Vulnerability of Transport through Evolving Spatial Networks
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arXiv
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| Format: | Preprint |
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2024
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| _version_ | 1866914977599717376 |
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| author | Molavi, Ali Hamzehpour, Hossein Shaebani, Reza |
| author_facet | Molavi, Ali Hamzehpour, Hossein Shaebani, Reza |
| contents | Insight into the blockage vulnerability of evolving spatial networks is important for understanding transport resilience, robustness, and failure of a broad class of real-world structures such as porous media and utility, urban traffic, and infrastructure networks. By exhaustive search for central transport hubs on porous lattice structures, we recursively determine and block the emerging main hub until the evolving network reaches the impenetrability limit. We find that the blockage backbone is a self-similar path with a fractal dimension which is distinctly smaller than that of the universality class of optimal path crack models. The number of blocking steps versus the rescaled initial occupation fraction collapses onto a master curve for different network sizes, allowing for the prediction of the onset of impenetrability. The shortest-path length distribution broadens during the blocking process reflecting an increase of spatial correlations. We address the reliability of our predictions upon increasing the disorder or decreasing the fraction of processed structural information. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2407_17977 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Vulnerability of Transport through Evolving Spatial Networks Molavi, Ali Hamzehpour, Hossein Shaebani, Reza Soft Condensed Matter Statistical Mechanics Insight into the blockage vulnerability of evolving spatial networks is important for understanding transport resilience, robustness, and failure of a broad class of real-world structures such as porous media and utility, urban traffic, and infrastructure networks. By exhaustive search for central transport hubs on porous lattice structures, we recursively determine and block the emerging main hub until the evolving network reaches the impenetrability limit. We find that the blockage backbone is a self-similar path with a fractal dimension which is distinctly smaller than that of the universality class of optimal path crack models. The number of blocking steps versus the rescaled initial occupation fraction collapses onto a master curve for different network sizes, allowing for the prediction of the onset of impenetrability. The shortest-path length distribution broadens during the blocking process reflecting an increase of spatial correlations. We address the reliability of our predictions upon increasing the disorder or decreasing the fraction of processed structural information. |
| title | Vulnerability of Transport through Evolving Spatial Networks |
| topic | Soft Condensed Matter Statistical Mechanics |
| url | https://arxiv.org/abs/2407.17977 |