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Heuristic optimization of submerged hydrofoil using ANFIS-PSO

机译：使用ANFIS-PSO的启发式水下翼型优化

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摘要

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.
机译：在这项研究中，通过启发式优化方法研究了淹没水翼的形状和工况的优化，该方法是基于自适应网络的模糊推理系统模型（ANFIS）和粒子群优化（PSO）的组合。约束离散变量（例如水翼的厚度和外倾角，攻角和淹没距离）明确定义为设计变量，升阻比选择为非线性目标函数，该函数是从精确的数值程序中提取的。对Navier-Stocks方程进行数值求解，并利用流体体积（VOF）方法来模拟两相流体（水和空气）。结果表明，在最佳操作条件下，水翼桨的主体应达到升阻比的最大值。

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