论文标题

关键结构,基础设施和社区的韧性

Resilience of critical structures, infrastructures and communities

论文作者

Cimellaro, Gian Paolo, Noori, Ali Zamani, Kammouh, Omar, Terzic, Vesna, Mahin, Stephen A.

论文摘要

近年来,与缓解灾难和管理有关的弹性概念已被引入工程领域。但是,建筑环境只是支持社区功能的一个元素。在灾难期间和之后保持社区功能(定义为弹性)受多个组成部分的影响。该报告总结了在灾难恢复能力领域,政治上的DI Torino和加利福尼亚大学伯克利分校之间持续合作的前两年的研究活动。第1章侧重于灾难恢复能力的经济方面,并向旧金山湾区的应用。第2章分析了使用基础隔离系统来提高医院和学校建筑的弹性的选择;第3章调查了采用离散事件仿真模型和元模型来衡量医院急诊科的弹性的可能性;第4章将在第3章中开发的元模型应用于旧金山湾区的医院网络,显示了该模型的潜力用于设计目的,第5章使用了一份问卷,并结合了阶乘分析来评估医院的弹性;第6章应用基于代理模型的概念来分析紧急情况下社会技术网络的性能。显示了两种应用:一个博物馆和一个火车站;第7章将恢复脆弱性定义为测量恢复过程中不确定性的工具;第8章侧重于使用不同空间尺度的时间网络建模基础架构相互依赖。

In recent years, the concept of resilience has been introduced to the field of engineering as it relates to disaster mitigation and management. However, the built environment is only one element that supports community functionality. Maintaining community functionality during and after a disaster, defined as resilience, is influenced by multiple components. This report summarizes the research activities of the first two years of an ongoing collaboration between the Politecnico di Torino and the University of California, Berkeley, in the field of disaster resilience. Chapter 1 focuses on the economic dimension of disaster resilience with an application to the San Francisco Bay Area; Chapter 2 analyzes the option of using base-isolation systems to improve the resilience of hospitals and school buildings; Chapter 3 investigates the possibility to adopt discrete event simulation models and a meta-model to measure the resilience of the emergency department of a hospital; Chapter 4 applies the meta-model developed in Chapter 3 to the hospital network in the San Francisco Bay Area, showing the potential of the model for design purposes Chapter 5 uses a questionnaire combined with factorial analysis to evaluate the resilience of a hospital; Chapter 6 applies the concept of agent-based models to analyze the performance of socio-technical networks during an emergency. Two applications are shown: a museum and a train station; Chapter 7 defines restoration fragility functions as tools to measure uncertainties in the restoration process; and Chapter 8 focuses on modeling infrastructure interdependencies using temporal networks at different spatial scales.

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