Airfoil Shape Design and Optimization Using Multifidelity Analysis and Embedded Inverse Design

Abstract

Design optimization using high-fidelity computational fluid dynamics simulations is becoming increasingly popular, sustaining the desire to make these methods more computationally efficient. A reduction in problem dimensions as a result of improved parameterization techniques is a common contributor to this efficiency. The focus of this paper is on the high-fidelity aerodynamic design of airfoil shapes. A multifidelity design search method is presented which uses a parameterization of the airfoil pressure distribution followed by inverse design, giving a reduction in the number of design variables used in optimization. Although an expensive analysis code is used in evaluating airfoil performance, computational cost is reduced by using a low-fidelity code in the inverse design process. This method is run side by side with a method which is considered to be a current benchmark in design optimization. The two methods are described in detail, and their relative performance is compared and discussed. The newly presented method is found to converge towards the optimum design significantly more quickly than the benchmark method, providing designs with greater performance for a given computational expense.