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城市互联基础设施网络的韧性评估

Resilience assessment of urban connected infrastructure networks.

作者信息

Liu Wei, Huang XiaoQin, Liang Baojun

机构信息

School of Civil Engineering and Architecture, East China Jiaotong University, Nanchang, 330013, China.

Jiangxi Provincial Key Laboratory of Traffic Infrastructure Safety, East China Jiaotong University, Nanchang, 330013, China.

出版信息

Sci Rep. 2025 Jun 5;15(1):19770. doi: 10.1038/s41598-025-03730-0.

Abstract

With the development of society, infrastructures have not only expanded in size, but have also formed complex dependencies among themselves, constituting closely interconnected network systems. At present, it has become a global consensus to enhance the resilience of infrastructure networks. In order to deeply understand how the interconnections among urban infrastructure systems affect the resilience performance of cities, this study adopts a combination of theoretical discussions and Python simulation techniques to systematically analyze the resilience dynamics of urban connected infrastructure networks when they encounter external perturbations. First, based on the principle of resilience construction and the multilayer network theoretical framework, we constructed a linkage model of the urban infrastructure network. Subsequently, focusing on the functional linkage perspective, we simulate the cascading failure mechanism of the network under three different external shocks, and construct a resilience assessment model for the urban infrastructure network with the help of the curve method of infrastructure system performance assessment. Finally, an empirical study is conducted with a county in Jiangxi Province as a specific case.

摘要

随着社会的发展,基础设施不仅规模不断扩大,而且相互之间形成了复杂的依赖关系,构成了紧密相连的网络系统。目前,增强基础设施网络的韧性已成为全球共识。为了深入了解城市基础设施系统之间的相互连接如何影响城市的韧性表现,本研究采用理论探讨与Python模拟技术相结合的方法,系统地分析城市互联基础设施网络在遭遇外部扰动时的韧性动态。首先,基于韧性建设原理和多层网络理论框架,构建了城市基础设施网络的联动模型。随后,从功能联动的角度出发,模拟了网络在三种不同外部冲击下的级联故障机制,并借助基础设施系统性能评估的曲线法构建了城市基础设施网络的韧性评估模型。最后,以江西省的一个县为例进行了实证研究。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7072/12141532/d3960c31d4c2/41598_2025_3730_Fig1_HTML.jpg

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