Sensitivity analysis of key parameters in Newtonian force monitoring of bedding rock landslides

The increasing demand for mineral resources has significantly deepened the excavation depths of open-pit mines. Large-scale deformation disasters caused by landslides on open pit mine slopes occur frequently, posing severe threats to human safety and mine operations. Therefore, research on monitoring and early warning technologies for open-pit mine landslides is of utmost importance. The emergence of the Newtonian force monitoring and early warning system has introduced an effective new approach for landslide monitoring in open-pit mines and has been successfully applied in the Nanfen open-pit mine, where it monitored landslides and issued early warnings up to 16 hours in advance. This study focuses on the bedding rock slope on the footwall of the Nanfen open pit mine, analyzing the geological conditions of the mining area. Through laboratory experiments, the mechanical parameters and mineral composition characteristics of the regional rock mass (greenschist) are obtained. A geological mechanical model of the landslide was then constructed, and the NPR anchor cable numerical analysis model was developed using FLAC3D numerical simulation software to analyze the variation patterns of Newtonian force during landslides. Based on this analysis, the influence of different NPR anchor cable parameters (including anchor cable inclination angle, spacing, and pre-tension force) on the Newtonian force was investigated. Comparative results indicate that the optimal design parameters for the NPR anchor cables are a 25° inclination angle, 40 m anchoring spacing, and a 400 kN pre-tension force. Additionally, it was found that the sensitivity of these three key parameters to the Newtonian force load, from highest to lowest, is as follows: pre-tension force, spacing, and inclination angle. This optimal configuration provides practical guidance for the design of NPR anchor cables in Newtonian force monitoring applications, offering theoretical and technical support for future landslide monitoring and early warning.