Simulating the Role of Transportation Infrastructure for Community Disaster Recovery

N. Blagojević, M. Didier, B. Stojadinović
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引用次数: 6

Abstract

Functional recovery of transportation infrastructure after a disaster is essential for community disaster resilience as the recovery of damaged community components depends on their accessibility for repair. This paper presents a community disaster recovery simulation that accounts for community component's accessibility for repair using a demand-supply framework. Considered components of a community are viewed as suppliers and/or users of various resources and services essential for community functionality, reflected in components’ supply and demand properties. Whenever the demand of a component is not met, that component ceases to operate, simulating interdependency effects. Similarly, recovery demand is attributed to damaged components, representing the amounts of resources and services (e.g., workers, machinery and transportation services) these components need to recover. The proposed framework is illustrated on a virtual community with 3600 inhabitants supported by several interdependent infrastructure systems. The results show that the transportation network damage slows down the recovery of the virtual community by preventing access to damaged components and reducing the ability of the community to mobilize available repair resources. Furthermore, the effect of such prolonged transportation system recovery on the damage-free infrastructure systems whose functionality was decreased due to their dependency on the affected infrastructure systems, is quantified.
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模拟交通基础设施在社区灾后恢复中的作用
灾后交通基础设施的功能恢复对社区抗灾能力至关重要,因为受损社区组成部分的恢复取决于其可修复性。本文提出了一个基于需求-供给框架的社区灾难恢复模拟模型,该模型考虑了社区构件的可达性。社区的考虑组件被视为社区功能所必需的各种资源和服务的供应商和/或用户,反映在组件的供需属性中。每当组件的需求没有得到满足时,该组件就会停止运行,从而模拟相互依赖的效果。同样,恢复需求归因于受损部件,代表这些部件需要恢复的资源和服务(例如工人、机械和运输服务)的数量。拟议的框架在一个拥有3600名居民的虚拟社区中得到说明,该社区由几个相互依存的基础设施系统提供支持。研究结果表明,交通网络的破坏阻碍了社区对受损部件的接触,降低了社区动员可用修复资源的能力,从而减缓了虚拟社区的恢复速度。此外,这种长时间的交通系统恢复对无损坏基础设施系统的影响是量化的,这些系统的功能由于依赖于受影响的基础设施系统而下降。
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来源期刊
CiteScore
3.00
自引率
10.00%
发文量
48
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