and effectiveness of the evaluated DSC technique for roof cutting. Highlights: A directionally single cracking (DSC) technique for roof cutting in automatic roadway formation of the non-pillar mining method is proposed. The mechanism of the DSC technique to achieve single cracking relies on effective control of the blast-induced stress. DEM simulation and field experiments are effective methods to evaluate the DSC and roof cutting parameters to improve the stability of the roadway surroundings. [ABSTRACT FROM AUTHOR]

Gob‐side entry formation by roof cutting is a new technology for no pillar coal mining, which can maximize coal resources and reduce roadway drivage ratio. However, the mechanical behavior of the formed entry is complex while it is crucial to ensure the stability of the entry for mining safety. This paper proposed a machine learning‐based method for predicting the stability of the formed entry, which combined artificial neural network (ANN) with particle swarm optimization (PSO) algorithm or genetic optimization (GO) algorithm. The data set from 75 coal mining faces from 2009 to 2022 was employed to train and test the models. A descriptive variable of dynamic unstable distance was introduced to evaluate the stability state of the formed entry and six other parameters were chosen as influence parameters. The two intelligent models were compared with each other to have a comprehensive assessment. Model assessment indices such as R2, mean absolute error, mean absolute percentage error, and root mean square error were used to evaluate the accuracy of the models. The results of both developed models are promising, and the predictive accuracy of the PSO‐ANN model is higher than that of the GO‐ANN model. Through sensitivity analyses, it has been found that the coal seam thickness and roof rock hardness are the most important parameters for influencing entry stability. The developed method provides a practical tool for the prediction of entry stability and the optimization of entry design. [ABSTRACT FROM AUTHOR]

• Using spring sets and built-in water bag to simulate aquifer; embedding guide lift hose and branch conduit as prefabricated water-conducting channel; Using "cutting-support-blocking" integrated device to simulate key equipment of ARFMP. • The floor failure characteristics of ARFMP are obtained and its effectiveness in preventing water inrush is verified. • An engineering treatment scheme combining ARFMP and floor regional control is proposed, and reliability of the model test results is verified after field application. The coal mining in North China is seriously threatened by floor water inrush from the Ordovician limestone, so it is particularly important to explore failure characteristics. Automatic roadway formation mining without pillars (ARFMP) provides an effective method for reducing floor failure. To explore failure characteristics above confined water, a two-dimensional model test system is built up. Such a system can be applied to compare the difference of floor failure between ARFMP above confined water and traditional retained coal pillar mining, and to intuitively analyze the lifting law of confined water under dynamic disturbance. The core features of this system include the customized spring sets and water bag adopted as materials to simulate the floor aquifer, the guide lift hose and branch conduit used as the lifting channel of confined water, and the flow rate and cumulative volume monitored in real time. The customized "cutting-support-blocking" integrated device is the key equipment to simulate ARFMP. Then, the model test is conducted on a typical engineering case. By comparing stress, displacement, and water inrush characteristics of floor in different areas, failure characteristics of the roof-cutting side, the middle of working face, the collapse column area, and the coal pillar side were obtained, and it was clarified that ARFMP can effectively prevent floor water inrush. According to the results of model test, a comprehensive treatment scheme combining ARFMP with the floor regional control is proposed to ensure the safe mining of working face. [ABSTRACT FROM AUTHOR]