Optimizing urban infrastructure resilience: Analyzing cascading failures and critical node dependencies through multilayer network models
As urbanization and industrialization progress, urban infrastructure systems grow increasingly complex, heightening their vulnerability to cascading failures from natural disasters and human-induced disruptions. Strengthening the resilience of these systems is critical for sustainable urban developm...
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| Format: | Article |
| Language: | English |
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KeAi Communications Co., Ltd.
2026-03-01
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| Series: | Journal of Safety Science and Resilience |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666449625000799 |
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| author | Cong Lu Jianjun She Hezhi Pan Zihao Guo Xuanling Zhou Zhijian Li |
| author_facet | Cong Lu Jianjun She Hezhi Pan Zihao Guo Xuanling Zhou Zhijian Li |
| author_sort | Cong Lu |
| collection | DOAJ |
| description | As urbanization and industrialization progress, urban infrastructure systems grow increasingly complex, heightening their vulnerability to cascading failures from natural disasters and human-induced disruptions. Strengthening the resilience of these systems is critical for sustainable urban development and sustaining residents’ quality of life. This study introduces a novel framework to analyze cascading failure propagation within infrastructure networks. Utilizing the implicit interdependency model, we construct a multilayer network that delineates interconnections and dependencies across infrastructure sectors. The PageRank algorithm is used to identify critical nodes by evaluating their network centrality, thereby highlighting key components within the system. Through simulations of random, PageRank-based, and betweenness-based attack scenarios, we explore failure dynamics and their propagation patterns. Additionally, we evaluate mitigation strategies, with the community periphery augmentation strategy proving most effective, enhancing resilience by linking peripheral nodes between communities. This research systematically connects the significance of key nodes to cascading effects, uncovering vulnerabilities and providing actionable insights for disaster response and recovery planning. |
| format | Article |
| id | doaj-art-4aa31bc618824debaef26e42dffae74a |
| institution | Kabale University |
| issn | 2666-4496 |
| language | English |
| publishDate | 2026-03-01 |
| publisher | KeAi Communications Co., Ltd. |
| record_format | Article |
| series | Journal of Safety Science and Resilience |
| spelling | doaj-art-4aa31bc618824debaef26e42dffae74a2025-08-25T04:14:50ZengKeAi Communications Co., Ltd.Journal of Safety Science and Resilience2666-44962026-03-017110024510.1016/j.jnlssr.2025.100245Optimizing urban infrastructure resilience: Analyzing cascading failures and critical node dependencies through multilayer network modelsCong Lu0Jianjun She1Hezhi Pan2Zihao Guo3Xuanling Zhou4Zhijian Li5College of Civil Engineering, Nanjing Tech University, Nanjing, 211816, China; Smart City Research Center, Nanjing Tech University, Nanjing, 211816, ChinaCollege of Civil Engineering, Nanjing Tech University, Nanjing, 211816, China; Smart City Research Center, Nanjing Tech University, Nanjing, 211816, ChinaCollege of Civil Engineering, Nanjing Tech University, Nanjing, 211816, ChinaCollege of Civil Engineering, Nanjing Tech University, Nanjing, 211816, ChinaCollege of Foreign Studies, Nanjing University, Nanjing, 210023, ChinaCollege of Civil Engineering, Nanjing Tech University, Nanjing, 211816, ChinaAs urbanization and industrialization progress, urban infrastructure systems grow increasingly complex, heightening their vulnerability to cascading failures from natural disasters and human-induced disruptions. Strengthening the resilience of these systems is critical for sustainable urban development and sustaining residents’ quality of life. This study introduces a novel framework to analyze cascading failure propagation within infrastructure networks. Utilizing the implicit interdependency model, we construct a multilayer network that delineates interconnections and dependencies across infrastructure sectors. The PageRank algorithm is used to identify critical nodes by evaluating their network centrality, thereby highlighting key components within the system. Through simulations of random, PageRank-based, and betweenness-based attack scenarios, we explore failure dynamics and their propagation patterns. Additionally, we evaluate mitigation strategies, with the community periphery augmentation strategy proving most effective, enhancing resilience by linking peripheral nodes between communities. This research systematically connects the significance of key nodes to cascading effects, uncovering vulnerabilities and providing actionable insights for disaster response and recovery planning.http://www.sciencedirect.com/science/article/pii/S2666449625000799Cascading failuresMulti-network analysisPagerank algorithmFailure propagation simulationRobust optimization |
| spellingShingle | Cong Lu Jianjun She Hezhi Pan Zihao Guo Xuanling Zhou Zhijian Li Optimizing urban infrastructure resilience: Analyzing cascading failures and critical node dependencies through multilayer network models Journal of Safety Science and Resilience Cascading failures Multi-network analysis Pagerank algorithm Failure propagation simulation Robust optimization |
| title | Optimizing urban infrastructure resilience: Analyzing cascading failures and critical node dependencies through multilayer network models |
| title_full | Optimizing urban infrastructure resilience: Analyzing cascading failures and critical node dependencies through multilayer network models |
| title_fullStr | Optimizing urban infrastructure resilience: Analyzing cascading failures and critical node dependencies through multilayer network models |
| title_full_unstemmed | Optimizing urban infrastructure resilience: Analyzing cascading failures and critical node dependencies through multilayer network models |
| title_short | Optimizing urban infrastructure resilience: Analyzing cascading failures and critical node dependencies through multilayer network models |
| title_sort | optimizing urban infrastructure resilience analyzing cascading failures and critical node dependencies through multilayer network models |
| topic | Cascading failures Multi-network analysis Pagerank algorithm Failure propagation simulation Robust optimization |
| url | http://www.sciencedirect.com/science/article/pii/S2666449625000799 |
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