A Bayesian network risk model for predicting ship besetting in ice during convoy operations along the Northern Sea Route

To facilitate shipping in ice and to meet the increasing requirements of icebreaker services, convoy operations are the most effective alternative. However, convoy operations are among the most dangerous operations as they can result in ship-ship collisions and/or ship besetting in ice. To safeguard...

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Published in:Reliability Engineering & System Safety
Main Authors: Xu, Sheng, Kim, Ekaterina, Haugen, Stein, Zhang, Mingyang
Format: Article in Journal/Newspaper
Language:English
Published: Elsevier 2022
Subjects:
Online Access:https://hdl.handle.net/11250/3032276
https://doi.org/10.1016/j.ress.2022.108475
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spelling ftntnutrondheimi:oai:ntnuopen.ntnu.no:11250/3032276 2023-05-15T16:42:00+02:00 A Bayesian network risk model for predicting ship besetting in ice during convoy operations along the Northern Sea Route Xu, Sheng Kim, Ekaterina Haugen, Stein Zhang, Mingyang 2022 application/pdf https://hdl.handle.net/11250/3032276 https://doi.org/10.1016/j.ress.2022.108475 eng eng Elsevier urn:issn:0951-8320 https://hdl.handle.net/11250/3032276 https://doi.org/10.1016/j.ress.2022.108475 cristin:2012450 Navngivelse 4.0 Internasjonal http://creativecommons.org/licenses/by/4.0/deed.no CC-BY 223 Reliability Engineering & System Safety Journal article Peer reviewed 2022 ftntnutrondheimi https://doi.org/10.1016/j.ress.2022.108475 2022-11-23T23:42:31Z To facilitate shipping in ice and to meet the increasing requirements of icebreaker services, convoy operations are the most effective alternative. However, convoy operations are among the most dangerous operations as they can result in ship-ship collisions and/or ship besetting in ice. To safeguard the assisted ships and improve the efficiency of convoy operations, predicting the besetment event is a paramount proactive measure. In this study, a Bayesian Network model is developed to predict the probability of ship besetting in ice in a convoy operation along the Northern Sea Route (NSR). The model focuses on the first-assisted ship and is based on expert elicitation. Correspondingly, four scenarios that may result in the first assisted ship besetting in ice have been identified. Further, the applicability of the model is evaluated through 12 scenarios derived from the real NSR voyage of ‘TIAN YOU’ assisted by the icebreaker ‘VAYGACH’ in August 2018. The results of the model evaluation and validity studies indicate that the developed model is feasible and can adequately predict the besetment event of the first assisted ship in convoy operations. The most important factors contributing to besetting in ice were found to be ice concentration, distance between icebreaker and ship, and navigation experience. publishedVersion Article in Journal/Newspaper Icebreaker Northern Sea Route Vaygach NTNU Open Archive (Norwegian University of Science and Technology) Vaygach ENVELOPE(58.789,58.789,70.394,70.394) Reliability Engineering & System Safety 223 108475
institution Open Polar
collection NTNU Open Archive (Norwegian University of Science and Technology)
op_collection_id ftntnutrondheimi
language English
description To facilitate shipping in ice and to meet the increasing requirements of icebreaker services, convoy operations are the most effective alternative. However, convoy operations are among the most dangerous operations as they can result in ship-ship collisions and/or ship besetting in ice. To safeguard the assisted ships and improve the efficiency of convoy operations, predicting the besetment event is a paramount proactive measure. In this study, a Bayesian Network model is developed to predict the probability of ship besetting in ice in a convoy operation along the Northern Sea Route (NSR). The model focuses on the first-assisted ship and is based on expert elicitation. Correspondingly, four scenarios that may result in the first assisted ship besetting in ice have been identified. Further, the applicability of the model is evaluated through 12 scenarios derived from the real NSR voyage of ‘TIAN YOU’ assisted by the icebreaker ‘VAYGACH’ in August 2018. The results of the model evaluation and validity studies indicate that the developed model is feasible and can adequately predict the besetment event of the first assisted ship in convoy operations. The most important factors contributing to besetting in ice were found to be ice concentration, distance between icebreaker and ship, and navigation experience. publishedVersion
format Article in Journal/Newspaper
author Xu, Sheng
Kim, Ekaterina
Haugen, Stein
Zhang, Mingyang
spellingShingle Xu, Sheng
Kim, Ekaterina
Haugen, Stein
Zhang, Mingyang
A Bayesian network risk model for predicting ship besetting in ice during convoy operations along the Northern Sea Route
author_facet Xu, Sheng
Kim, Ekaterina
Haugen, Stein
Zhang, Mingyang
author_sort Xu, Sheng
title A Bayesian network risk model for predicting ship besetting in ice during convoy operations along the Northern Sea Route
title_short A Bayesian network risk model for predicting ship besetting in ice during convoy operations along the Northern Sea Route
title_full A Bayesian network risk model for predicting ship besetting in ice during convoy operations along the Northern Sea Route
title_fullStr A Bayesian network risk model for predicting ship besetting in ice during convoy operations along the Northern Sea Route
title_full_unstemmed A Bayesian network risk model for predicting ship besetting in ice during convoy operations along the Northern Sea Route
title_sort bayesian network risk model for predicting ship besetting in ice during convoy operations along the northern sea route
publisher Elsevier
publishDate 2022
url https://hdl.handle.net/11250/3032276
https://doi.org/10.1016/j.ress.2022.108475
long_lat ENVELOPE(58.789,58.789,70.394,70.394)
geographic Vaygach
geographic_facet Vaygach
genre Icebreaker
Northern Sea Route
Vaygach
genre_facet Icebreaker
Northern Sea Route
Vaygach
op_source 223
Reliability Engineering & System Safety
op_relation urn:issn:0951-8320
https://hdl.handle.net/11250/3032276
https://doi.org/10.1016/j.ress.2022.108475
cristin:2012450
op_rights Navngivelse 4.0 Internasjonal
http://creativecommons.org/licenses/by/4.0/deed.no
op_rightsnorm CC-BY
op_doi https://doi.org/10.1016/j.ress.2022.108475
container_title Reliability Engineering & System Safety
container_volume 223
container_start_page 108475
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