The factors influencing the accuracy of Kriging surrogate model including the number of sample points

the parameters of model and their types

were researched. The drag property of two-dimensional transonic airfoil was used to construct the surrogate model. The computational fluid dynamics (CFD) was employed to compute the drag coefficient. Three kinds of errors

i.e. average error

maximal error and standardized cross-validated residual were employed to measure the accuracy of the Kriging surrogate model while the cross validation was applied as the accuracy validation method. The results obtained are summarized as follows. First

the Kriging surrogate model performs well when predicting the aerodynamic drag of the two-dimensional transonic airfoil. Second

the accuracy of model improves with the increase of sample number

and when the ‘bizarre airfoil’ whose responses based on Kriging surrogate model are opposite with the normal ones are deleted

the accuracy of the model is improved obviously

and the average error and maximal error decrease 5%-38% and 13%-77% respectively. Third

the model accuracy is mainly affected by type of kernal function

followed by the correlation parameter

while the regression model has little influences. The Kriging surrogate model with Gauss correlation function

second order regression model and optimal correlation parameter has the best accuracy.