Assessment of bimodal sea states by the wave buoy analogy method

The paper focuses on the development of a new algorithm, based on the wave buoy analogy, for bimodal sea state conditions. After a brief review about the worldwide persistence of bimodal sea states, the theoretical background is outlined. The ship accelerations, due to wind sea and swell components, are preliminarily estimated by iteratively applying a high and a low-pass filters to the ship motion time history. The prevailing directions of wind sea and swell are provided by weather forecast platforms, while the remaining sea state parameters are estimated by maximizing the correlation coefficient between measured and tentative filtered acceleration spectra in the encounter wave frequency domain. A wide ship motion synthetic dataset of a containership is simulated by solving the Cummins equations and randomly varying the sea state parameters, in order to investigate the statistics of errors on the prevailing wave direction, the significant wave height and the wave energy period of the equivalent sea state condition. The incidence of the time interval between two subsequent sea state measurements is also investigated. Based on current result, the new algorithm provides an accurate estimate of the main sea state parameters, which seems promising for future research activities.