Physical Model Experimental Study on the Coalface Overburden Movement Law on the End-slope of an Open-pit Mine

Due to technology and safety limitations, the amount of coal resources overlying slopes in open pit coal mines is immense. In recent years, this problem has gradually attracted the attention of researchers. How to realize the efficient recovery of the side overburden resources with the premise of ensuring the stability and safety of the slope has become an important topic for the development of opencast mining technology in China. To study the yield failure characteristics of coal pillars and the rock mass migration law of the end slope mining field under the mining condition of the end slope shearer, 2D/3D, integrated, simulation experimental equipment is developed based on similarity theory and efficient region theory. This equipment overcomes the technical problem that the internal failure of the rock mass is invisible and that deformation data are not easily obtained during the simulation of end slope coal mining on an existing experimental platform. Based on the engineering geological conditions of the Ordos mining area in China, a typical engineering geological model of the slope near the horizontal condition is constructed to simulate the process “formation of mining cave group -failure of support coal pillars - instability of slope rock mass”. Based on laser positioning technology and multiangle, oblique photography technology, a panoramic phase 3D laser scanner, high-resolution digital camera and deep space micromonitoring system are comprehensively employed to carry out the whole process tracking monitoring and analysis of the deformation and failure of the supporting coal pillars and slope rock mass. The experiment is verified by numerical simulation. The results show that under the experimental conditions, with an increase in mining cave depth, the vertical stress of the supporting coal pillar increases linearly. At a certain distance before reaching the end of the mining cave, the peak value is reached. At this time, the depth continues to increase, and the stress value decreases sharply. The vertical stress gradually decreases to the original rock stress after a certain distance beyond the end of the mining cave. A certain length of supporting coal pillar from the end of the mining cave will never collapse, which is approximately 2.5~3 times the width of the mining cave. The triggering condition of slope deformation and failure is under the combined action of dynamic and static loads. The actual stress of the supporting coal pillar in the deep part of the geometric centre along the slope of the mining cave group is greater than the ultimate stress, and then large discontinuous deformation of multiple adjacent coal pillars around the central coal pillar is caused by compressive shear failure. The boundary of the final collapse plane range of the roadway group is approximately a closed curve formed by two paraboloids, which are axisymmetric with the No. Ⅳ coal pillar and open opposite. The parabola opening in the shallow part of the slope area is small, and the parabola opening in the deep part of the slope area is large. There is a significant space-time correspondence between the failure of supporting coal pillars and the deformation of the slope surface. According to the failure process of the rock mass structure and the movement and deformation characteristics of the slope surface, the slope after failure can be divided into three areas, and the upper part of the slope is the key area of deformation and instability of the overlying rock mass in the end-slope mining field. The research results provide a theoretical basis for scientific monitoring and stability control of slope deformation coal mining conditions in open-pit mines.

Artificial Neural Network Potentials for Mechanics and Fracture Dynamics of Materials

Atomistic understanding of mechanics and failure of materials is the key for engineering and applications. Modeling accurately brittle failure with crack propagation in covalent crystals requires a quantum mechanics-based description of individual bond-breaking events for large system sizes. Machine Learned (ML) potentials have emerged to overcome the traditional, physics-based modeling tradeoff between accuracy and accessible time and length scales. Previous studies have shown successful applications of ML potentials for describing the structure and dynamics of molecular systems and amorphous or liquid phases of materials. However, their application to deformation and failure processes in materials is yet uncommon. In this study, we discuss apparent limitations of ML potentials to describe deformation and fracture under loadings and propose a way to generate and select training data for their employment in simulations of deformation and fracture of crystals. We applied the proposed approach to 2D crystal graphene, utilizing the density-functional tight-binding (DFTB) method for more efficient and extensive data generation in place of density functional theory (DFT). Then, we explore how the data selection affects the accuracy of the developed artificial neural network potential (NNP), indicating that only the errors in total energies and atomic forces are insufficient to judge the NNP’s reliability. Therefore, we evaluate and select NNPs based on their performance in describing physical properties, e.g., stress-strain curves and geometric deformation. In sharp contrast to popular reactive bond order potentials, our optimized NNP predicts straight crack propagation in graphene along both armchair and zigzag lattice directions, as well as higher fracture toughness of zigzag edge direction. Our study provides significant insight into crack propagation mechanisms at atomic scales and highlights strategies for NNP developments of broader materials.

The material ratio of roadside backfill body based on spatiotemporal law of ground pressure: a case study of Xingtai Mine, China

The material ratio of the roadside backfill body in gob-side entry retaining determines its mechanical properties, which plays an important role in the supporting effect of the roadway surrounding rock. In this paper, a similar material modeling is used to verify the spatiotemporal law of the ground pressure in the engineering case of dense solid backfilling mining in Xingtai Mine, China. Based on that law, the theoretical requirements for the bearing performance of the roadside backfill body are proposed. Finally, a material ratio that meets the theoretical requirements is obtained by compression test, and the deformation and failure characteristics of the backfill body with this ratio are analyzed. The results show that the maximum pressure of the backfill body measured in Xingtai Mine is 5.5 MPa, which is about 40 m away from the coal face, after 40m, the pressure of the backfill body will not increase anymore. The similar simulation test also proved that the ground pressure behind the coal face increases gradually and tends to be stable during the backfilling process, which shows certain spatiotemporal characteristics. Through the proportioning experiment, it is determined that the optimal material ratio of the roadside backfill body is gangue: fly ash: cement = 10:3:1, which meets the theoretical requirement that the strength of the roadside backfill body at any position is not less than the ground pressure at that position. The research results provide a reference for the engineering practice of gob-side entry retaining in dense backfilling mining.