A machine learning method for the evaluation of hydrodynamic performance of floating breakwaters in waves - Saghi, Hassan; Mikkola, Tommi; Hirdaris, Spyros (Ships and offshore structures, 2022)
This paper presents a two-dimensional simulation model for the idealisation of moored rectangular and trapezoidal floating breakwaters (FB) motions in regular and irregular waves. Fast-Fictitious Domain and Volume of Fluid methods are coupled to track-free surface effects and predict FB motions. Hydrodynamic performance is assessed by a machine learning method based on Cuckoo Search-Least Square Support Vector Machine model (CS-LSSVM). Results confirm that a suitable combination of the aspect ratio of an FB and her sidewall mooring angle could help attenuate incoming waves to a minimum height. It is concluded that moored trapezoidal FBs are more efficient than traditional rectangular designs and subject to further validation CS-LSSVM can be useful in terms of optimising the values of predicted wave transmission coefficients.