Heuristic optimization of submerged hydrofoil using ANFIS-PSO

In this research, optimization of shape and operating conditions of a submerged hydrofoil is investigated by a heuristic optimization approach, been a combination of an adaptive network based fuzzy inference system model (ANFIS) and particle swarm optimization (PSO). The constrained discrete variables such as the thickness and camber of hydrofoil, angle of attack and submerge distance are clearly defined as design variables and the lift to drag ratio is selected as a nonlinear objective function, which is extracted from an accurate numerical procedure. The Navier-Stocks equation is numerically solved, and volume of fluid (VOF) method has been utilized to simulate two-phase fluid (water and air). The results demonstrate that the resulted body of the hydrofoil in the optimum operating conditions should reach a maximum value of lift to drag ratio.