Hydrodynamic hull form optimization of fast catamarans using surrogate models

This paper demonstrates the practical benefit of using efficient computational methods to optimize fast catamarans hydrodynamically. The development of a simplified panel method, which is based on thin ship theory, and the validation of the associated code for the prediction of the calm water resistance of twin-hull vessels is presented. The method was applied in the multi-objective optimization of a fast, zero-emission, battery-driven catamaran by a genetic algorithm, while considering the ensuing design constraints. Results of the study were compared with resistance predictions from a non-linear Rankine panel method and a viscous CFD solver. Moreover, surrogate models were implemented to speed up the optimization process involving several hundred parametrically generated designs. The proposed simplified panel method in connection with a empirical correction for the stern flow proved very valuable in the resistance prediction and hull form optimization of fast catamarans and of slender hulls in general.