Due to their distinct geotechnical and structural features, soft rock tunnels pose serious issues because of their seismic sensitivity. These tunnels, often constructed in formations with lower shear strength and higher deformability, are particularly susceptible to damage during earthquakes. Fragility curves, which graphically represent the probability that a structure may sustain damage up to or beyond a particular threshold as a function of seismic intensity, are essential tools for evaluating the seismic resilience of these infrastructures. This research looks closely at the use of fragility curves to assess the seismic vulnerability of soft rock tunnels. Exploring the fundamental concepts and methodologies involved in constructing fragility curves, including seismic hazard analysis, structural modeling, damage state definition, data collection and statistical analysis is looked at first. The review highlighted the integration of soft rock characteristics such as strength and deformation properties into the fragility assessment process. Key developments in the topic are covered such as how machine learning and Bayesian inference might improve the precision and usefulness of fragility curves. The paper identified key findings such as the high sensitivity of fragility curves to geotechnical properties and seismic intensity levels and emphasized the importance of accurate data collection and model calibration. Important gaps in seismic risk evaluations are filled by integrating cutting-edge methodologies, such as Bayesian inference and real-time machine learning models that clarify the seismic behaviour of soft rock tunnels in the real world. For the purpose of strengthening earthquake-resistant infrastructure in earthquake-prone areas, engineers, scholars and policymakers are given practical insights.

The polyurethane foam (PU) compressible layer is a viable solution to the problem of damage to the secondary lining in squeezing tunnels. Nevertheless, the mechanical behaviour of the multi-layer yielding supports has not been thoroughly investigated. To fill this gap, large-scale model tests were conducted in this study. The synergistic load-bearing mechanics were analyzed using the convergenceconfinement method. Two types of multi-layer yielding supports with different thicknesses (2.5 cm, 3.75 cm and 5 cm) of PU compressible layers were investigated respectively. Digital image correlation (DIC) analysis and acoustic emission (AE) techniques were used for detecting the deformation fields and damage evolution of the multi-layer yielding supports in real-time. Results indicated that the loaddisplacement relationship of the multi-layer yielding supports could be divided into the crack initiation, crack propagation, strain-hardening, and failure stages. Compared with those of the stiff support, the toughness, deformability and ultimate load of the yielding supports were increased by an average of 225%, 61% and 32%, respectively. Additionally, the PU compressible layer is positioned between two primary linings to allow the yielding support to have greater mechanical properties. The analysis of the synergistic bearing effect suggested that the thickness of PU compressible layer and its location significantly affect the mechanical properties of the yielding supports. The use of yielding supports with a compressible layer positioned between the primary and secondary linings is recommended to mitigate the effects of high geo-stress in squeezing tunnels. (c) 2024 Institute of Rock and Soil Mechanics, Chinese Academy of Sciences. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/ 4.0/).