No abstract

In order to alleviate the relationship between mining and roadway, the 3204 working face and the 3206 roadway in Shanxi Taitou coal mine are taken as an example, and the width of mining and the support parameters of mining while reversing mining and excavation under dynamic pressure are optimized. The research includes field investigations, theoretical analysis, numerical simulation, and field tests. Based on the characteristics of roof fracture and the distribution of coal pillar stresses that determine the coal pillar is 18.7 m wide, the control scheme of mining while reversing mining and excavation was developed; the stress of coal pillar and the characteristics of roadway deformation and failure are summarized. By means of FLAC3D numerical simulation software, the influence of coal pillar widths and different mining positions on the stability of roadway surrounding rock are discussed. The asymmetric support structure of trapezoidal roadway is proposed as the core support, and the support scheme of dense bolts and anchor cables is proposed. The support of the 3206 return airway is composed of bolt, anchor cable, and anchor mesh, combined with M-shaped steel belt and steel beam. Through the research on the current situation of roadway support, the support scheme is optimized to make the 3206 return airway meet the production requirements, which provides a new breakthrough for roadway support under dynamic pressure in deep mines in China.

The advancement of artificial intelligence (AI) has transformed almost all sectors. It has been used to optimize operations for cost reduction, time management, and anomaly detection to reduce operational risk. Despite the emergence of hybrid AI models, the mining industry has not given significant attention. In mining, blasting is frequently used both on the surface and underground. It is considered to be the most cost-effective method. Although the efficiency of mine blasting has improved significantly over the last few decades, blasting still has some inevitable limitations. Blasting risks such as blast-induced ground vibration, flying rock, overbreak, and backbreak caused by blasting should be considered prior to the blasting design stage. Therefore, this study aims to assess the limitations and strengths of each existing AI model and to address the potential development of AI approaches in the mining industry.