| Citation: | Zeng Fei, LI Tang, Ouyang Yuqing. Flow field reconstruction method and application for turbine blade cascade based on experimental data assimilation[J]. Journal of Aerospace Power, 2026, 42（X）：20250038 doi: 10.13224/j.cnki.jasp.20250038
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To improve the efficiency of linear cascade row experiment, this study employs the principles of ensemble Kalman filtering. A Latin hypercube sampling method is used to generate a set matrix of SST turbulence model parameters, computational data, and experimental data. The KNN algorithm is applied to align the resolution errors between different datasets. A data assimilation program suitable for linear cascade rows is developed. The program is used for data assimilation analysis of the flow field under various operating conditions of a linear cascade row with a wide range of attack angles.Experimental data from three strategies are incorporated to re-calibrate the coefficients of the SST turbulence model. The assimilation results show a high degree of agreement with the experimental data. The findings indicate that, under different operating conditions, all three assimilation strategies reduce the relative error between numerical calculations and experimental data by more than 64.7%. Therefore, assimilated data can be appropriately trusted in experiments to adjust experimental plans, which helps improve experimental efficiency and reduce costs.
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