Low Speed Airfoil Optimization for Improved Multi-Point Performance of ACC Aircraft - Pangas, Guilherme Filipe da Silva (2024)
The advancement of computational capabilities has allowed for more efficient analysis and iteration of airfoil designs. Consequently, it has become possible to expand the design space and explore new geometries and configurations. However, the current state does not allow for a press-and-run optimization. The new capabilities have simply carried over the trial-and-error approach, previously used for the geometry, to the formulation of the optimization problem. The goal of this work is to study the formulation of an optimization problem and propose a new methodology that better portrays the aircraft’s requirements for airfoil performance. The new objective, based on the Aircargo Challenge 2022, is implemented by modifying an existing tool. This software has implemented a constraint multi-point optimization to improve the aircraft’s airfoil performance. The optimization is based on the free-gradient technique called Particle Swarm Optimization (PSO), using B-spline parametrization and a coupled viscous/inviscid interaction method. The new objective function, added to this program, estimates the performance of the aircraft developed for the competition, such as lift-off weight, the climb speed, and the maximum cruise and turn velocity. The estimations are done using a method that extrapolates the characteristics of the airfoil, analyzed through a sequence of operating points, into the aircraft’s performance. A penalty is then added to the score if any of the restrictions imposed are not met, and the sum is used as the objective function value. The dissertation includes two case studies. First, the PSO optimizer is evaluated through the effect of some of its settings on design space exploration and the resulting airfoil. The study concluded that the exhaustive option obtains the best and most consistent results among the settings studied. These results also provide an estimation of the airfoil and the score variance across different optimizations. Furthermore, in terms of the objective function, this case also reveals the tendency to increase the payload carried in order to obtain a higher flight score in the competition. In the second case study, the behavior of the new objective function under different initial conditions is analyzed. This investigation revealed the same trends in terms of scoring and validated/refuted some of the ACC2022 team’s decisions.