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    A Robust Polynomial-Based Machine Learning Algorithm for the Ship Roll Equations Under Different Wave Excitation: A Hybrid Approach 

    Source: Journal of Offshore Mechanics and Arctic Engineering:;2026:;volume( 148 ):;issue:004:;page 6
    Author(s): Krithikka, S.; Hariharan, G.
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Abstract. Accurate modeling of ship roll dynamics under varying wave excitations remains challenging due to nonlinear system behavior and measurement noise. This study presents a physics-informed neural network (PINN) for ...
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    A Robust Computational Algorithm for a Class of Unsteady-State Free-Surface Models in Ship Hydrodynamics 

    Source: Journal of Computational and Nonlinear Dynamics:;2026:;volume( 021 ):;issue:006:;page 101
    Author(s): Kavitha, J.; Hariharan, G.; Kannan, T.
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Abstract. In this paper, we present an efficient stable set polynomial of the complete bipartite graph algorithm (SPBA) to address the time-dependent free-surface behavior resulting from unsteady ship movements. Analytical ...
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    Two Robust Computational Algorithms for a Few Nonlinear Roll Damping Models in Ocean Engineering: A Novel Graph Polynomial Approach 

    Source: Journal of Computational and Nonlinear Dynamics:;2026:;volume( 021 ):;issue:009:;page 180
    Author(s): Kavitha, J.; Hariharan, G.; Kannan, K.
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Abstract. Accurate prediction of ship roll motion is challenging due to strong nonlinear damping effects that directly impact vessel safety. This study introduces two novel graph theoretic spectral algorithms, namely, the ...
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