Journal of Marine Science and Technology, 2024 (SCI-Expanded)
This study introduces a methodology for multi-objective optimization of a high-speed vessel. The introduced methodology was put into practical application on benchmark form Model 5365, a 1/8.25 scaled representation of R/V Athena. The methodology combines fully parametric model generation, Reynolds-averaged Navier–Stokes (RANS) based resistance estimation, Strip Theory based seakeeping estimation, stability-check and genetic algorithm evaluation. CAESES, a simulation-based design (SBD) platform, was employed to consolidate the entire workflow and autonomously manage the procedural aspects. The non-dominated sorting genetic algorithm II (NSGA-II) was employed to optimize the conflicting objectives simultaneously. Pareto Frontiers were evaluated according to the scenarios created by weighting the objectives and compared with the initial hull (Model 5365). Consequently, it can be deduced that the utilization of the simulation-based design (SBD) technique proves to be effective in addressing multi-objective optimization issues pertaining to ship hydrodynamics.