@article{GU2025, 
author = {Yue GU and Renchuan ZHU and Chuanqing LI and Chengyu WU},
title = {SVR-based identification of nonlinear roll motion of trimaran},
year = {2025},
journal = {Chinese Journal of Ship Research},
volume = {20},
number = {2},
pages = {187-195},
keywords = {trimaran, nonlinear roll damping, computational fluid dynamics, support vector regression, regression analysis},
url = {https://www.sciopen.com/article/10.19693/j.issn.1673-3185.03584},
doi = {10.19693/j.issn.1673-3185.03584},
abstract = {ObjectiveAiming at the nonlinearity of trimaran rolling, a system identification modeling method combining CFD and support vector regression (SVR) is proposed. MethodsBased on the STAR-CCM+ platform, numerical simulations of forced rolling motion of the trimarans with different lateral layouts are performed. Then the SVR method is used to identify the parameters of the hydrodynamic moment history curve and calculate the additional mass and damping coefficient of the hull at different frequencies. ResultsThe results show that the damping coefficient of the trimaran shows strong frequency dependence; the nonlinear characteristics of the damping are profound at low frequencies, and the damping component of the bilge keel accounts for a large proportion. ConclusionCompared with potential theory, the proposed SVR method can accurately capture the nonlinear characteristics of the trimaran's rolling motion, and better account for the flow interactions between hulls.}
}