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Title: Prediction of the motion of a ship in regular head waves using artificial neural networks
Authors: Liu, Shukui
Xu, Rong
Papanikolaou, Apostolos
Keywords: Engineering::Mechanical engineering
Issue Date: 2021
Source: 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.
Project: 020211-00001
metadata.dc.contributor.conference: 31st International Ocean and Polar Engineering Conference (ISOPE 2021)
Abstract: 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.
Schools: School of Mechanical and Aerospace Engineering 
Rights: © 2021 International Society of Offshore and Polar Engineers (ISOPE). All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:MAE Conference Papers

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