Study of metamodel sampling criterion

For certain problem, a practical criterion which is to distill information from known space to guide sampling in another space is proposed in the paper. A mathematical function is taken as illustration to reflect influences of several factors based on Kriging and Latin Hypercude Design Sampling. The influence of design space to sampling is discussed firstly, and then the impact of samples distribution to metamodel prediction accuracy is analyzed. In order to describe the samples distribution characteristics, concepts of mean density, distant density and close density are defined. The distant sampling criterion is proposed according to the relationships of the parameters and metamodel prediction error. Both different-dimensional mathematical functions and airfoil aerodynamic analysis model are investigated to demonstrate its veracity and practicability.