ArticleJournal of the Royal Society, Interface2019
Robust component: a robustness measure that incorporates access to critical facilities under disruptions.
Article in Journal of the Royal Society, Interface, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
8 citing papers in PubMed.
- Modeling Culvert Failure and Community Accessibility Impacts During Hazards.Risk analysis : an official publication of the Society for Risk Analysis · 2026Article
- Conceptual Design and Additive Manufacturing of a Bidirectional Gradient Gyroid Structure for Tibial Stem.Annals of biomedical engineering · 2025Article
- Limitations and considerations of using composite indicators to measure vulnerability to natural hazards.Scientific reports · 2024Article
- Characterizing equitable access to grocery stores during disasters using location-based data.Scientific reports · 2022Article
- Local impacts on road networks and access to critical locations during extreme floods.Scientific reports · 2022Article
- Quantifying community resilience based on fluctuations in visits to points-of-interest derived from digital trace data.Journal of the Royal Society, Interface · 2021Article
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Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The objective of this paper is to integrate the post-disaster network access to critical facilities into the network robustness assessment, considering the geographical exposure of infrastructure to natural hazards. Conventional percolation modelling that uses generating function to measure network robustness fails to characterize spatial networks due to the degree correlation. In addition, the giant component alone is not sufficient to represent the performance of transportation networks in the post-disaster setting, especially in terms of the access to critical facilities (i.e. emergency services). Furthermore, the failure probability of various links in the face of different hazards needs to be encapsulated in simulation. To bridge this gap, this paper proposed the metric robust component and a probabilistic link-removal strategy to assess network robustness through a percolation-based simulation framework. A case study has been conducted on the Portland Metro road network during an M9.0 earthquake scenario. The results revealed how the number of critical facilities severely impacts network robustness. Besides, earthquake-induced failures led to a two-phase percolation transition in robustness performance. The proposed robust component metric and simulation scheme can be generalized into a wide range of scenarios, thus enabling engineers to pinpoint the impact of disastrous disruption on network robustness. This research can also be generalized to identify critical facilities and sites for future development.
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Registered trials
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