An operational risk analysis tool to analyze marine transportation in Arctic waters
Abstract The Arctic Ocean has drawn major attention in recent years due to its rich natural resources and shorter navigational routes. Arctic development and transportation involve significant risk caused by the unique features of this region, such as ice, severe operating conditions, unpredictable...
Published in: | Reliability Engineering & System Safety |
---|---|
Main Authors: | , , , , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
Reliability Engineering & System Safety
2018
|
Subjects: | |
Online Access: | http://nur.nu.edu.kz/handle/123456789/3005 https://doi.org/10.1016/j.ress.2017.09.014 https://www.sciencedirect.com/science/article/pii/S0951832017303101 |
id |
ftnazarbayevuniv:oai:testnur.nu.edu.kz:123456789/3005 |
---|---|
record_format |
openpolar |
spelling |
ftnazarbayevuniv:oai:testnur.nu.edu.kz:123456789/3005 2023-05-15T14:49:36+02:00 An operational risk analysis tool to analyze marine transportation in Arctic waters Bushra, Khan Khan, Bushra Khan, Faisal Veitch, Brian Yang, Ming 2018-01-01 http://nur.nu.edu.kz/handle/123456789/3005 https://doi.org/10.1016/j.ress.2017.09.014 https://www.sciencedirect.com/science/article/pii/S0951832017303101 en eng Reliability Engineering & System Safety Reliability Engineering & System Safety © 2017 Elsevier Ltd. All rights reserved. Northern Sea Route (NSR) Risk analysis Object Oriented Bayesian Network Collision Potential consequences Article 2018 ftnazarbayevuniv https://doi.org/10.1016/j.ress.2017.09.014 2019-04-02T14:35:57Z Abstract The Arctic Ocean has drawn major attention in recent years due to its rich natural resources and shorter navigational routes. Arctic development and transportation involve significant risk caused by the unique features of this region, such as ice, severe operating conditions, unpredictable climatic changes, and remoteness. Considering the high degree of uncertainty in the performance of vessel operating systems and humans, robust risk analysis and management tools are required to provide decision-support to prevent accidents and ensure safety at sea. This paper proposes an Object-Oriented Bayesian Network model to dynamically predict ship-ice collision probability based on navigational and operational system states, weather and ice conditions, and human error. The model, when integrated with potential consequences, may help estimate risk. A case study related to oil tanker navigation on the Northern Sea Route (NSR) is used to show the application of the proposed model to predict oil tanker collision with sea ice. Article in Journal/Newspaper Arctic Arctic Ocean Northern Sea Route Sea ice Nazarbayev University Repository Arctic Arctic Ocean Reliability Engineering & System Safety 169 485 502 |
institution |
Open Polar |
collection |
Nazarbayev University Repository |
op_collection_id |
ftnazarbayevuniv |
language |
English |
topic |
Northern Sea Route (NSR) Risk analysis Object Oriented Bayesian Network Collision Potential consequences |
spellingShingle |
Northern Sea Route (NSR) Risk analysis Object Oriented Bayesian Network Collision Potential consequences Bushra, Khan Khan, Bushra Khan, Faisal Veitch, Brian Yang, Ming An operational risk analysis tool to analyze marine transportation in Arctic waters |
topic_facet |
Northern Sea Route (NSR) Risk analysis Object Oriented Bayesian Network Collision Potential consequences |
description |
Abstract The Arctic Ocean has drawn major attention in recent years due to its rich natural resources and shorter navigational routes. Arctic development and transportation involve significant risk caused by the unique features of this region, such as ice, severe operating conditions, unpredictable climatic changes, and remoteness. Considering the high degree of uncertainty in the performance of vessel operating systems and humans, robust risk analysis and management tools are required to provide decision-support to prevent accidents and ensure safety at sea. This paper proposes an Object-Oriented Bayesian Network model to dynamically predict ship-ice collision probability based on navigational and operational system states, weather and ice conditions, and human error. The model, when integrated with potential consequences, may help estimate risk. A case study related to oil tanker navigation on the Northern Sea Route (NSR) is used to show the application of the proposed model to predict oil tanker collision with sea ice. |
format |
Article in Journal/Newspaper |
author |
Bushra, Khan Khan, Bushra Khan, Faisal Veitch, Brian Yang, Ming |
author_facet |
Bushra, Khan Khan, Bushra Khan, Faisal Veitch, Brian Yang, Ming |
author_sort |
Bushra, Khan |
title |
An operational risk analysis tool to analyze marine transportation in Arctic waters |
title_short |
An operational risk analysis tool to analyze marine transportation in Arctic waters |
title_full |
An operational risk analysis tool to analyze marine transportation in Arctic waters |
title_fullStr |
An operational risk analysis tool to analyze marine transportation in Arctic waters |
title_full_unstemmed |
An operational risk analysis tool to analyze marine transportation in Arctic waters |
title_sort |
operational risk analysis tool to analyze marine transportation in arctic waters |
publisher |
Reliability Engineering & System Safety |
publishDate |
2018 |
url |
http://nur.nu.edu.kz/handle/123456789/3005 https://doi.org/10.1016/j.ress.2017.09.014 https://www.sciencedirect.com/science/article/pii/S0951832017303101 |
geographic |
Arctic Arctic Ocean |
geographic_facet |
Arctic Arctic Ocean |
genre |
Arctic Arctic Ocean Northern Sea Route Sea ice |
genre_facet |
Arctic Arctic Ocean Northern Sea Route Sea ice |
op_relation |
Reliability Engineering & System Safety |
op_rights |
© 2017 Elsevier Ltd. All rights reserved. |
op_doi |
https://doi.org/10.1016/j.ress.2017.09.014 |
container_title |
Reliability Engineering & System Safety |
container_volume |
169 |
container_start_page |
485 |
op_container_end_page |
502 |
_version_ |
1766320693060829184 |