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...
Published in: | Reliability Engineering & System Safety |
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Language: | English |
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Online Access: | https://hdl.handle.net/11250/3032276 https://doi.org/10.1016/j.ress.2022.108475 |
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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 |
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Open Polar |
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NTNU Open Archive (Norwegian University of Science and Technology) |
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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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1766032467868778496 |