To investigate the protective effect of ground concrete cushion layers on buried pipelines used for water transmission, field rockfall impact tests were conducted by pre-burying multi-section bell-and-spigot concrete pipelines and casting in-situ concrete cushions on the ground. Combined with the DH8302 dynamic strain testing system, the spatial distribution characteristics of dynamic strain in the pipeline body and the variation law of earth pressure at the bell-and-spigot joints were analyzed. The LS-DYNA numerical simulation software was used to establish a detailed model of the rockfall impact test, and the reliability of the numerical model was verified by comparing simulation results with test results. By increasing the impact energy of rockfalls, the failure characteristics of buried bell-and-spigot concrete pipelines were studied. The influence mechanism of concrete cushion parameters (thickness and strength) on the protective effect was further analyzed by varying these parameters. The results show that under the condition of a burial depth of 2 m, unstable crack propagation in the pipeline body is more likely to cause leakage of bell-and-spigot concrete pipelines under rockfall impact. The peak tensile strain in the pipeline body decreases nonlinearly with the increase of cushion thickness and strength. The cushion thickness must exceed a critical value (15 cm) to significantly dissipate energy, and there is an optimal strength range (C30−C35). Excessive strength enhancement will reduce protective efficiency. Cushion thickness accounts for 74% of the protective effect contribution, indicating that the design principle of “geometry prior to material” should be followed. It is recommended to use a concrete cushion with a strength of C30−C35 and a thickness large than 0.2 m, which can significantly reduce the risk of pipeline impact damage and provide a quantitative design basis for pipeline protection in mountainous areas.

To achieve vibration control in tunnel blasting under complex geological conditions, clarifying the propagation laws of blasting velocities and accurately predicting blasting velocities are crucial aspects of safe blasting construction. Based on the multi-level surrounding rock and multi-scheme blasting engineering of the Houyu tunnel on the expressway, LS-DYNA was used to analyze the vibration attenuation characteristics of multi-level surrounding rock under various blasting methods. Field tests were conducted to validate the rationality of the numerical simulations. Finally, a velocity prediction model considering the influence of elevation differences was established by dimensional theory. The results show that as the blast center distance increases, the resultant velocity decays rapidly at first and then more slowly. The velocity of the surrounding rock above the tunnel in the excavated area is greater than that in the unexcavated area. There is a negative correlation between the strength grade of rock and the vibration velocity. The resultant velocities of the surrounding rock, from largest to smallest, are as follows: the reserved core soil method for step excavation, the single side drift method with right upper bench, and the single side drift method with left side drift. The attenuation rates of the resultant velocities, from largest to smallest, are as follows: the single side drift method with right upper bench, the reserved core soil method for step excavation, and the single side drift method with left side drift. When using the reserved core soil method for step excavation, the minimum safety distances for buried pipelines, building clusters, temples, and oil depots are 95, 81, 447 and 73 m, respectively. When using the single side drift method, the minimum safety distances for buried pipelines, building clusters, temples, and oil depots are 56, 72, 327 and 71 m, respectively.

The impact of fragmentation size and gradation on the stability and permeability of rockfill in hydraulic engineering is of great significance. Accurate prediction of fragmentation size has become a key focus in rock blasting research. In this study, a PSO-BPNN model is developed based on the Backpropagation Neural Networks(BPNN) with optimized network weights and biases using the Particle Swarm Optimization(PSO) algorithm. The model is trained and tested using representative blasting data, and its reliability and applicability are validated through its application in the Hunyuan Pumped Storage Power Station project in Shanxi. Results demonstrate that the PSO-BPNN model exhibits short computation time and high reliability for predicting fragmentation size, with a maximum relative error between the model output and actual average fragmentation size of 6.56%. Therefore, this model demonstrates high predictive accuracy and applicability, providing precise guidance for construction of rock-fill dams at the Hunyuan Pumped Storage Power Station in Shanxi province.