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Scaling laws of failure dynamics on complex networks
The topology of the network of load transmitting connections plays an essential role in the cascading failure dynamics of complex systems driven by the redistribution of load after local breakdown events. In particular, as the network structure is gradually tuned from regular to completely random a...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10643452/ https://www.ncbi.nlm.nih.gov/pubmed/37957302 http://dx.doi.org/10.1038/s41598-023-47152-2 |
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author | Pál, Gergő Danku, Zsuzsa Batool, Attia Kádár, Viktória Yoshioka, Naoki Ito, Nobuyasu Ódor, Géza Kun, Ferenc |
author_facet | Pál, Gergő Danku, Zsuzsa Batool, Attia Kádár, Viktória Yoshioka, Naoki Ito, Nobuyasu Ódor, Géza Kun, Ferenc |
author_sort | Pál, Gergő |
collection | PubMed |
description | The topology of the network of load transmitting connections plays an essential role in the cascading failure dynamics of complex systems driven by the redistribution of load after local breakdown events. In particular, as the network structure is gradually tuned from regular to completely random a transition occurs from the localized to mean field behavior of failure spreading. Based on finite size scaling in the fiber bundle model of failure phenomena, here we demonstrate that outside the localized regime, the load bearing capacity and damage tolerance on the macro-scale, and the statistics of clusters of failed nodes on the micro-scale obey scaling laws with exponents which depend on the topology of the load transmission network and on the degree of disorder of the strength of nodes. Most notably, we show that the spatial structure of damage governs the emergence of the localized to mean field transition: as the network gets gradually randomized failed clusters formed on locally regular patches merge through long range links generating a percolation like transition which reduces the load concentration on the network. The results may help to design network structures with an improved robustness against cascading failure. |
format | Online Article Text |
id | pubmed-10643452 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-106434522023-11-13 Scaling laws of failure dynamics on complex networks Pál, Gergő Danku, Zsuzsa Batool, Attia Kádár, Viktória Yoshioka, Naoki Ito, Nobuyasu Ódor, Géza Kun, Ferenc Sci Rep Article The topology of the network of load transmitting connections plays an essential role in the cascading failure dynamics of complex systems driven by the redistribution of load after local breakdown events. In particular, as the network structure is gradually tuned from regular to completely random a transition occurs from the localized to mean field behavior of failure spreading. Based on finite size scaling in the fiber bundle model of failure phenomena, here we demonstrate that outside the localized regime, the load bearing capacity and damage tolerance on the macro-scale, and the statistics of clusters of failed nodes on the micro-scale obey scaling laws with exponents which depend on the topology of the load transmission network and on the degree of disorder of the strength of nodes. Most notably, we show that the spatial structure of damage governs the emergence of the localized to mean field transition: as the network gets gradually randomized failed clusters formed on locally regular patches merge through long range links generating a percolation like transition which reduces the load concentration on the network. The results may help to design network structures with an improved robustness against cascading failure. Nature Publishing Group UK 2023-11-13 /pmc/articles/PMC10643452/ /pubmed/37957302 http://dx.doi.org/10.1038/s41598-023-47152-2 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Pál, Gergő Danku, Zsuzsa Batool, Attia Kádár, Viktória Yoshioka, Naoki Ito, Nobuyasu Ódor, Géza Kun, Ferenc Scaling laws of failure dynamics on complex networks |
title | Scaling laws of failure dynamics on complex networks |
title_full | Scaling laws of failure dynamics on complex networks |
title_fullStr | Scaling laws of failure dynamics on complex networks |
title_full_unstemmed | Scaling laws of failure dynamics on complex networks |
title_short | Scaling laws of failure dynamics on complex networks |
title_sort | scaling laws of failure dynamics on complex networks |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10643452/ https://www.ncbi.nlm.nih.gov/pubmed/37957302 http://dx.doi.org/10.1038/s41598-023-47152-2 |
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