Determination of earth pressure balance tunnel-related maximum surface settlement: a multivariate adaptive regression splines approach

Abstract

A major consideration in urban tunnel design is to estimate the ground movements and surface settlements associated with the tunnelling operations. Excessive ground movements may result in damage to adjacent buildings and utilities. Numerous empirical and analytical solutions have been proposed to relate the shield tunnel characteristics and surface/subsurface deformation. Numerical analyses, either 2D or 3D, have also been applied to such tunnelling problems. However, substantially fewer approaches have been developed for earth pressure balance (EPB) tunnelling. Based on instrumented data on ground deformation and shield operation from three separate EPB tunnelling projects in Singapore, this paper utilizes a multivariate adaptive regression splines (MARS) approach to establish relationships between the maximum surface settlement and the major influencing factors, including the operation parameters, the cover depth and the ground conditions. Since the method has the ability to map input to output patterns, MARS enables one to map all influencing parameters to surface settlements. The main advantages of MARS over other soft computing techniques such as ANN, RVM, SVM and GP are its capacity to produce a simple, easy-to-interpret model, its ability to estimate the contributions of the input variables, and its computational efficiency.