1. 扬州大学 电气与能源动力工程学院,扬州,225127
2. 扬州大学 广陵学院,扬州,225000
孟令庭(1999—),男,江苏南京人,硕士研究生,研究方向:风力机空气动力学. E-mail:mz120211133@stu.yzu.edu.cn
杨华*(1975—),男,博士,教授,研究方向:流体机械及工程. E-mail:yanghua@yzu.edu.cn
纸质出版:2024
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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.
MENG Lingting, YANG Junwei, YANG Hua. Research on data assimilation of wind turbine airfoils in stall[J]. 2024, 42(4): 37-45.
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. DOI: 10.7638/kqdlxxb-2023.0113
MENG Lingting, YANG Junwei, YANG Hua. Research on data assimilation of wind turbine airfoils in stall[J]. 2024, 42(4): 37-45. DOI: 10.7638/kqdlxxb-2023.0113.
为验证数据同化优化湍流模型参数方法在不同厚度翼型上的效果以及同一优化参数在不同翼型上的适用性,对应用在风力机上的3种不同厚度的翼型(NACA63415、S809、DU97W300)进行失速流动下的数据同化研究。基于现有的风洞试验数据,使用集合卡尔曼滤波方法优化S-A(Spalart-Allramas)湍流模型的参数,确定各模型参数对数值模拟的影响程度,并对比同一翼型优化前后以及在不同翼型上计算的表面压力分布结果。结果表明,模型参数优化后,计算误差减小,模拟的气流分离点和压力分布曲线都更加贴近实验值。此外,翼型S809的优化参数同样可以减小另两个翼型的计算误差,能够适应其他翼型的气动性能计算,但是误差略大于其自身优化计算结果。同化后,3种翼型的模型参数中变化较大的是
$C_{{\rm{b}}1} $
<
img text_id='Z-20240530102017' class='formula-img' style='display:none;' src='2023-113_Z-20240530102017.jpg'>
、
$C_{\upsilon\text{1}}$
<
img text_id='Z-2024053007865294030' class='formula-img' style='display:none;' src='2023-113_Z-2024053007865294030.jpg'>
和
σ
,其中
$C_{{\rm{b}}1} $
<
img text_id='Z-20240530102017' class='formula-img' style='display:none;' src='2023-113_Z-20240530102017.jpg'>
变化幅度最大,且在各翼型上的变化趋势都表现为减小。因此可以推测
$C_{{\rm{b}}1} $
<
img text_id='Z-20240530102017' class='formula-img' style='display:none;' src='2023-113_Z-20240530102017.jpg'>
对于模型参数的适用性至关重要,至少对于本文研究的3种翼型而言是如此。
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
$C_{{\rm{b}}1} $
<
img text_id='Z-20240530102257' class='formula-img' style='display:none;' src='2023-113_Z-20240530102257.jpg'>
$C_{\upsilon\text{1}}$
<
img text_id='Z-20240530094030' class='formula-img' style='display:none;' src='2023-113_Z-20240530094030.jpg'>
and
σ
of which
$C_{{\rm{b}}1} $
<
img text_id='Z-20240530102257' class='formula-img' style='display:none;' src='2023-113_Z-20240530102257.jpg'>
undergoes the most prominent change
and decreases posterior of assimilation for all three airfoils. It is speculated that
$C_{{\rm{b}}1} $
<
img text_id='Z-20240530102257' class='formula-img' style='display:none;' src='2023-113_Z-20240530102257.jpg'>
is crucial for the model parameters' universality
at least for the present three airfoils
of the model parameters.
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