Numerical and Experimental Investigation of the Impact of Close-Range Construction of Large-Section Tunnels on Existing Subway

Large-section tunnel construction using the mining method can significantly affect the operational safety of existing metro lines and ground stability, while their non-uniform settlement remains challenging to monitor comprehensively. In this study, the post-station section of a metro project in Chengdu was investigated to elucidate the vertical displacement and ground settlement behavior induced by a large-section tunnel undercrossing an existing metro line. A displacement reconstruction method integrating sparse-point monitoring with a radial basis function neural network (RBFNN) was developed to fit the full-field settlement distribution of both the existing line and the ground surface. A finite element model incorporating the existing shield tunnels, station structures, and the newly constructed mined tunnel was established, and the construction process was simulated. The numerical results indicated maximum settlements of 4.42 mm for the existing line and 4.37 mm for the ground surface, with fitting errors below 5.8% and 6.1%, respectively. Physical model tests further validated the approach, yielding maximum settlements of 0.86 mm and 1.01 mm for the existing line and ground surface, respectively, and an average fitting error below 3.5%. Both numerical and experimental findings confirmed that the induced displacements were within a controllable range and that the surrounding strata remained stable. The proposed method enables accurate and intuitive reconstruction of displacement distribution during under-crossing tunnel construction, reducing the number of required monitoring points while maintaining high fitting accuracy.