Path-following control problem for maritime autonomous surface ships (MASS) in adverse weather conditions at low speeds
Path-following control problem for maritime autonomous surface ships (MASS) in adverse weather conditions at low speeds
With the increasing popularity of autonomous vehicles, the maritime industry has focused on the development of Maritime Autonomous Surface Ships (MASS). An essential aspect of autonomous ships is their ability to follow a predetermined path at sea, as deviations from this path can jeopardize navigational safety, leading to accidents like collisions and grounding incidents. Therefore, ensuring that autonomous ships can safely navigate by following predefined routes is of utmost importance. Simultaneously, the implementation of the Energy Efficiency Design Index (EEDI) by the International Maritime Organization (IMO) has raised interest in a ship's manoeuvring performance in adverse sea conditions, aiming to reduce greenhouse gas emissions. The Marine Environment Protection Committee (MEPC) has provided guidelines to determine the minimum propulsion power required to maintain ship manoeuvrability in adverse conditions. This study investigates the path-following performance of a ship operating at low forward speeds in adverse weather conditions using a free-running Computational Fluid Dynamics (CFD) model, enabling accurate prediction of manoeuvring behaviour. The numerical results emphasise the significance of low forward speeds in enabling a ship to follow a predetermined route, offering valuable insights into path-following performance with minimum propulsion power in adverse weather. The study reveals that increasing propulsive power reduces deviations from the predetermined route when the ship encounters bow and beam waves. However, the impact of propulsion power on deviation is negligible in quartering waves during path-following control. This research contributes to improving guidelines for minimum ship powering, ensuring safe autonomous navigation in adverse weather conditions.
Adverse weather conditions, Line-of-Sight (LOS), Maritime autonomous surface ships (MASS), Path-following control, computational fluid dynamics, Line-of-Sight, Computational fluid dynamics, Maritime autonomous surface ships
Kim, Daejeong
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Yim, Jeongbin
0cc7751e-5d39-4e31-b338-3f931aafbbb0
Song, Soonseok
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Park, Jun-Bum
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Kim, Jongsung
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Yu, Yongung
2cf689a4-7a6d-431a-9ad9-15e9c87f1934
Elsherbiny, Khaled
757191dd-29ef-4d11-bbb6-0c983cee2e15
Tezdogan, Tahsin
7e7328e2-4185-4052-8e9a-53fd81c98909
1 November 2023
Kim, Daejeong
2730cb06-0014-46d4-a4d0-1b27d65668b7
Yim, Jeongbin
0cc7751e-5d39-4e31-b338-3f931aafbbb0
Song, Soonseok
5eab39f4-35ac-42b5-b01b-8c4a9d53f2b1
Park, Jun-Bum
019db241-5f74-4334-8b9a-c2b177436449
Kim, Jongsung
7af4a0ab-1541-4cd5-ade4-334024bddc79
Yu, Yongung
2cf689a4-7a6d-431a-9ad9-15e9c87f1934
Elsherbiny, Khaled
757191dd-29ef-4d11-bbb6-0c983cee2e15
Tezdogan, Tahsin
7e7328e2-4185-4052-8e9a-53fd81c98909
Kim, Daejeong, Yim, Jeongbin, Song, Soonseok, Park, Jun-Bum, Kim, Jongsung, Yu, Yongung, Elsherbiny, Khaled and Tezdogan, Tahsin
(2023)
Path-following control problem for maritime autonomous surface ships (MASS) in adverse weather conditions at low speeds.
Ocean Engineering, 287 (2), [115860].
(doi:10.1016/j.oceaneng.2023.115860).
Abstract
With the increasing popularity of autonomous vehicles, the maritime industry has focused on the development of Maritime Autonomous Surface Ships (MASS). An essential aspect of autonomous ships is their ability to follow a predetermined path at sea, as deviations from this path can jeopardize navigational safety, leading to accidents like collisions and grounding incidents. Therefore, ensuring that autonomous ships can safely navigate by following predefined routes is of utmost importance. Simultaneously, the implementation of the Energy Efficiency Design Index (EEDI) by the International Maritime Organization (IMO) has raised interest in a ship's manoeuvring performance in adverse sea conditions, aiming to reduce greenhouse gas emissions. The Marine Environment Protection Committee (MEPC) has provided guidelines to determine the minimum propulsion power required to maintain ship manoeuvrability in adverse conditions. This study investigates the path-following performance of a ship operating at low forward speeds in adverse weather conditions using a free-running Computational Fluid Dynamics (CFD) model, enabling accurate prediction of manoeuvring behaviour. The numerical results emphasise the significance of low forward speeds in enabling a ship to follow a predetermined route, offering valuable insights into path-following performance with minimum propulsion power in adverse weather. The study reveals that increasing propulsive power reduces deviations from the predetermined route when the ship encounters bow and beam waves. However, the impact of propulsion power on deviation is negligible in quartering waves during path-following control. This research contributes to improving guidelines for minimum ship powering, ensuring safe autonomous navigation in adverse weather conditions.
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Accepted/In Press date: 13 September 2023
e-pub ahead of print date: 25 September 2023
Published date: 1 November 2023
Additional Information:
Funding Information:
This work was supported by the Development of Autonomous Ship Technology [grant number 20200615 ], funded by the Ministry of Oceans and Fisheries (MOF, Korea) . Part of the present work was also supported by Inha University Research Grant.
Publisher Copyright:
© 2023 Elsevier Ltd
Keywords:
Adverse weather conditions, Line-of-Sight (LOS), Maritime autonomous surface ships (MASS), Path-following control, computational fluid dynamics, Line-of-Sight, Computational fluid dynamics, Maritime autonomous surface ships
Identifiers
Local EPrints ID: 482122
URI: http://eprints.soton.ac.uk/id/eprint/482122
ISSN: 0029-8018
PURE UUID: ea69c9b5-174b-4a12-9cc9-736b34e4af24
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Date deposited: 19 Sep 2023 17:06
Last modified: 18 Mar 2024 04:10
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Contributors
Author:
Daejeong Kim
Author:
Jeongbin Yim
Author:
Soonseok Song
Author:
Jun-Bum Park
Author:
Jongsung Kim
Author:
Yongung Yu
Author:
Khaled Elsherbiny
Author:
Tahsin Tezdogan
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