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Analysis on a database of ship accidents in port areas

In the last 15 years, the number of vessels in the world fleet has grown by around 53% and their gross tonnage has increased by 47%, with a consequent significant increment of marine accidents worldwide. Accident database are the basic resource for risk assessment methods to help decision-makers to...

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Autores principales: Marino, Massimiliano, Cavallaro, Luca, Castro, Elisa, Musumeci, Rosaria Ester, Martignoni, Matteo, Roman, Federico, Foti, Enrico
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10149327/
https://www.ncbi.nlm.nih.gov/pubmed/37139115
http://dx.doi.org/10.1016/j.dib.2023.109127
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author Marino, Massimiliano
Cavallaro, Luca
Castro, Elisa
Musumeci, Rosaria Ester
Martignoni, Matteo
Roman, Federico
Foti, Enrico
author_facet Marino, Massimiliano
Cavallaro, Luca
Castro, Elisa
Musumeci, Rosaria Ester
Martignoni, Matteo
Roman, Federico
Foti, Enrico
author_sort Marino, Massimiliano
collection PubMed
description In the last 15 years, the number of vessels in the world fleet has grown by around 53% and their gross tonnage has increased by 47%, with a consequent significant increment of marine accidents worldwide. Accident database are the basic resource for risk assessment methods to help decision-makers to enact strategies and undergo hazard and vulnerability mitigation measures. Understanding ship accidents distribution in terms of involved GT, typical age of the affected vessels, category of the ships, as well as distribution of underlying causes and consequences is the first necessary step to improve accident mitigation actions to be implemented for future assessments. In the present work, the results of an analysis on a database of vessel accidents in Mediterranean and worldwide port areas developed within the framework of the project ISY PORT (Integrated SYstem for navigation risk mitigation in PORTs) is herein presented. The distribution of accidents was analyzed in terms of relevant vessel characteristics i.e. Grosse Tonnage (GT), age at the time of the accident, ship's category, causality event, weather conditions and number of fatalities/injuries/lost at sea. The database can be used as a basis for maritime risk assessment methods and for calibration of real-time ship collision avoidance scenarios.
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spelling pubmed-101493272023-05-02 Analysis on a database of ship accidents in port areas Marino, Massimiliano Cavallaro, Luca Castro, Elisa Musumeci, Rosaria Ester Martignoni, Matteo Roman, Federico Foti, Enrico Data Brief Data Article In the last 15 years, the number of vessels in the world fleet has grown by around 53% and their gross tonnage has increased by 47%, with a consequent significant increment of marine accidents worldwide. Accident database are the basic resource for risk assessment methods to help decision-makers to enact strategies and undergo hazard and vulnerability mitigation measures. Understanding ship accidents distribution in terms of involved GT, typical age of the affected vessels, category of the ships, as well as distribution of underlying causes and consequences is the first necessary step to improve accident mitigation actions to be implemented for future assessments. In the present work, the results of an analysis on a database of vessel accidents in Mediterranean and worldwide port areas developed within the framework of the project ISY PORT (Integrated SYstem for navigation risk mitigation in PORTs) is herein presented. The distribution of accidents was analyzed in terms of relevant vessel characteristics i.e. Grosse Tonnage (GT), age at the time of the accident, ship's category, causality event, weather conditions and number of fatalities/injuries/lost at sea. The database can be used as a basis for maritime risk assessment methods and for calibration of real-time ship collision avoidance scenarios. Elsevier 2023-04-11 /pmc/articles/PMC10149327/ /pubmed/37139115 http://dx.doi.org/10.1016/j.dib.2023.109127 Text en © 2023 The Author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Data Article
Marino, Massimiliano
Cavallaro, Luca
Castro, Elisa
Musumeci, Rosaria Ester
Martignoni, Matteo
Roman, Federico
Foti, Enrico
Analysis on a database of ship accidents in port areas
title Analysis on a database of ship accidents in port areas
title_full Analysis on a database of ship accidents in port areas
title_fullStr Analysis on a database of ship accidents in port areas
title_full_unstemmed Analysis on a database of ship accidents in port areas
title_short Analysis on a database of ship accidents in port areas
title_sort analysis on a database of ship accidents in port areas
topic Data Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10149327/
https://www.ncbi.nlm.nih.gov/pubmed/37139115
http://dx.doi.org/10.1016/j.dib.2023.109127
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