Marine transportation risk assessment using Bayesian Network:application to Arctic waters

Maritime transportation poses risks regarding possible accidents resulting in damage to vessels, crew members and to the ecosystem. The safe navigation of ships, especially in the Arctic waters, is a growing concern to maritime authorities. This study proposes a new risk model applicable to the Nort...

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Bibliographic Details
Published in:Ocean Engineering
Main Authors: Baksh, Al-Amin, Abbassi, Rouzbeh, Garaniya, Vikram, Khan, Faisal
Format: Article in Journal/Newspaper
Language:English
Published: 2018
Subjects:
Online Access:https://researchers.mq.edu.au/en/publications/9be95142-190a-4535-8f5d-29737c09dc0b
https://doi.org/10.1016/j.oceaneng.2018.04.024
http://www.scopus.com/inward/record.url?scp=85046739874&partnerID=8YFLogxK
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author Baksh, Al-Amin
Abbassi, Rouzbeh
Garaniya, Vikram
Khan, Faisal
author_facet Baksh, Al-Amin
Abbassi, Rouzbeh
Garaniya, Vikram
Khan, Faisal
author_sort Baksh, Al-Amin
collection Unknown
container_start_page 422
container_title Ocean Engineering
container_volume 159
description Maritime transportation poses risks regarding possible accidents resulting in damage to vessels, crew members and to the ecosystem. The safe navigation of ships, especially in the Arctic waters, is a growing concern to maritime authorities. This study proposes a new risk model applicable to the Northern Sea Route (NSR) to investigate the possibility of marine accidents such as collision, foundering and grounding. The model is developed using Bayesian Network (BN). The proposed risk model has considered different operational and environmental factors that affect shipping operations. Historical data and expert judgments are used to estimate the base value (prior values) of various operational and environmental factors. The application of the model is demonstrated through a case study of an oil-tanker navigating the NSR. The case study confirms the highest collision, foundering and grounding probabilities in the East Siberian Sea. However, foundering probabilities are very low in all five regions. By running uncertainty and sensitivity analyses of the model, a significant change in the likelihood of the occurrence of accidental events is identified. The model suggests ice effect as a dominant factor in accident causation. The case study illustrates the priority of the model in investigating the operational risk of accidents. The estimated risk provides early warning to take appropriate preventive and mitigative measures to enhance the overall safety of shipping operations.
format Article in Journal/Newspaper
genre Arctic
Arctic
East Siberian Sea
Northern Sea Route
genre_facet Arctic
Arctic
East Siberian Sea
Northern Sea Route
geographic Arctic
East Siberian Sea
geographic_facet Arctic
East Siberian Sea
id ftmacquarieunicr:oai:https://researchers.mq.edu.au:publications/9be95142-190a-4535-8f5d-29737c09dc0b
institution Open Polar
language English
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op_container_end_page 436
op_doi https://doi.org/10.1016/j.oceaneng.2018.04.024
op_rights info:eu-repo/semantics/closedAccess
op_source Baksh , A-A , Abbassi , R , Garaniya , V & Khan , F 2018 , ' Marine transportation risk assessment using Bayesian Network : application to Arctic waters ' , Ocean Engineering , vol. 159 , pp. 422-436 . https://doi.org/10.1016/j.oceaneng.2018.04.024
publishDate 2018
record_format openpolar
spelling ftmacquarieunicr:oai:https://researchers.mq.edu.au:publications/9be95142-190a-4535-8f5d-29737c09dc0b 2025-06-15T14:16:37+00:00 Marine transportation risk assessment using Bayesian Network:application to Arctic waters Baksh, Al-Amin Abbassi, Rouzbeh Garaniya, Vikram Khan, Faisal 2018-07-01 https://researchers.mq.edu.au/en/publications/9be95142-190a-4535-8f5d-29737c09dc0b https://doi.org/10.1016/j.oceaneng.2018.04.024 http://www.scopus.com/inward/record.url?scp=85046739874&partnerID=8YFLogxK eng eng info:eu-repo/semantics/closedAccess Baksh , A-A , Abbassi , R , Garaniya , V & Khan , F 2018 , ' Marine transportation risk assessment using Bayesian Network : application to Arctic waters ' , Ocean Engineering , vol. 159 , pp. 422-436 . https://doi.org/10.1016/j.oceaneng.2018.04.024 accident modelling Bayesian network Arctic transportation Northern Sea Route article 2018 ftmacquarieunicr https://doi.org/10.1016/j.oceaneng.2018.04.024 2025-06-02T00:02:22Z Maritime transportation poses risks regarding possible accidents resulting in damage to vessels, crew members and to the ecosystem. The safe navigation of ships, especially in the Arctic waters, is a growing concern to maritime authorities. This study proposes a new risk model applicable to the Northern Sea Route (NSR) to investigate the possibility of marine accidents such as collision, foundering and grounding. The model is developed using Bayesian Network (BN). The proposed risk model has considered different operational and environmental factors that affect shipping operations. Historical data and expert judgments are used to estimate the base value (prior values) of various operational and environmental factors. The application of the model is demonstrated through a case study of an oil-tanker navigating the NSR. The case study confirms the highest collision, foundering and grounding probabilities in the East Siberian Sea. However, foundering probabilities are very low in all five regions. By running uncertainty and sensitivity analyses of the model, a significant change in the likelihood of the occurrence of accidental events is identified. The model suggests ice effect as a dominant factor in accident causation. The case study illustrates the priority of the model in investigating the operational risk of accidents. The estimated risk provides early warning to take appropriate preventive and mitigative measures to enhance the overall safety of shipping operations. Article in Journal/Newspaper Arctic Arctic East Siberian Sea Northern Sea Route Unknown Arctic East Siberian Sea ENVELOPE(166.000,166.000,74.000,74.000) Ocean Engineering 159 422 436
spellingShingle accident modelling
Bayesian network
Arctic transportation
Northern Sea Route
Baksh, Al-Amin
Abbassi, Rouzbeh
Garaniya, Vikram
Khan, Faisal
Marine transportation risk assessment using Bayesian Network:application to Arctic waters
title Marine transportation risk assessment using Bayesian Network:application to Arctic waters
title_full Marine transportation risk assessment using Bayesian Network:application to Arctic waters
title_fullStr Marine transportation risk assessment using Bayesian Network:application to Arctic waters
title_full_unstemmed Marine transportation risk assessment using Bayesian Network:application to Arctic waters
title_short Marine transportation risk assessment using Bayesian Network:application to Arctic waters
title_sort marine transportation risk assessment using bayesian network:application to arctic waters
topic accident modelling
Bayesian network
Arctic transportation
Northern Sea Route
topic_facet accident modelling
Bayesian network
Arctic transportation
Northern Sea Route
url https://researchers.mq.edu.au/en/publications/9be95142-190a-4535-8f5d-29737c09dc0b
https://doi.org/10.1016/j.oceaneng.2018.04.024
http://www.scopus.com/inward/record.url?scp=85046739874&partnerID=8YFLogxK