Fast modelling of wavy wind turbine trailing edge for reducing noise and power loss

由于轻型材料和结构完整性要求，叶片尾缘的气动和气动声学性能是现代风力涡轮机可行性和可操作性的关键。波浪形尾缘在降低噪声和总压力损失方面具有巨大的优势。数值模拟在理解这些新型几何形状的流动物理特性和预测其性能方面起着重要作用。然而，对于大规模应用，高分辨率的大涡模拟虽然非常有能力，但对于工业用途是不切实际的。首先，该项目将使用分辨率高的大涡模拟（LES）对波浪状尾缘周围的复杂流动模式进行大量研究。随着知识和数据库的创建，它将为波浪后缘开发机器学习增强RANS模型。人们的期望是，与LES相比，新方法可以更快，而不会损失太多的精度。该项目还将致力于与欧洲的风力涡轮机行业合作，并将在当地和全国范围内使用高性能计算设施。

Aerodynamic and aeroacoustic behaviours of blade trailing edge hold keys to the viability and operability of modern wind turbines due to light-weight materials and structure integrity requirements. Wavy trailing edges have demonstrated tremendous benefits in terms of reducing noise and total pressure losses. Numerical simulation plays an important role in understanding the flow physics and predicting the performance of these novel geometries. However, for large scale applications, highly resolving large-eddy simulations, while very capable, are impractical for industrial uses. Primarily the project will heavily study the complex flow patterns around the wavy trailing edges using well-resolved Large-Eddy Simulations (LES). With the knowledge and databased created, it will then develop machine-learning augmented RANS modelling for wavy trailing edges. The expectation is that the new approach could be much faster without losing too much accuracies compared to LES.The project will also aim to collaborate with the wind turbine industry in Europe and will make use of High Performance Computing facilities locally and nationally.