This paper presents a comprehensive optimization procedure for improving the keel and stern regions of a Tirhandil hull form in terms of resistance and wake characteristics. The optimization procedure involves a hybrid approach that combines CFD methods and CAD systems with a multi-objective genetic algorithm. According to the genetic algorithm, new hull forms are derived from the reference model (RF) by considering the design variables on the design splines and the design constraints. The optimization efforts concentrate on the keel and stern regions, where high resistance is observed. The study generates the new hull forms using CAD systems and predicts the hydrodynamic characteristics and flow field through CFD methods. A grid independence study determines the optimal mesh configuration for the numerical analyses. Validation studies are performed to assess the accuracy of the numerical analysis models by comparing the results obtained from the RANS models with experimental data. As a result of evaluating the objective functions using the Pareto Front approach, two hull forms with the best performance are selected as the optimal solutions (OP1, OP2). The optimized models (OP1, OP2) provide approximately 17% reduction in the resistance coefficient and about 5% reduction in the wake coefficient, with improved pressure and skin friction distributions in the keel and stern regions. Additionally, the optimized models form smoother wave transitions and lower amplitudes, with reduced or canceled stern waves. These effects are seen as resistance reduction, hence fuel consumption reduction in sailing cruise speed.
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