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在目标攻击加剧的强烈洪灾下城市交通网络的弹性。

Resilience of Urban Transport Network-of-Networks under Intense Flood Hazards Exacerbated by Targeted Attacks.

机构信息

Sustainability and Data Sciences Laboratory, Department of Civil and Environmental Engineering, Northeastern University, Boston, MA, USA.

Computing and Analytics Division, National Security Directorate, Pacific Northwest National Laboratory, Richland, WA, USA.

出版信息

Sci Rep. 2020 Jun 25;10(1):10350. doi: 10.1038/s41598-020-66049-y.

Abstract

Natural hazards including floods can trigger catastrophic failures in interdependent urban transport network-of-networks (NoNs). Population growth has enhanced transportation demand while urbanization and climate change have intensified urban floods. However, despite the clear need to develop actionable insights for improving the resilience of critical urban lifelines, the theory and methods remain underdeveloped. Furthermore, as infrastructure systems become more intelligent, security experts point to the growing threat of targeted cyber-physical attacks during natural hazards. Here we develop a hypothesis-driven resilience framework for urban transport NoNs, which we demonstrate on the London Rail Network (LRN). We find that topological attributes designed for maximizing efficiency rather than robustness render the network more vulnerable to compound natural-targeted disruptions including cascading failures. Our results suggest that an organizing principle for post-disruption recovery may be developed with network science principles. Our findings and frameworks can generalize to urban lifelines and more generally to real-world spatial networks.

摘要

自然危害,包括洪水,可能会引发相互依存的城市交通网络(NoNs)的灾难性故障。人口增长提高了交通需求,而城市化和气候变化则加剧了城市洪水。然而,尽管显然需要为提高关键城市生命线的弹性制定可行的见解,但理论和方法仍然不够发达。此外,随着基础设施系统变得更加智能化,安全专家指出,在自然灾害期间,针对网络物理攻击的威胁日益增加。在这里,我们为城市交通 NoNs 开发了一个基于假设的弹性框架,并在伦敦铁路网络(LRN)上进行了演示。我们发现,旨在最大化效率而不是鲁棒性的拓扑属性使网络更容易受到包括级联故障在内的复合自然目标破坏。我们的结果表明,可以用网络科学原理来开发灾难后的恢复组织原则。我们的发现和框架可以推广到城市生命线,更广泛地推广到现实世界的空间网络。

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