ArticleScientific reports2022
Edge betweenness centrality as a failure predictor in network models of structurally disordered materials.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Edge percolation centrality: A new measure to quantify the influence of edges during percolation in networks.PloS one · 2025Article
- A review on molecular simulations for the rupture of cross-linked polymer networks.Science and technology of advanced materials · 2025Review
- Tuning load redistribution and damage near heterogeneous interfaces.Scientific reports · 2024Article
- Advancing the complex adaptive systems approach to enterprise risk management with quantified risk networks (QRNs).Scientific reports · 2024Article
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Authors and funding
3 authors.
Funding
Abstract
Network theoretical measures such as geodesic edge betweenness centrality (GEBC) have been proposed as failure predictors in network models of load-driven materials failure. Edge betweenness centrality ranks which links are significant, based on the fraction of shortest paths that pass through the links between network nodes. We study GEBC as a failure predictor for two-dimensional fuse network models of load transmission in structurally disordered materials. We analyze the evolution of edge betweenness centrality in the run-up to failure and the correlation between GEBC and failure propensity for both hierarchical and non-hierarchical networks exhibiting various degrees of disorder. We observe a non trivial relationship between GEBC and failure propensity, which suggests that the idea of GEBC as a useful failure predictor needs to be strongly qualified.
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