Airfoil shape design and optimization using multifidelity analysis and embedded inverse design

Description/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.