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Coal mining in China is increasingly moving towards deeper resources. In certain Carboniferous–Permian coal fields in North China, there is a typical problem of repeated mining over short distances and multiple coal seams, and the distance between the main coal seam and the mined shallow coal seam is relatively small. This leads to repetitive disturbance damage to the surrounding rock during closed‐coal seam mining. This was followed by more serious threats from water disasters. Therefore, it is particularly important to systematically study the disturbance and failure characteristics of rock masses under repeated mining conditions in multiple coal seams and to investigate repeated mining damage law and characteristics of the overlying rock of a close coal seam. This study focuses on six mining areas in the Jiyang coal mine. This study also predicts the damage height of the top and bottom slabs of mined No. 7 coal and main mined No. 10 coal based on an empirical formula. An on‐site investigation was conducted using downhole drilling and segmental water injection to determine the damage depths of the two seams. A numerical simulation was then conducted to study the height, displacement, and stress of the overlying rock damage caused by mining close to the coal seams. Changes in height, displacement, and stress of the overburden rock mining damage were also studied through numerical simulations. Results indicated the following: (1) The height of the plastic zone of the overburden rock increased by 6.25%, (2) maximum settlement displacement increased by 5.05%, and maximum horizontal displacement increased by 9%. It is important to note that these findings are objective and based solely on presented data. Repetitive disturbances with larger amplitudes caused a 27% change in horizontal displacement. (3) Maximum principal stress in the stress field decreased with the overall value of the vertical stress. The influence range increased slightly and the two sides of the hollow area at the open cutting eye and stopping line were also affected. These findings were obtained through numerical simulations. Stress concentration was more pronounced in the open‐cut eye and near‐the‐stop line. [ABSTRACT FROM AUTHOR]

In order to improve the rationality of the planning and layout of electric vehicle (EV) charging stations and avoid the situation of high investment and low efficiency, a planning method of EV charging station that considered users' dynamic charging demand was proposed. Firstly, the starting and ending points of user were obtained by using the travel theory, start and end point (origin-destination, OD) matrix method; a dynamic traffic road network model with time-varying traffic congestion was constructed. The Dijkstra algorithm was improved to plan the EV travel path, considering the real-time changes of ambient temperature and vehicle speed. Based on the influence of mileage and power consumption, a charging station selection model considering the dynamic charging needs of users was established; then, the M/M/c queuing theory method was used to configure the capacity of charging stations. The cost of construction, operation and maintenance of charging stations and the economic losses of EV users (including the sum of time loss and power loss) was minimized as the objective function, and a charging station planning model was established. Finally, taking the actual road conditions in the main urban area of a city as the planning area, the model was solved by iterative arrangement optimization combined with particle swarm algorithm. The results showed that the locations of the six planned charging stations in the area were evenly distributed, which could reduce the cost of users' charging journeys. And the optimal configuration number of charging piles could ensure charging satisfaction while minimizing the total economic cost of charging stations. The proposed planning method was reasonable and effective. [ABSTRACT FROM AUTHOR]

The Taihang–Lvliangshan region is located in the central part of the North China Craton (NCC), which has undergone significant reactivation and reconstruction during the Mesozoic–Cenozoic period. Documenting its long‐term uplift and exhumation history is critical for accurately characterizing the reformation extent of the NCC. In order to further reveal the Mesozoic and Cenozoic exhumation stages and spatial exhumation pattern of the Taihang–Lvliangshan, we present a comprehensive low‐temperature thermochronometric datasets from the region. The compilation revealed five distinct rapid exhumation episodes within the Taihang–Lvliangshan, including the Middle‐Late Jurassic (~160–150 Ma), Early Cretaceous (~120–110 Ma), Late Cretaceous (~100–60 Ma), Eocene (~50–40 Ma), and Late Oligocene–Early Miocene (~30–20 Ma). During the Middle–Late Jurassic, the Taihang–Lvliangshan underwent a strong thrusting deformation caused by the synthesis of northwestward subduction of the Palaeo‐Pacific Plate and southward subduction/collision of the Mongol–Okhotsk suture zone. Subsequently, rapid exhumation under an extensional tectonic environment occurred during the Early Cretaceous primarily owing to the subduction of the Palaeo‐Pacific Plate. During the Late Cretaceous, the collision between the Okhotomorsk Block and East Asia resulted in the regional northwest–southeast shortening and uplift of the Taihang–Lvliangshan. During the Eocene, normal fault activations were occurring throughout the range, likely owing to the change in the convergence rate and direction between the Palaeo‐Pacific Plate and East Asia. Another important exhumation event occurred during the Late Oligocene–Early Miocene period, which was likely attributed to the result of combined effects from both the India–Eurasia collision and Pacific Plate subduction. Furthermore, differential exhumation of the Taihang–Lvliangshan were clearly revealed according to the five separate E–W elevation–distance profiles of the Taihang–Lvliangshan. They displayed greater exhumation thicknesses at the southern regions than those along the northern regions, which can be explained by the development of the Shanxi Rift that began to form following the Oligocene–Miocene period. [ABSTRACT FROM AUTHOR]