arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2406.05415physics.flu-dyn
收藏

基于致动线模型的低成本风力机气动声学预测

Low-cost wind turbine aeroacoustic predictions using actuator lines

Laura Botero-Bolivar, Oscar A Marino, Cornelis H. Venner, Leandro D. de Santana, Esteban Ferrer

AI总结:

本文提出将致动线大涡模拟与基于Amiet-Schlinker理论的快速噪声预测方法耦合,利用XFOIL计算截面气动参数,实现对风力机气动噪声的低成本高保真预测,并通过全尺寸机组现场测量验证了方法的有效性。

摘要:

气动噪声是进一步开发风能资源的一个限制因素。由于这类噪声由湍流与机身相互作用引起,因此需要对流动进行精细解析,才能准确预测远场噪声。计算流体力学(CFD)求解器可以模拟流场,但计算成本很高,当进一步解析声场时成本会大幅增加。因此,利用数值方法进行风力机噪声预测仍然是一个挑战。本文提出了一种方法,将使用致动线模型且计算速度相对较快的风力机CFD模拟与一种快速周转的噪声预测方法耦合起来。流场采用致动线模型和大涡模拟进行仿真。噪声预测方法基于Amiet-Schlinker旋转噪声源理论,将前缘噪声和后缘噪声视为唯一的噪声源。二维面元代码(XFOIL)用于计算截面力和边界层参数。由于在流动预测和声学预测中都考虑了风力机几何形状,所得到的噪声预测方法具有较高的保真度。将结果与一台全尺寸风力机在两种运行工况下的现场测量数据进行了对比,验证了本研究的有效性。

英文摘要:

Aerodynamic noise is a limitation for further exploitation of wind energy resources. As this type of noise is caused by the interaction of turbulent flow with the airframe, a detailed resolution of the flow is necessary to obtain an accurate prediction of the far-field noise. Computational fluid dynamic (CFD) solvers simulate the flow field but only at a high computational cost, which is much increased when the acoustic field is resolved. Therefore, wind turbine noise predictions using numerical approaches remain a challenge. This paper presents a methodology that couples (relatively fast) wind turbine CFD simulations using actuator lines with a fast turn-around noise prediction method. The flow field is simulated using actuator lines and large eddy simulations. The noise prediction method is based on the Amiet-Schlinker's theory for rotatory noise sources, considering leading- and trailing-edge noise as unique noise sources. A 2D panel code (XFOIL) calculates the sectional forces and boundary layer quantities. The resulting methodology for the noise prediction method is of high fidelity since the wind turbine geometry is accounted for in both flow and acoustics predictions. Results are compared with field measurements of a full-scale wind turbine for two operational conditions, validating the results of this research.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

↑