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Based on a volume of fluid two-phase model imbedded in the general computational fluid dynamics code FLUENT6.3.26, the viscous flow with free surface around a model-scaled KRISO container ship (KCS) was first numerically simulated. Then with a rigid-lid-free-surface method, the underwater flow field was computed based on the mixture multiphase model to simulate the bubbly wake around the KCS hull. The realizable k-ɛ two-equation turbulence model and Reynolds stress model were used to analyze the effects of turbulence model on the ship bubbly wake. The air entrainment model, which is relative to the normal velocity gradient of the free surface, and the solving method were verified by the qualitatively reasonable computed results.

Two computations of the KCS model with motions are presented. Self-propulsion in model scale free to sink and trim are studied with the rotating discretized propeller from the Hamburg Model Basin (HSVA) at Fr = 0.26. This case is particularly complex to simulate due to the close proximity of the propeller to the rudder. The second case involves pitch and heave in regular head waves. Computations were performed with CFDShip-Iowa version 4.5, a RANS/DES CFD code designed for ship hydrodynamics. The self-propulsion computations were carried out following the procedure described in Carrica et al. [1] , in which a speed controller is used to find the propeller rotational speed that results in the specified ship velocity. The rate of revolutions n , sinkage, trim, thrust and torque coefficients K T , K Q and resistance coefficient CT ( SP ) are thus obtained. Comparisons between CFD and EFD show that the rate of revolutions n , thrust and torque coefficients K T and K Q have higher prediction accuracies than sinkage and trim. For the simulation of pitch and heave in head waves, the geometry includes KCS hull and rudder under three conditions with two Froude numbers and three wave length and amplitude combinations. 0th and 1st harmonic amplitudes and 1st harmonic phase are computed for total resistance coefficient C T , heave motion z and pitch angle θ . Comparisons between CFD and EFD show that pitch and heave are much better predicted than the resistance. In both cases comparisons with simulations by other authors presented at the G2010 CFD Workshop [2] using different CFD methodologies are included.