Shape optimization for otter board using computational fluid dynamics analysis and response surface methodology

In this study, a method for optimizing the design of otter boards by computational fluid dynamics (CFD) analysis was developed. The optimization was based on response surface methodology. Here, a neural network model was employed for the response surface, then the design parameters of the otter board were optimized by a multi-objective genetic algorithm. In the optimization, lift and drag coefficients (CL and CD) were employed for the objective function such that CL was maximized and CD was minimized. The proposed method was applied to the biplane-type otter board. The hydrodynamic characteristics of the optimized otter board were compared with those of a comparative model. In the balanced model, one of the optimized models, CL was slightly increased, and CD was decreased by 14% compared with the comparative model. Furthermore, the separation area of the optimized model was decreased relative to the comparative model. From these results, it was concluded that the proposed optimization method is useful for designing otter boards with CFD.