The focus of the study is to examine the undrained behavior of twin circular tunnels in anisotropic and nonhomogeneous clays. To consider the effect of anisotropic soil, the popular anisotropic undrained shear (AUS) failure criteria are adopted in the study while the nonhomogeneous behavior is represented by linearly increasing strength with depth. Using Broms and Bennermarks' stability number, this study investigates the dependence of the undrained stability number N on four dimensionless input parameters, namely the isotropic ratio (re), the undrained shear strength gradient (rho D/suTC0), the cover depth ratio (C/D), and the spacing ratio (S/D). The effects of these four design parameters on the failure mechanism are also examined graphically. After being verified with previously published works, the comprehensive 1080 numerical results are then utilized as the dataset to create several machine learning models, including artificial neural network (ANN), support vector machine (SVM), and multivariate adaptive regression splines (MARS). The evaluating process by optimizing hyper-parameters reveals that the MARS model is a top competitor, providing considerable regression accuracy with a simple predictive function. The sensitivity analysis has also uncovered that both rho D/suTC0 and C/D have significant influences on the undrained stability number N, while comparing to re and S/D. The present study would provide many practical insights to the problem of twin circular tunnels in anisotropic and nonhomogeneous clays.

Tunnels buried in liquefiable soils are prone to liquefaction-induced uplift damage during strong earthquakes. Studying the parameters that affect the liquefaction-induced uplift of tunnels is crucial for enhancing the seismic resilience of tunnels, minimizing potential damage, and ensuring the safety of critical infrastructure during strong earthquakes. This study investigates the effects of tunnel diameter (D), burial depth (H), and amplitude of input shaking at the base of the soil layer (amax) on the liquefaction-induced uplift of circular tunnels using numerical simulation. A comprehensive parametric study was conducted to investigate the effect of the H/D ratio and the value of amax on the dynamic responses, such as uplifts and internal forces in the lining of the tunnel. Using the numerical results, an empirical function was proposed to estimate the liquefaction-induced uplift of circular tunnels buried in liquefiable, loose soils. Finally, the results predicted by the proposed function were compared with those of a shaking table test and a centrifuge experiment. It has been demonstrated that the burial depth of a tunnel has the greatest impact on its seismic performance. Under identical input motion, increasing the burial depth of a tunnel with a 5-m diameter from 5 to 10 m resulted in a 270% increase in uplift and increased the internal forces in the tunnel lining, noticeably.

Seismic isolation is an effective strategy to mitigate the risk of seismic damage in tunnels. However, the impact of surface -reflected seismic waves on the effectiveness of tunnel isolation layers remains under explored. In this study, we employ the wave function expansion method to provide analytical solutions for the dynamic responses of linings in an elastic half -space and an infinite elastic space. By comparing the results of the two models, we investigate the seismic isolation effect of tunnel isolation layers induced by reflected seismic waves. Our findings reveal significant differences in the dynamic responses of the lining in the elastic half -space and the infinitely elastic space. Specifically, the dynamic stress concentration factor (DSCF) of the lining in the elastic half -space exhibits periodic fluctuations, influenced by the incident wave frequency and tunnel depth, while the DSCF in the infinitely elastic space remain stable. Overall, the seismic isolation application of the tunnel isolation layer is found to be less affected by surfacereflected seismic waves. Our results provide valuable insights for the design and assessment of the seismic isolation effect of tunnel isolation layers.

This paper presents a systematic study to develop the probabilistic seismic capacity models for circular tunnel linings. The uncertainties of lining parameters, soil properties, and ground motions are all considered. The Bayesian approach is used to estimate the model parameters based on the capacity samples simulated by a large number of refined dynamical numerical analyses. Finally, probabilistic capacity models are separately con-structed for circular tunnels at three performance levels. To demonstrate the properties of the proposed method, the capacity models are used to estimate the capacities and the fragility curves of a typical tunnel. It is concluded that (1) the probabilistic model can quickly estimate the probability distribution of capacity based on existing parameters, with the estimated median value closely approximating the numerical result; (2) the proposed probabilistic capacity models can be used to quickly derive fragility curves for specific tunnels, which facilitates safety evaluation and performance-based seismic design of tunnels.