Uncertainty analysis of wind tunnel test data based on Noise-Kriging

Wind tunnel test data often do not have repeated test samples for specific models, which makes it difficult to evaluate the aerodynamic uncertainty of test data. Based on the limited experimental data, a Noisy-Kriging (N-Kriging) based modeling and uncertainty analysis method is developed. N-Kriging optimizes the model parameters in the modeling process, realizes the reasonable estimation of the noise, and realizes the high-precision aerodynamic force prediction. The advantages of this method are verified by the typical one-dimensional and two-dimensional function examples. The N-Kriging method is used to model and analyze the uncertainty of the wind tunnel test data of a hypersonic flight vehicle, and the high-precision aerodynamic data prediction and data noise evaluation are realized. The results show high precision and reliable confidence. The uncertainty estimation results of the test data are tested, and the 95% confidence interval prediction results of N-Kriging are highly consistent with the actual data distribution. The numerical example shows that this method can evaluate the aerodynamic noise and analyze the uncertainty of the limited experimental data.