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Title
Ship nonlinear roll motion identification using artificial neural network

ISSN printed: 1733-8670, ISSN on-line: 2392-0378
Mousavi, Seyed Mohamadreza1; Khoogar, Ahmad Reza2; Ghassemi, Hassan3
URI: http://repository.scientific-journals.eu/handle/123456789/2751
2022-12-31
The solution of the nonlinear equation for a ship’s rotational motion around its longitudinal axis, even with simplifying assumptions, is complicated. This oscillatory motion, which is known as the roll motion, is generated when the ship sails in the waves, and the irregular behavior of the waves causes time-varying dynamics. Calculating the ship’s roll response is possible by determining roll equation coefficients. In the current study, the coefficients were determined from the dynamic response of the ship using a training feed-forward neural network. The training was carried out in two modes: as a free swing in calm water and forced oscillation in irregular waves. The DTMB 5415 vessel was selected as the case study ship. The results of the simulation by the neural network were validated by numerical analysis and model test results.
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Title

Ship nonlinear roll motion identification using artificial neural network

Pages

Figures

17

Tables

2

ISSN printed

1733-8670

ISSN on-line

2392-0378

DOI

Type

Original scientific article

Journal

72 Scientific Journals of the Maritime University of Szczecin, no. 72 / 2022

Publisher

Scientific Journals Maritime University of Szczecin, Zeszyty Naukowe Akademia Morska w Szczecinie

Copyright Holder

Scientific Journals Maritime University of Szczecin, Zeszyty Naukowe Akademia Morska w Szczecinie

Published

2022-12-31

Recieved

2022-03-16

Accepted

2022-09-22

Funding

No data

Keywords

nonlinear roll motion, dynamic identification, DTMB 5415, roll decay

URI:

http://repository.scientific-journals.eu/handle/123456789/2751

Language

English

Authors

Mousavi, Seyed Mohamadreza1; Khoogar, Ahmad Reza2; Ghassemi, Hassan3

Affiliation

1 Malek Ashtar University of Technology, Maritime Engineering Department Esfahan, Iran, srmousavi@aut.ac.ir
2 Malek Ashtar University of Technology, Mechanical Engineering Department Lavizan Ave., Tehran, Iran, khoogar@mut.ac.ir
3 Amirkabir University of Technology Marine Engineering Department, gasemi@aut.ac.ir

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