Robust optimization with Gaussian process models

Abstract

In this chapter, the application of the Gaussian regression models in the robust design and uncertainty quantification is demonstrated. The computationally effective approach based on the Kriging method and relative expected improvement concept is described in detail. The new sampling criterion is proposed which leads to localization of the robust optimum in a limited number of steps. The methodology is employed to the optimal design process of the intake channel of the small turboprop engine.