Inverse design of transonic airfoils using variable-resolution modeling and pressure distribution alignment

Abstract

The paper presents a computationally efficient and robust methodology for the inverse design of transonic airfoils. The approach replaces the direct optimization of an accurate, but computationally expensive, high-fidelity airfoil model by an iterative re-optimization of a corrected low-fidelity model. The low-fidelity model is based on the same governing fluid flow equations as the high-fidelity one, but uses coarser discretization and relaxed convergence criteria. The shape-preserving response prediction technique is utilized to align the pressure distribution of the low-fidelity model with that of the high-fidelity model. This alignment process is particularly suitable since a target pressure distribution is specified in the inverse design problem. The method is applied to constrained inverse airfoil design in inviscid transonic flow. The results show that the proposed method is able to match the target pressure distributions closely and requiring over 90 percent lower computational cost than when using only the high-fidelity model.