空气动力学学报2024，Vol.42Issue(4)：37-45,9.DOI:10.7638/kqdlxxb-2023.0113
风力机翼型失速流动数据同化
Research on data assimilation of wind turbine airfoils in stall
摘要
Abstract
In the present paper,we utilize the ensemble Kalman filter(EnKF)method to optimize parameters of the turbulence model Spalart-Allramas(S-A)to simulate flow fields around three wind turbine airfoils(NACA63415,S809,and DU97W300)at the same stall degree.The optimized parameters of the medium-thickness airfoil S809 are further applied to the other two airfoils to investigate their performance on airfoils with various thicknesses.For each airfoil,comparisons to experimental data regarding the pressure coefficient distribution and separation location show that using the optimized parameters can reduce numerical errors significantly.Even though applying the optimized parameters of S809 to the other two can also considerably reduce the numerical errors,the errors are slightly larger than those obtained by the optimized parameters of their own.In addition,the model parameters with significant changes after assimilation are Cb1,Cυ1,and σ,of which Cb1 undergoes the most prominent change and decreases posterior of assimilation for all three airfoils.It is speculated that Cb1 is crucial for the model parameters'universality,at least for the present three airfoils,of the model parameters.关键词
数据同化/集合卡尔曼滤波/失速/S-A湍流模型/压力分布Key words
data assimilation/ensemble Kalman filter/stall/S-A turbulence model/pressure distribution分类
能源科技引用本文复制引用
孟令庭,杨俊伟,杨华..风力机翼型失速流动数据同化[J].空气动力学学报,2024,42(4):37-45,9.基金项目
扬州市自然科学基金(YZ2023169) （YZ2023169）
