Tunnels are critical infrastructure for the sustainable development of urban areas worldwide,especially for modern metropolises.This study investigates the effects of salient parameters,such as the soil conditions,tun...Tunnels are critical infrastructure for the sustainable development of urban areas worldwide,especially for modern metropolises.This study investigates the effects of salient parameters,such as the soil conditions,tunnel burial depth,tunnel construction quality,and aging phenomena of the lining,on the direct seismic losses of circular tunnels in alluvial deposits when exposed to ground seismic shaking.For this purpose,a practical approach is employed to probabilistically assess the direct losses of single tunnel segment with unit length,as well as of tunnel elements representative of the Shanghai Metro Lines 1 and 10,assuming various levels of seismic intensity.The findings of this study can serve as the basis for decision-making,seismic loss,and risk management based on the principles of infrastructure resilience.展开更多
Recent earthquakes have shown that tunnels are prone to damage,posing a major threat to safety and having major cascading and socioeconomic impacts.Therefore,reliable models are needed for the seismic fragility assess...Recent earthquakes have shown that tunnels are prone to damage,posing a major threat to safety and having major cascading and socioeconomic impacts.Therefore,reliable models are needed for the seismic fragility assessment of underground structures and the quantitative evaluation of expected losses.Based on previous researches,this paper presented a probabilistic framework based on an artificial neural network(ANN),aiming at the development of fragility curves for circular tunnels in soft soils.Initially,a two-dimensional incremental dynamic analysis of the nonlinear soil-tunnel system was performed to estimate the response of the tunnel under ground shaking.The effects of soil-structure-interaction and the ground motion characteristics on the seismic response and the fragility of tunnels were adequately considered within the proposed framework.An ANN was employed to develop a probabilistic seismic demand model,and its results were compared with the traditional linear regression models.Fragility curves were generated for various damage states,accounting for the associated uncertainties.The results indicate that the proposed ANN-based probabilistic framework can results in reliable fragility models,having similar capabilities as the traditional approaches,and a lower computational cost is required.The proposed fragility models can be adopted for the risk analysis of typical circular tunnel in soft soils subjected to seismic loading,and they are expected to facilitate decision-making and risk management toward more resilient transport infrastructure.展开更多
基金support of the National Natural Science Foundation of China(Grants No.52108381,51978517,52090082)the National Key R&D Program(Grant No.2021YFF0502200)the China Postdoctoral Science Foundation(Grants No.2022T150484,2021M702491).
文摘Tunnels are critical infrastructure for the sustainable development of urban areas worldwide,especially for modern metropolises.This study investigates the effects of salient parameters,such as the soil conditions,tunnel burial depth,tunnel construction quality,and aging phenomena of the lining,on the direct seismic losses of circular tunnels in alluvial deposits when exposed to ground seismic shaking.For this purpose,a practical approach is employed to probabilistically assess the direct losses of single tunnel segment with unit length,as well as of tunnel elements representative of the Shanghai Metro Lines 1 and 10,assuming various levels of seismic intensity.The findings of this study can serve as the basis for decision-making,seismic loss,and risk management based on the principles of infrastructure resilience.
基金financially supported by National Natural Science Foundation of China(Grant Nos.52108381,52090082,41772295,51978517)Innovation Program of Shanghai Municipal Education Commission(Grant No.2019-01-07-00-07-456 E00051)key innovation team program of innovation talents promotion plan by MOST of China(No.2016RA4059).
文摘Recent earthquakes have shown that tunnels are prone to damage,posing a major threat to safety and having major cascading and socioeconomic impacts.Therefore,reliable models are needed for the seismic fragility assessment of underground structures and the quantitative evaluation of expected losses.Based on previous researches,this paper presented a probabilistic framework based on an artificial neural network(ANN),aiming at the development of fragility curves for circular tunnels in soft soils.Initially,a two-dimensional incremental dynamic analysis of the nonlinear soil-tunnel system was performed to estimate the response of the tunnel under ground shaking.The effects of soil-structure-interaction and the ground motion characteristics on the seismic response and the fragility of tunnels were adequately considered within the proposed framework.An ANN was employed to develop a probabilistic seismic demand model,and its results were compared with the traditional linear regression models.Fragility curves were generated for various damage states,accounting for the associated uncertainties.The results indicate that the proposed ANN-based probabilistic framework can results in reliable fragility models,having similar capabilities as the traditional approaches,and a lower computational cost is required.The proposed fragility models can be adopted for the risk analysis of typical circular tunnel in soft soils subjected to seismic loading,and they are expected to facilitate decision-making and risk management toward more resilient transport infrastructure.
