Prediction of the tunnel displacement induced by laterally adjacent excavations using multivariate adaptive regression splines

Excavations may cause excessive ground movements, resulting in potential damage to laterally adjacent tunnels. The aim of this investigation is to present a simple assessment technique using a multivariate adaptive regression splines (MARS) model, which can map the nonlinear interactions between the influencing factors and the maximum horizontal deformation of tunnels. A high-quality case history in Tianjin, China, is presented to illustrate the effect of excavation on the tunnel deformation and to validate the FEM. The hypothetical data produced by the FEM provide a basis for developing the proposed MARS model. Based on the proposed model, the independent and coupled effects of the input variables (i.e. the normalized buried depth of tunnels Ht/He, the normalized horizontal distance between tunnels and retaining structures Lt/He, and the maximum horizontal displacement of retaining structures, δRmax) on the tunnel response are analysed. The prediction precision and accuracy of the MARS model are validated via the artificial data and the collected case histories.