A new and better metamodel utilizing difference between high-and low-fidelity model

We construct a new and better metamodel, called by us LMIM(low-fidelity model improving method) model, by applying Kriging method and Latin Hypercube Design (LHD). It improves the fidelity of low-fidelity model utilizing the difference between high- and low-fidelity models. Sections 1 and 2 explain the construction of our metamodel and its application to three examples. Subsection 1.1 briefs LHD and subsection 1.2 briefs the Kriging model. Subsection 2.1 is entitled framework of LMIM metamodel; Fig. 1 shows its framework. Subsection 2.2 is entitled airfoil aerodynamic LMIM metamodel; Table 1 gives this example's design space; Figs. 3 through 6 and Table 2 give its calculation results. Subsection 2.3 is entitled wing aerodynamic LMIM metamodel; Figs. 7 through10 and Table 3 give its calculation results. Subsection 2.4 is entitled unmanned aerial vehicle radar cross section LMIM metamodel; Figs. 11 and 12 and Table 4 give its calculation results. Subsection 2.5 is entitled the mechanism analysis of LMIM metamodel; Figs. 13 and 14 give its calculation results. Section 3, based on the calculation results of the three examples and their analysis, gives the two following preliminary conclusions: (1) LMIM metamodel has greater computational efficiency than high-fidelity model; (2) it has higher fidelity and smaller database than the respective ones of traditional metamodel.