Efficient Multi-Objective Shape Optimization Using Variable Fidelity Performance Data

Abstract

A variable fidelity concept is introduced in the proper orthogonal decomposition (POD) based re-parameterization approach to efficiently solve multi-objective aerodynamic shape optimizations. The re-parameterization approach enables to extract dominant shape deformation modes from a database of good airfoil designs and to reduce the number of design variables. Our proposed variable fidelity approach is realized by utilizing low-fidelity functional evaluations to select the good airfoil designs. The validity of the proposed approach is investigated in a multi-objective aerodynamic shape optimization problem of 2D airfoil.