An integrated risk assessment model for safe Arctic navigation

Safety is always the first concern for a ship's navigation in the Arctic. Ships navigating in the Arctic may face two main accident scenarios, i.e., getting stuck in the ice and ship-ice collision. More specifically, excessive speed may cause severe hull damage, while a very low speed may lead...

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Published in:Transportation Research Part A: Policy and Practice
Main Authors: Zhang, Chi, Zhang, Di, Zhang, Mingyang, Lang, Xiao, Mao, Wengang
Language:unknown
Published: 2020
Subjects:
Online Access:https://doi.org/10.1016/j.tra.2020.10.017
https://research.chalmers.se/en/publication/520323
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record_format openpolar
spelling ftchalmersuniv:oai:research.chalmers.se:520323 2023-05-15T14:36:02+02:00 An integrated risk assessment model for safe Arctic navigation Zhang, Chi Zhang, Di Zhang, Mingyang Lang, Xiao Mao, Wengang 2020 text https://doi.org/10.1016/j.tra.2020.10.017 https://research.chalmers.se/en/publication/520323 unknown http://dx.doi.org/10.1016/j.tra.2020.10.017 https://research.chalmers.se/en/publication/520323 Transport Systems and Logistics Marine Engineering Oceanography Hydrology Water Resources Ship-ice collision Risk assessment Bayesian Network Stuck in the ice Safe speed 2020 ftchalmersuniv https://doi.org/10.1016/j.tra.2020.10.017 2022-12-11T07:12:14Z Safety is always the first concern for a ship's navigation in the Arctic. Ships navigating in the Arctic may face two main accident scenarios, i.e., getting stuck in the ice and ship-ice collision. More specifically, excessive speed may cause severe hull damage, while a very low speed may lead to a high probability of getting stuck in the ice. Based on this multi-risk perspective, an integrated risk assessment model was proposed to obtain the overall risk using the Bayesian Network (BN), in which the probabilities of accident occurrence and the severities of the possible consequences for ships getting stuck in the ice and for ship-ice collision could be estimated. Then, the voyage data collected from Yong Sheng's Arctic sailing in 2013 were inputted into the integrated risk assessment model to perform a case study. A sensitivity analysis was performed to validate the proposed model and reveal the inherent mechanisms behind these two accidental scenarios. The proposed model can be applied to identify the safe speed for Arctic navigation under various ice conditions, a duty that is traditionally performed by well-trained crew members, but which entails too many uncertainties. The results can, to some extent, provide useful suggestions for navigators. They are imperative in supporting decision-making to shape the Arctic policy and to enhance the safety of Arctic shipping. Other/Unknown Material Arctic Chalmers University of Technology: Chalmers research Arctic Transportation Research Part A: Policy and Practice 142 101 114
institution Open Polar
collection Chalmers University of Technology: Chalmers research
op_collection_id ftchalmersuniv
language unknown
topic Transport Systems and Logistics
Marine Engineering
Oceanography
Hydrology
Water Resources
Ship-ice collision
Risk assessment
Bayesian Network
Stuck in the ice
Safe speed
spellingShingle Transport Systems and Logistics
Marine Engineering
Oceanography
Hydrology
Water Resources
Ship-ice collision
Risk assessment
Bayesian Network
Stuck in the ice
Safe speed
Zhang, Chi
Zhang, Di
Zhang, Mingyang
Lang, Xiao
Mao, Wengang
An integrated risk assessment model for safe Arctic navigation
topic_facet Transport Systems and Logistics
Marine Engineering
Oceanography
Hydrology
Water Resources
Ship-ice collision
Risk assessment
Bayesian Network
Stuck in the ice
Safe speed
description Safety is always the first concern for a ship's navigation in the Arctic. Ships navigating in the Arctic may face two main accident scenarios, i.e., getting stuck in the ice and ship-ice collision. More specifically, excessive speed may cause severe hull damage, while a very low speed may lead to a high probability of getting stuck in the ice. Based on this multi-risk perspective, an integrated risk assessment model was proposed to obtain the overall risk using the Bayesian Network (BN), in which the probabilities of accident occurrence and the severities of the possible consequences for ships getting stuck in the ice and for ship-ice collision could be estimated. Then, the voyage data collected from Yong Sheng's Arctic sailing in 2013 were inputted into the integrated risk assessment model to perform a case study. A sensitivity analysis was performed to validate the proposed model and reveal the inherent mechanisms behind these two accidental scenarios. The proposed model can be applied to identify the safe speed for Arctic navigation under various ice conditions, a duty that is traditionally performed by well-trained crew members, but which entails too many uncertainties. The results can, to some extent, provide useful suggestions for navigators. They are imperative in supporting decision-making to shape the Arctic policy and to enhance the safety of Arctic shipping.
author Zhang, Chi
Zhang, Di
Zhang, Mingyang
Lang, Xiao
Mao, Wengang
author_facet Zhang, Chi
Zhang, Di
Zhang, Mingyang
Lang, Xiao
Mao, Wengang
author_sort Zhang, Chi
title An integrated risk assessment model for safe Arctic navigation
title_short An integrated risk assessment model for safe Arctic navigation
title_full An integrated risk assessment model for safe Arctic navigation
title_fullStr An integrated risk assessment model for safe Arctic navigation
title_full_unstemmed An integrated risk assessment model for safe Arctic navigation
title_sort integrated risk assessment model for safe arctic navigation
publishDate 2020
url https://doi.org/10.1016/j.tra.2020.10.017
https://research.chalmers.se/en/publication/520323
geographic Arctic
geographic_facet Arctic
genre Arctic
genre_facet Arctic
op_relation http://dx.doi.org/10.1016/j.tra.2020.10.017
https://research.chalmers.se/en/publication/520323
op_doi https://doi.org/10.1016/j.tra.2020.10.017
container_title Transportation Research Part A: Policy and Practice
container_volume 142
container_start_page 101
op_container_end_page 114
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