This paper uses the three-dimensional numerical simulation method to analyze the first deep foundation pit project directly above the operating subway in a certain area. The monitoring data were compared with the numerical results to verify the accuracy of the numerical model, and then a series of analyses were performed. The soil beneath the tunnel is the most direct object of tunnel deformation caused by the excavation of deep foundation pits above the tunnel. The rebound deformation of the soil beneath the tunnel forces the tunnel to produce an upward deformation cooperatively. Therefore, after comparing and analyzing the prevention criteria of traditional excavation measures, which were not sufficient for this project, a new method of fortification is proposed for the foundation pit above the tunnel, which is called the micro-disturbance drill pipe pre-reinforcement method (PRM) for the soil beneath the tunnel. The comprehensive parameter analysis of the PRM shows that the PRM can effectively reduce the uplift value of the tunnel, and the reinforcement effect is obvious.

The subterranean environment of tunnels poses considerable uncertainty as tunnel structures are ensconced in soil, unlike their above-ground counterparts. This significantly complicates tunnel risk assessment during earthquakes. This study introduces a novel method that integrates multiple damage indices to evaluate the seismic resilience of tunnels. Initially, seismic attenuation is introduced to calculate earthquake exceedance probabilities for various tunnel damage indicators, employing finite element methods (FEM). A robustness evaluation criterion scale value is established based on the amalgamation of multiple tunnel damage indices. Standard Cloud Models are then generated utilising the robustness evaluation criteria. Subsequently, the independent and correlated weights of the robustness evaluation indices are determined using the CRITIC-G1 and decision-making trial and evaluation laboratory (DEMATEL) methods, respectively. A game theory (GT) method is then utilised to amalgamate and allocate weights to these robustness evaluation indices. The evaluation Cloud Models are subsequently generated using a backward cloud generator, based on the division of damage grades for the evaluation criteria and combination weights. Finally, the robustness grade is determined by comparing the similarities between the standard and evaluation Cloud Models. The repair time of the tunnel is quantified using a repair function based on robustness grades. The efficacy of the seismic resilience assessment method is discussed based on three hypothetical cases, providing valuable guidance for assessing the seismic resilience of underground structures.