Performance Enhancement of Fluidic Diode for a Wave Energy System through Genetic Algorithm

Emeel Kerikous, Doddamani Hithaish, Abdus Samad, S. Hoerner, Dominique Thévenin
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Abstract

The oscillating water column (OWC) is an extensively studied wave energy converter that produces pneumatic power from the motion of the sea waves, which can be harvested using a pair of turbines without additional devices. However, its efficiency is hampered by poor flow blockage. Researchers have proposed a fluidic diode (FD) to improve flow blockage. Its performance is given by diodicity, which is the ratio of pressure drop in reverse to forward flow. A higher resistance in the reverse path signifies enhanced flow blockage, while a lower resistance in the forward flow minimises power loss at the turbine entry. In the present study, the numerical investigation was performed by solving three-dimensional unsteady Reynolds-Averaged Navier Stokes equations using ANSYS-Fluent 16.1 to simulate the flow behaviour inside the FD. Five geometrical parameters for FD were varied to obtain its optimal shape leading to a lower pressure drop in the forward direction and higher in reverse. The optimal shape was obtained through the genetic algorithm, showing a 12% improvement in performance compared to the base model. Detailed fluid flow and performance analysis of both base and optimum models are presented in this article.
用遗传算法增强波能系统的流控二极管性能
振荡水柱(OWC)是一种被广泛研究的波浪能转换器,它从海浪的运动中产生气动动力,可以使用一对涡轮机收集,而不需要额外的设备。然而,其效率受到流动阻塞不良的影响。研究人员提出了一种流体二极管(FD)来改善流动阻塞。它的性能是用逆压降与正流压降之比来表示的。较高的阻力在反向路径表示增强流动阻塞,而较低的阻力在正向流动最小化功率损失在涡轮入口。本文采用ANSYS-Fluent 16.1软件对三维非定常reynolds - average Navier - Stokes方程进行数值模拟,模拟FD内部的流动特性。通过改变FD的5个几何参数,得到FD的最佳形状,使其正向压降较低,反向压降较高。通过遗传算法获得最优形状,与基本模型相比,性能提高了12%。本文对基本模型和优化模型进行了详细的流体流动和性能分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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