Abstract

There have been many attempts worldwide to reduce ships׳ fuel consumption. With fuel-efficiency improvement as their designed purpose, a variety of energy saving devices (ESD) have been developed and deployed. Much research with respect to ESD performance already has been carried out; however, the issue of ESD structural safety has received relatively little attention. According to the current approach to ESD structural safety assessment, the Morison equation, which is calculated for a certain probability-level velocity, is applied, or alternatively, a spectral method based on the assumption of a linear system between wave and response is utilized. Unfortunately, this methodology does not take into account the nonlinearity of hydrodynamic loads. Therefore, a new ESD structural safety assessment procedure that utilizes the neural network and time-domain simulation using the Gumbel fitting method is herein proposed. The procedure entails four main steps: sea-keeping analysis, hydrodynamic load analysis and neural network, ultimate strength analysis, and fatigue strength analysis. The important features of the proposed procedure are, in order, as follows. First, to consider the nonlinearity of hydrodynamic force acting on the ESD, computational fluid dynamics (CFD) analysis is carried out on samples consisting of various wave heights and periods. The neural network is then trained based on the CFD analysis results for the prediction of hydrodynamic loads. Second, to take into account the randomness of the peak hydrodynamic force, a three-hour time-domain simulation is repeated 20 times for each sea state of a wave-scatter diagram, and Gumbel parameters are calculated for long-term analysis. Third, approximate long-term analyses using a contribution coefficient and short-term analysis are performed for an efficient long-term analysis.

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