Ship nonlinear roll motion identification using artificial neural network

• Autorzy: Mousavi Seyed Mohamadreza , Khoogar Ahmad Reza , Ghassemi Hassan

Identyfikatory

DOI

10.17402/535

• Języki publikacji: EN

Abstrakty

EN

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.

Słowa kluczowe

EN

nonlinear roll motion; dynamic identification; DTMB 5415; roll decay; artificial neural network

• Wydawca: Wydawnictwo Naukowe Akademii Morskiej w Szczecinie
• Czasopismo: Zeszyty Naukowe Akademii Morskiej w Szczecinie
• Rocznik: 2022
• Tom: nr 72 (144)
• Strony: 65--74
• Opis fizyczny: Bibliogr. 13 poz., rys., tab.

Twórcy

autor

Mousavi Seyed Mohamadreza

• Malek Ashtar University of Technology, Maritime Engineering Department Esfahan, Iran

• https://orcid.org/0000-0003-0410-757X

autor

Khoogar Ahmad Reza

• Malek Ashtar University of Technology, Mechanical Engineering Department Lavizan Ave., Tehran, Iran

• https://orcid.org/0000-0002-9259-5229

autor

Ghassemi Hassan

• Amirkabir University of Technology Marine Engineering Department

• https://orcid.org/0000-0002-6201-346X

Bibliografia

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• 5. Hou, X.-R., Zou, Z.-J. & Liu, C. (2018) Nonparametric identification of nonlinear ship roll motion by using the motion response in irregular waves. Applied Ocean Research 73, pp. 88–99.
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• 10. Mousavi, S.M., Khoogar, A.R. & Ghassemi, H. (2020) Time Domain Simulation of Ship Motion in Irregular Oblique Waves. Journal of Applied Fluid Mechanics 13(2), pp. 549–559.
• 11. Oskin, D.A., Dyda, A.A. & Markin, V.E. (2013) Neural network identification of marine ship dynamics. IFAC Proceedings Volumes 46, 33, pp. 191–196.
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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).