Hydrodynamic hull form optimization of fast catamarans using surrogate models

Abstract

ABSTRACT 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.