This paper presents an integrated hydrodynamic optimization tool and the application of the tool to the design of a modern container ship. Instead of using very complex and computationally expensive CFD solvers with standard optimization methods, the present tool adopts the variable fidelity method that uses lower-fidelity models and a scaling function to approximate the higher-fidelity models to reduce computational cost. An Euler based finite-element flow solver and a linear potential theory based flow solver are used as high-fidelity model and lower-fidelity model, respectively. To update the domain grid automatically during the optimization, the radial basis function interpolation method is adopted. The present variable fidelity method is globally convergent to the solution of the original and high-fidelity problem. The radial basis function interpolations are effective in deforming unstructured domain mesh according to updated hull form and keeping the quality of mesh after deformation. For purposes of illustration, the present hydrodynamic optimization tool is used to determine the optimal hull form of a modern container ship by minimizing the wave resistance for a given design speed with a displacement constraint.
Hydrodynamic optimization is an important aspect of ship design. In order to perform hydrodynamic design optimization, an objective function that compares the merit of different designs quantitatively needs to be defined. This objective function depends on design variables, and the changes in flow variables due to them. The aim is then to minimize (or maximize) this objective function subject to PDE (Partial Differential Equations that govern the flow) constraints, geometry constraints, and physical constraints. The CFD-based hull form hydrodynamic optimization consists of CFD solver/solvers that can be used to compute the flow field and evaluate the objective function and its gradient if required by the optimization technique, hull geometry representation and modification that are linked to the design variables, optimization technique that can be used to minimize the objective function under given constraints.