A Framework of Probabilistic Seismic Risk Analysis of Urban Shallow-Buried Tunnels Subjected to Active Fault Dislocations

ABSTRACTThis study develops a methodology for conducting a quantitative seismic risk assessment for shallow-buried tunnels that are induced by active fault dislocations. A case study for a tunnel crossing a strike-slip fault zone is performed using this method. The fault-tunnel crossing angle, the bedrock overburden thickness, the tunnel burial depth, the lining thickness, and the soil properties parameters are analysed in terms of their effects on the seismic responses, fragility curves, and seismic risks for the tunnels. This methodology could quantify the seismic risk of existing metro tunnels that pass through active fault zones, and could also assist in the establishment of a benchmark tunnel design for designing a tunnel that passes through an active fault zone.KEYWORDS: Probabilistic seismic risk analysisshallow-buried tunnelsactive fault dislocationstunnel seismic risktunnel fragility curves AcknowledgmentsWe acknowledge the financial support from the National Natural Science Foundation of China Grant (Nos. 51708460, 52278413), China Postdoctoral Science Foundation (Grant No. 2021M702718) and Sichuan Science and Technology Program (Nos. 2022NSFSC0475, 2021YFS0037).Disclosure StatementNo potential conflict of interest was reported by the authors.Data Availability StatementThe data that support the findings of this study are available from the corresponding author [Yin, Cheng], upon reasonable request.Additional informationFundingThe work was supported by the National Natural Science Foundation of China [52278413]; National Natural Science Foundation of China [52278331]. In addtion ,please add the funding from China Postdoctoral as: China Postdoctoral Science Foundation [2021M702718] Please also correct the acknowledgements part as: We acknowledge the financial support from the National Natural Science Foundation of China (Nos. 52278431, 52278331), China Postdoctoral Science Foundation (No. 2021M702718) and Sichuan Province Science and Technology Support Program (2022NSFSC0475).