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张陈龙, 张东明, 黄忠凯, 黄宏伟. 考虑地震强度不确定性的车站韧性评估方法[J]. 岩土工程学报, 2025, 47(1): 164-172. DOI: 10.11779/CJGE20231153
引用本文: 张陈龙, 张东明, 黄忠凯, 黄宏伟. 考虑地震强度不确定性的车站韧性评估方法[J]. 岩土工程学报, 2025, 47(1): 164-172. DOI: 10.11779/CJGE20231153
ZHANG Chenlong, ZHANG Dongming, HUANG Zhongkai, HUANG Hongwei. Resilience assessment method for subway stations considering uncertainty of seismic intensity[J]. Chinese Journal of Geotechnical Engineering, 2025, 47(1): 164-172. DOI: 10.11779/CJGE20231153
Citation: ZHANG Chenlong, ZHANG Dongming, HUANG Zhongkai, HUANG Hongwei. Resilience assessment method for subway stations considering uncertainty of seismic intensity[J]. Chinese Journal of Geotechnical Engineering, 2025, 47(1): 164-172. DOI: 10.11779/CJGE20231153

考虑地震强度不确定性的车站韧性评估方法

Resilience assessment method for subway stations considering uncertainty of seismic intensity

  • 摘要: 地铁车站作为地下交通的枢纽,是社会经济交流和人员交往的重要组成部分,但其同时也面临着诸多灾害风险。以前包括地震在内的灾害,会对地下交通网络造成严重后果,也对城市功能造成重大损失。因此,地铁车站等关键交通枢纽的韧性评估对于提高城市安全性和维护其功能至关重要。提供了一个考虑地震强度不确定性的综合韧性评估框架,用于评估浅埋地铁车站在地震灾害下的鲁棒性和快速恢复能力。该框架方法利用有限元软件,建立相关地铁车站数值模型;然后,通过所选择的地震动展开大量数值分析,以便生成关于峰值地面加速度(PGA)的地铁车站易损性函数;接着利用蒙特卡洛模拟进一步量化地震动强度不确定性,并最终确定车站在各个损伤阶段的概率。最终,通过联立地铁车站损伤概率与经济损失关系,考虑地铁车站的恢复路径和可恢复性,完成韧性评估。本研究通过该韧性评估框架和所计算出的韧性指标R,评价和讨论了性能恢复模型和场地条件对车站抗震韧性的影响。这项工作可以帮助地铁网络基于韧性的设计和管理,以支持对地震灾害的适应,从而促进相关决策者关于资源的有效分配。

     

    Abstract: Subway stations serve as the vital hubs in underground transportation systems and play a critical role in facilitating social and economic exchanges as well as interpersonal interactions. However, these stations are also susceptible to various disaster risks. The historical incidents, including earthquakes, have had severe consequences on underground transit networks, leading to significant disruptions in urban functionality. Therefore, assessing the resilience of key transportation hubs such as subway stations is crucial for enhancing the urban safety and ensuring their continued functionality. The objective of this study is to provide a comprehensive resilience assessment framework for shallow-buried subway stations to evaluate their robustness and rapid recovery capability, considering the uncertainty of seismic intensity. The proposed framework involves the utilization of finite element software to build numerical models for the relevant subway stations. Subsequently, a large number of numerical analyses are conducted using the selected seismic motions to derive vulnerability functions for the subway stations based on the peak ground acceleration. Additionally, the Monte Carlo simulations are employed to further quantify the uncertainty of seismic motion intensity, ultimately determining the probabilities of damage of the subway station damage at various stages. By integrating the probabilities of damage with the relationship between damage and economic loss and considering the recovery paths and recoverability of the subway stations, a comprehensive resilience assessment is achieved. The impacts of performance recovery models, site conditions and disaster preparedness time on the seismic resilience of the subway stations are evaluated and discussed using the derived resilience index R. This research contributes to the design and management of subway networks based on resilience, enabling them to adapt to seismic disasters and facilitating the effective allocation of resources by the relevant decision-makers.

     

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