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Propagation network of tailings dam failure risk and the identification of key hazards

The tailings dam system is complex, and the dam structure changes continuously over time, which can make it difficult to identify key hazards of failure and characterize the accident formation process. To solve the above problems, based on complex network theory, the paper uses the identified hazard...

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Autores principales: Zhen, Zhixin, Wu, Xu, Ma, Bo, Zhao, Huijie, Zhang, Ying
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8976462/
https://www.ncbi.nlm.nih.gov/pubmed/35368042
http://dx.doi.org/10.1038/s41598-022-08282-1
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author Zhen, Zhixin
Wu, Xu
Ma, Bo
Zhao, Huijie
Zhang, Ying
author_facet Zhen, Zhixin
Wu, Xu
Ma, Bo
Zhao, Huijie
Zhang, Ying
author_sort Zhen, Zhixin
collection PubMed
description The tailings dam system is complex, and the dam structure changes continuously over time, which can make it difficult to identify key hazards of failure and characterize the accident formation process. To solve the above problems, based on complex network theory, the paper uses the identified hazards and the relationship between hazards to construct the propagation network of tailings dam failure risk (PNTDFR). The traditional analysis methods of network centrality usually focus on one aspect of the information of the network, while it cannot take into account to absorb the advantages of different methods, resulting in the difference between identified key nodes and real key hazards. To find the key hazards of tailing dam failure, based on the characteristics of multi-stage propagation of failure risk, the paper proposes a multi-stage collaborative hazard remediation method (MCHRM) to determine the importance of hazard nodes by absorbing the advantages of different centrality methods under different hazard remediation (deletion) ratios. The paper applies the above methods to Feijão Dam I. It can be found that when the priority remediation range is increased to 45%, the key hazards obtained by the MCHRM will cover all the causes of accidents proposed by the Dam I failure investigation expert group. Besides, the paper compares the monitoring data, daily inspection results and safety evaluation information of key hazards with the ‘Grading standards of hazard indicators’, and obtains the formation process of the Dam I failure and 30 key hazards in trigger state.
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spelling pubmed-89764622022-04-04 Propagation network of tailings dam failure risk and the identification of key hazards Zhen, Zhixin Wu, Xu Ma, Bo Zhao, Huijie Zhang, Ying Sci Rep Article The tailings dam system is complex, and the dam structure changes continuously over time, which can make it difficult to identify key hazards of failure and characterize the accident formation process. To solve the above problems, based on complex network theory, the paper uses the identified hazards and the relationship between hazards to construct the propagation network of tailings dam failure risk (PNTDFR). The traditional analysis methods of network centrality usually focus on one aspect of the information of the network, while it cannot take into account to absorb the advantages of different methods, resulting in the difference between identified key nodes and real key hazards. To find the key hazards of tailing dam failure, based on the characteristics of multi-stage propagation of failure risk, the paper proposes a multi-stage collaborative hazard remediation method (MCHRM) to determine the importance of hazard nodes by absorbing the advantages of different centrality methods under different hazard remediation (deletion) ratios. The paper applies the above methods to Feijão Dam I. It can be found that when the priority remediation range is increased to 45%, the key hazards obtained by the MCHRM will cover all the causes of accidents proposed by the Dam I failure investigation expert group. Besides, the paper compares the monitoring data, daily inspection results and safety evaluation information of key hazards with the ‘Grading standards of hazard indicators’, and obtains the formation process of the Dam I failure and 30 key hazards in trigger state. Nature Publishing Group UK 2022-04-02 /pmc/articles/PMC8976462/ /pubmed/35368042 http://dx.doi.org/10.1038/s41598-022-08282-1 Text en © The Author(s) 2022 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
Zhen, Zhixin
Wu, Xu
Ma, Bo
Zhao, Huijie
Zhang, Ying
Propagation network of tailings dam failure risk and the identification of key hazards
title Propagation network of tailings dam failure risk and the identification of key hazards
title_full Propagation network of tailings dam failure risk and the identification of key hazards
title_fullStr Propagation network of tailings dam failure risk and the identification of key hazards
title_full_unstemmed Propagation network of tailings dam failure risk and the identification of key hazards
title_short Propagation network of tailings dam failure risk and the identification of key hazards
title_sort propagation network of tailings dam failure risk and the identification of key hazards
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8976462/
https://www.ncbi.nlm.nih.gov/pubmed/35368042
http://dx.doi.org/10.1038/s41598-022-08282-1
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