Abstract
The present work focuses on the application of simulation-based design for the resistance optimization of waterjet propelled Delft catamaran, using integrated computational and experimental fluid dynamics. A variable physics/variable fidelity approach was implemented wherein the objective function was evaluated using both low fidelity potential flow solvers with a simplified CFD waterjet model and high fidelity RANS solvers with discretized duct flow calculations. Both solvers were verified and validated with data for the original hull. The particle swarm optimizer was used for single speed optimization at Fr=0.5, and genetic algorithms were used for multi speed optimization at Fr=0.3, 0.5 and 0.7. The variable physics/variable fidelity approach was compared with high fidelity approach for the bare-hull shape optimization and it showed an overall CPU time reduction of 54% and converged to the same optimal design at Fr=0.5. The multi-speed optimization showed design improvement at Fr=0.5 and 0.7, but not at Fr=0.3 since the design variables were obtained based on sensitivity analysis at Fr=0.5. High fidelity simulation results for the optimized barehull geometry indicated 4% reduction in resistance and the optimized waterjet equipped geometry indicated 11% reduction in effective pump power required at self-propulsion. Verification was performed for the optimized hull form and its reduction in powering will be validated in forthcoming experimental campaign.