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Neuro-fuzzy based approach for estimation of Hydrofoil performance

机译：基于神经模糊的水翼性能评估方法

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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.
机译：在这项研究中，采用数值方法求解水下翼型上的Navier-Stokes方程，并通过自适应神经模糊推理系统（ANFIS）模型完成翼型性能的估算。基于压力的隐式技术和具有并置有限体积公式的非正交网格用于模拟水翼周围的流动。该程序结合了k-ε涡流粘性湍流模型，并且已经利用流体体积（VOF）过程来模拟两相流体（水和空气）。在提到的方法中，对水翼的厚度和外倾效应，淹没距离（h / c）和攻角（AOA）的分析给水翼的性能留下了深刻的印象。为了验证数值模拟，将部分结果与已发布的实验数据进行了比较。这种比较证实了数值过程。此外，通过ANFIS模型评估了水翼的配置和操作条件。因此，结果证明了ANFIS模型可以很好地预测水翼性能。

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