Neuro-fuzzy based approach for estimation of Hydrofoil performance

In this research, a numerical procedure is used to solve the Navier-Stokes equation on a submerge hydrofoil and the estimation of hydrofoil performance is done by an Adaptive Neuro-Fuzzy Inference System (ANFIS) model. A pressure-based implicit technique and a non-orthogonal mesh with collocated finite volume formulation are used to simulate flow around the hydrofoil. The procedure incorporates the k−ε eddy-viscosity turbulence model and a Volume of Fluid (VOF) process has been utilized to simulate two-phase fluid (water and air). In the mentioned method, the analyses of thickness and camber effect of hydrofoil, submerge distance (h/c), and the angle of attack (AOA) make an impression on the hydrofoil performance. To verify the numerical simulation, a part of the presented results is compared with the published experimental data. This comparison confirms the numerical process. Moreover, the hydrofoil configuration and operating condition are assessed by ANFIS model. Consequently, the results prove that the ANFIS model can predicate the hydrofoil performance very well.

► Adaptive Neuro-Fuzzy Interface System is used to predict the hydrodynamic performance.
► Effect of hydrofoil configurations (camber and thickness) is numerically simulated.
► Influence of submerge distance and angle of attack is studied on the performance.
► The lift and drag coefficient predictions prove a good accuracy of the model.
► The model can be used as a reference for future hydrodynamic performances studies.