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Microseismic monitoring technology has developed rapidly in recent years, and effectively evaluating the risk of water inrush from coal seam floor using microseismic monitoring is a research method with development potential, which is of great significance for ensuring the safe and efficient mining of coal resources. Based on the research background of the threat of Ordovician limestone water inrush during the mining process of the 9212 working face in Dongpang Coal Mine, this paper proposes a new method for evaluating floor spatial failure characteristics and water inrush risk based on microseismic monitoring. First, three research stages are established according to theoretical analysis and comprehensive geophysical exploration, and the response characteristics and temporal and spatial distribution of the microseismic events in the different stages are analysed. Second, the weighted coefficient of variation ( CV W ) and three floor factors (S, e , and θ ) are introduced as new risk evaluation indices for the risk of floor water inrush in the vertical direction. The comprehensive weight is determined based on the analytic hierarchy process (AHP) and the entropy weight method, and then the water inrush evaluation model is established by the vulnerability index method. For the water inrush risk of the floor in the horizontal direction, the stratified cumulative kernel density estimation method is employed to determine the degree of water inrush risk and distribution location of different layers from the perspective of microseismic frequency and microseismic energy. Finally, the potential location of the water-conducting channel in the three-dimensional space of the floor is successfully predicted in the analysed working face, and targeted grouting reinforcement and other treatment measures are effectively implemented to ensure the safe mining of the working face. Highlights: Based on microseismic monitoring, a new universally applicable method for analysing the characteristics of floor failure and evaluating the risk of water inrush is proposed. The Weighted Coefficient of Variation ( CV W ) and Three Floor Factors (S, e , and θ) are introduced to analyse the migration characteristics of floor strata and used as the new indices to evaluate the risk of water inrush in vertical direction. The method of stratified cumulative energy kernel density and stratified cumulative frequency kernel density evaluation (SC-KDE) is introduced to comprehensively determine the connectivity degree and range of transverse fractures in the horizontal direction. The potential location of the water-conducting channel in the floor space has been successfully predicted in field engineering. [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]

Automatic roadway formation by roof cutting (ARFRC) is a novel nonpillar mining method that has the potential to dramatically increase coal recovery while reducing the roadway excavation ratio. When this method is used below a fault influenced longwall goaf, large deformation and support failure occur in the roadway using conventional roadway formation techniques. In the study, the ARFRC method was tested in the Liliu mining area of China, which is characterized by goafs and faults. Field experiments and numerical modelling were used to evaluate the stability of the roadway by analysing the behaviour of overlying strata under the special geological condition. The results show that the surroundings of the formed roadway were greatly affected by the fault and the overlying coal pillar in the goaf. In the fault- and coal pillar-affected areas, the loads on the roadway roof increased by approximately 35% and 15%, respectively. According to the strata behaviour of the formed roadway surroundings, targeted support techniques for ARFRC were proposed, and the reliability of the support techniques were demonstrated by field practice. [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]

• A new method for evaluating the failure of roof and floor strata under dynamic load impact is proposed. • The Energy Variation Coefficient (CV E) and Two Spatial Factors (S and α) are introduced to study the energy difference and aggregation characteristics of microseismic events respectively. • The vulnerability index model is established based on the principal component - entropy method, and the risk zoning map is determined by ArcGIS. • The different microseismic response characteristics of roof and floor are distinguished, which can be used for targeted disaster prevention and control. The disaster induced by dynamic loads in the coal mining process seriously affects the safe production of coal mines. A new method for failure evaluation of roof and floor strata under dynamic load impact is proposed in this paper. The key roof strata breaking and periodic weighting experienced by the 9212 working face of the Dongpang Coal Mine in China while passing through the abandoned roadway is taken as the research background. Firstly, the research stages are divided through theoretical analysis and microseismic monitoring, and then the plane, profile distribution and spatial position relationship of microseismic events in different stages are analyzed. After that, the energy variation coefficient ( CV E) and two spatial factors (S and α) are introduced to analyse the difference in the migration characteristics and damage degree of roof and floor strata under dynamic load impact. Then, the comprehensive weight is determined by principal component analysis and entropy weight method, and the failure evaluation model is established based on vulnerability index method; Finally, the risk grade zoning map of three stages is drawn by using ArcGIS technology. The research shows that the angle factor α can better describe the development direction of roof and floor fissures. The area factor S combined with the energy variation coefficient CV E can explain the development speed of fissures and the damage degree of coal and rock mass. According to the failure evaluation model, the corresponding risk degree of roof and floor in different stages can be comprehensively evaluated. The research results can be used as a reference for targeted disaster prevention and control in similar situations, such as large-area roof collapse and floor water inrush. [ABSTRACT FROM AUTHOR]