Simulation and factor analysis for post-earthquake recovery of densely populated urban residential communities in China

被引:0
|
作者
Tao, Qian [1 ]
He, Zheng [1 ,2 ]
Li, Haijiang [3 ]
机构
[1] Dalian Univ Technol, Dept Civil Engn, Dalian, Peoples R China
[2] Dalian Univ Technol, State Key Lab Coastal & Offshore Engn, Dalian, Peoples R China
[3] Cardiff Univ, Cardiff Sch Engn, Cardiff, Wales
关键词
Buildings; earthquakes; functionality; infrastructure; residential; residents; resilience; simulation; utility networks; SEISMIC RESILIENCE;
D O I
10.1080/15732479.2023.2165116
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Post-earthquake recovery simulation is crucial for resilient community planning, and different interconnected factors are required to be considered holistically. To identify the key infrastructural characteristics affecting the recovery of densely populated urban residential communities (URCs) in China, a comprehensive methodology for resilience assessment and analysis is established on a systematic integration of multiple analysis tools (e.g. population-based functionality indicators, post-earthquake recovery simulations, and infrastructural dependence analyses). The methodology can consider the dependence among residential buildings, supporting buildings, and utility networks, as well as the relationships between their functionalities and resident outmigration; it also includes infrastructural repair sequences to allow flexible repair plans to be simulated. A case study is employed to conduct a factor analysis to clarify the impacts of three important infrastructural characteristics. Results show that improvements on the seismic performance of residential buildings facilitate recovery more significantly than utility networks, and the use of redundant utility pipelines can hardly impact the recovery of URCs. In long-term community recoveries, utility networks play more important role due to the cascading effects arising from the extension of repair durations. The proposed methodology can promote the understanding of community recovery, and the results demonstrate the effectiveness of identifying key factors.
引用
收藏
页码:1746 / 1764
页数:19
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