LAUSR

Airfoils play significant roles in aerodynamic engineering as they are important devices in designing aircraft and engines. For airfoils, geometric design variables often deviate from nominal values that deteriorate airfoil quality. Thus, the design optimization of airfoils under the noises of design variables is important. However, the existing literature does not consider functional responses that can more adequately describe airfoil performances than univariate and multivariate responses. To fill in this gap and further improve airfoil quality, we develop a surrogate-based robust parameter design methodology for the design optimization of airfoils with functional responses. A new optimization criterion that involves both location and dispersion effects associated with the functional feature of quality losses, noises of design variables, and emulator uncertainty is proposed. A Gaussian process (GP) model with functional responses is employed as a surrogate/emulator. An efficient method for computing the proposed criterion is developed. The proposed methodology is applied to a typical airfoil design optimization problem to demonstrate that better and more robust solutions are obtained with the proposed criterion for airfoils, and the computing time is significantly reduced with the proposed estimation method.