Abstract
In this paper, a variable fidelity Kriging model approach is applied to aerodynamic data modeling and uncertainty quantification of 2D airfoil aerodynamic performances. This approach enables to construct an accurate surrogate model efficiently by utilizing high and low fidelity function information simultaneously. The low fidelity functions are defined by utilizing coarser computational meshes in this research. The uncertainty quantification is executed by Monte-Carlo simulation on the surrogate model, which is often referred to as Inexpensive Monte-Carlo simulation approach. The developed uncertainty quantification approach showed comparable accuracy with full non-linear Monte-Carlo simulation results and was executed with much lower computational cost.
