Prediction of the motion of a ship in regular head waves using artificial neural networks
This paper presents a research on the application of artificial neural networks (ANNs) to predict the seakeeping behavior of ships in head waves. The decisive input parameters of the ANNs are identified by analyzing the general equations governing the ship motions. Then, a ship database that conside...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Conference Paper |
| Language: | English |
| Published: |
2022
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/160589 https://onepetro.org/ISOPEIOPEC/ISOPE21/conference/All-ISOPE21 |
| _version_ | 1826114168875384832 |
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| author | Liu, Shukui Xu, Rong Papanikolaou, Apostolos |
| author2 | School of Mechanical and Aerospace Engineering |
| author_facet | School of Mechanical and Aerospace Engineering Liu, Shukui Xu, Rong Papanikolaou, Apostolos |
| author_sort | Liu, Shukui |
| collection | NTU |
| description | This paper presents a research on the application of artificial neural networks (ANNs) to predict the seakeeping behavior of ships in head waves. The decisive input parameters of the ANNs are identified by analyzing the general equations governing the ship motions. Then, a ship database that considers all major merchant ship types and hull forms is set up and an in-house frequency domain 3D panel method is used to predict the heave and pitch motions of these ships in head waves at typical operational speeds, thus, establishing a motion database, which provides data to train the ANN networks. Several types of neural networks are explored and systematically trained. The developed network is applied to the prediction of the motions of several ships, which are not in the database, to demonstrate their efficiency in quickly and accurately predicting the seakeeping performance of typical merchant ships. |
| first_indexed | 2024-10-01T03:34:47Z |
| format | Conference Paper |
| id | ntu-10356/160589 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T03:34:47Z |
| publishDate | 2022 |
| record_format | dspace |
| spelling | ntu-10356/1605892022-07-28T05:31:37Z Prediction of the motion of a ship in regular head waves using artificial neural networks Liu, Shukui Xu, Rong Papanikolaou, Apostolos School of Mechanical and Aerospace Engineering 31st International Ocean and Polar Engineering Conference (ISOPE 2021) Engineering::Mechanical engineering Artificial Neural Networks Multi-Layer Perceptron Seakeeping Assessment Heave and Pitch Head Waves Ship Operation This paper presents a research on the application of artificial neural networks (ANNs) to predict the seakeeping behavior of ships in head waves. The decisive input parameters of the ANNs are identified by analyzing the general equations governing the ship motions. Then, a ship database that considers all major merchant ship types and hull forms is set up and an in-house frequency domain 3D panel method is used to predict the heave and pitch motions of these ships in head waves at typical operational speeds, thus, establishing a motion database, which provides data to train the ANN networks. Several types of neural networks are explored and systematically trained. The developed network is applied to the prediction of the motions of several ships, which are not in the database, to demonstrate their efficiency in quickly and accurately predicting the seakeeping performance of typical merchant ships. Ministry of Education (MOE) This research is partly supported by the Ministry of Education, Singapore, under its Academic Research Fund Tier 1 (Award Number: #020211-00001; Award Title: “Investigation of the self-propulsion factors for determining minimum propulsion power to ensure safe ship operation at low speeds”). 2022-07-28T05:30:39Z 2022-07-28T05:30:39Z 2021 Conference Paper Liu, S., Xu, R. & Papanikolaou, A. (2021). Prediction of the motion of a ship in regular head waves using artificial neural networks. 31st International Ocean and Polar Engineering Conference (ISOPE 2021), 1687-1693. https://hdl.handle.net/10356/160589 https://onepetro.org/ISOPEIOPEC/ISOPE21/conference/All-ISOPE21 1687 1693 en 020211-00001 © 2021 International Society of Offshore and Polar Engineers (ISOPE). All rights reserved. |
| spellingShingle | Engineering::Mechanical engineering Artificial Neural Networks Multi-Layer Perceptron Seakeeping Assessment Heave and Pitch Head Waves Ship Operation Liu, Shukui Xu, Rong Papanikolaou, Apostolos Prediction of the motion of a ship in regular head waves using artificial neural networks |
| title | Prediction of the motion of a ship in regular head waves using artificial neural networks |
| title_full | Prediction of the motion of a ship in regular head waves using artificial neural networks |
| title_fullStr | Prediction of the motion of a ship in regular head waves using artificial neural networks |
| title_full_unstemmed | Prediction of the motion of a ship in regular head waves using artificial neural networks |
| title_short | Prediction of the motion of a ship in regular head waves using artificial neural networks |
| title_sort | prediction of the motion of a ship in regular head waves using artificial neural networks |
| topic | Engineering::Mechanical engineering Artificial Neural Networks Multi-Layer Perceptron Seakeeping Assessment Heave and Pitch Head Waves Ship Operation |
| url | https://hdl.handle.net/10356/160589 https://onepetro.org/ISOPEIOPEC/ISOPE21/conference/All-ISOPE21 |
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