Data Assimilation Method for Turbine Cascade FlowField with Low Reynolds Number

SHEN Bin; PENG Hao; CHEN Liu; DAI Ren

doi:10.19805/j.cnki.jcspe.2026.240715

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Data Assimilation Method for Turbine Cascade FlowField with Low Reynolds Number

更新时间：2026-10-10

- Data Assimilation Method for Turbine Cascade FlowField with Low Reynolds Number
- Chinese Journal of Power Engineering Vol. 46, Issue 2, Pages: 36-44(2026)
- 作者机构：
  
  上海理工大学能源与动力工程学院,上海,200093
- 作者简介：
- 基金信息：
- DOI：10.19805/j.cnki.jcspe.2026.240715
  CLC：
- Online First：10 February 2026，
  
  Published：10 February 2026
- 稿件说明：
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沈斌,彭昊,陈榴,戴韧. 低雷诺数涡轮叶栅流场的数据同化方法动力工程学报, 2026, 46(2): 36-44 https://doi.

org/10.19805/j.cnki.jcspe.2026.240715
沈斌,彭昊,陈榴,戴韧. 低雷诺数涡轮叶栅流场的数据同化方法动力工程学报, 2026, 46(2): 36-44 https://doi. DOI： 10.19805/j.cnki.jcspe.2026.240715.

org/10.19805/j.cnki.jcspe.2026.240715 DOI：

摘要

低雷诺数涡轮叶栅流动的数值模拟结果与计算边界条件和湍流预测能力有关。应用集合卡尔曼滤波法

建立了基于少量实验测量数据与雷诺平均纳维-斯托克斯(RANS)方程计算流体力学(CFD)解的数据同化方法

并且在2种典型涡轮叶栅上验证了该方法。通过导向叶栅尾迹形态的测量值修正叶栅计算域入口的速度分布。同化后尾迹损失的平均相对误差减小了30%。在PakB叶型上

以叶片表面静压测量值同化剪切应力输运(SST)模型的8个预设常数。同化后叶片表面静压系数的平均相对误差减小了21%。基于实验测量的数据同化降低了CFD模拟中的不确定度

提升了RANS方程分析涡轮低雷诺数流动的可信度。

Abstract

The numerical simulation results of low Reynolds number turbine cascade flows are related to the computational boundary conditions and turbulence prediction capabilities. By applying the ensemble Kalman filtration method

a data assimilation approach was established

which is based on computational fluid dynamics (CFD) solutions obtained from a small amount of experimental measurement data and Reynolds-averaged Navier-Stokes (RANS) equations. After which

the proposed method was validated on two typical turbine cascades. The velocity distribution at the inlet of the cascade computational domain was corrected through using the measured values of the trail profile in the guide cascade. After assimilation

the average relative error of trail loss is reduced by 30%. For the PakB blade profile

eight preset constants of shear stress transport (SST) model were assimilated by using the measured values of static pressure on the blade surface. After assimilation

the average relative error of static pressure coefficient on the blade surface is reduced by 21%. With data assimilation based on experimental measurements

uncertainties in CFD simulations are reduced

and the credibility of analyzing low Reynolds number turbine flows by RANS equations is enhanced.

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references

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