Low-speed airfoil optimization using CFD and low fidelity solvers
Mihai-Vlăduț HOTHAZIE, Mihai Victor Pricop, Ionuț BUNESCU · AIAA SCITECH 2023 Forum · 2023
View Video Presentation: https://doi.org/10.2514/6.2023-1013.vid Although the aviation sector has become more fuel-efficient, the need of reducing the carbon footprint pushes aerodynamic optimization forward. Even if low fidelity methods such as panel methods coupled with viscous models are widely used in the airfoil optimization processes to determine the aerodynamic performance due to their low computational time, in certain scenarios they can predict misleading results that do not reflect the physical phenomena. Hence, a verification method against high-fidelity CFD analysis is required. While the computational time required to carry out the analysis is increased, advances in computational power have enabled the use of high-fidelity models for 2D aerodynamic optimization. This paper approaches an improved certainty level prediction using high-fidelity CFD analysis. For optimization two evolutionary algorithms are considered (Genetic Algorithm and Differential Evolution Algorithm). A parametric study of the design space was performed to determine an overview of the objective function behavior. In the end, the results obtained using both optimization algorithms and both solvers (low and high-fidelity) are compared, and corresponding conclusions are drawn.