基于支持向量回归的三体船非线性横摇运动辨识

SVR-based identification of nonlinear roll motion of trimaran

    摘要
  • 摘要:
    目的 针对三体船横摇的非线性，提出CFD与支持向量回归(SVR)相结合的船体运动辨识建模方法，
    方法 基于STAR-CCM+平台，对不同侧体横向位置三体船的强迫横摇运动进行数值模拟，并应用SVR方法对力矩时历曲线进行参数辨识，计算不同频率下船体的附加质量与阻尼系数。
    结果 结果表明，三体船阻尼系数呈现出较强的频率相关性；低频时阻尼非线性特征明显，舭龙骨阻尼成分占比较大。
    结论 所提方法能够准确捕捉三体船横摇运动的非线性特征，相比于势流理论能够更好地考虑片体间流场的相互作用。

     

    Abstract:
    Objective Aiming at the nonlinearity of trimaran rolling, a system identification modeling method combining CFD and support vector regression (SVR) is proposed.
    Method Based 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.
    Results The 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.
    Conclusion Compared 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.

     

    • HTML全文
    • 参考文献(24)
    • 相关文章
    • 施引文献
  • 资源附件(0)

/

返回文章
返回