Soft-Finite-Element-Method-Driven Multiphysics Airfoil Optimization

Abstract

The soft finite element method (SoftFEM) was recently developed as an efficient black-box engineering optimization framework combining population-based evolutionary global optimization and a local search technique using a hybrid self-adaptive strategy. This framework simultaneously leverages exploration and exploitation without the need to know a priori which strategy is best fitted to the problem at hand. In this work, we first improve SoftFEM by replacing the original differential evolution by the so-called success-history-based adaptive differential evolution. The developed framework is then applied to optimize the aerodynamic performance of 1) an airfoil, 2) a wing, and 3) the fluid–structure interaction problem of an airfoil with a flexible trailing edge. In the first two cases, the open-source computational fluid dynamics code OpenFOAM is considered to evaluate the aerodynamic characteristics of the airfoil, while in the latter case, we combine OpenFOAM and MuPhiSim—our recently released open-source code for computational solids mechanics—to conduct fluid–structure interaction simulations. The results demonstrate that this approach can effectively find optimal solutions with improved aerodynamic performance in all three cases. The proposed framework has the potential to significantly impact the design and optimization of aerodynamic systems in complex design spaces. In particular, new systems involving soft components and soft–hard junctions would benefit from a seamless application of the developed framework to their optimization.