Shape optimization in ship hydrodynamics using computational fluid dynamics

A definite trend in computational applied mechanics is the development of integrated procedures for design optimization based on large-scale numerical simulations (Simulation-Based Design, SBD). In the present paper the fundamental elements of a SBD environment for shape optimization are presented and analyzed. The focus is on complex engineering optimization problems which involve computationally highly expensive objective functions and nonlinear constraints. Advanced strategies adopted for reducing the overall computational effort are illustrated, optimization algorithms for nonlinear programming problems are discussed as well as alternative techniques for shape variation and mesh manipulation, necessary to automatically adapt the volume grid to the evolving shapes. A new Verification and Validation (V&V) methodology for assessing errors and uncertainties in simulation based optimization is also introduced based on the trends, i.e., the differences between the numerically predicted improvement of the objective function and the actual improvement measured in a dedicated experimental campaign, including consideration of numerical and experimental uncertainties. Two different SBD versions are then presented and demonstrated on a complex industrial problem, namely the optimal shape redesign of a ship under real-world geometrical and functional constraints, whose evaluation during the optimization process involves repeated solutions of the Reynolds Averaged Navier–Stokes equations. Finally an experimental campaign is carried out on the two optimized models to validate the computations and assess the success of the optimization process. Both the optimized models demonstrate improved characteristics beyond the numerical and experimental uncertainties, confirming the validity of the SBD frameworks.