Xiaosong Du

TL;DR: In this article, a B-spline-based generative adversarial network (GAN) is used to filter out unrealistic airfoils for a reduced design space that contains all relevant airfoil shapes.

TL;DR: In this article , the authors review the applications of ML in aerodynamic shape optimization (ASO) and provide a perspective on the state-of-the-art and future directions.

TL;DR: Two-dimensional benchmark cases involving lift-constrained drag minimization in inviscid and viscous transonic flows are solved using derivative-free multi-fidelity optimization algorithms (space mapping and manifold mapping) and are compared with direct gradient-based optimization algorithms using adjoint sensitivities and trust regions.

TL;DR: In this paper, a polynomial chaos expansion metamodel with the least-angle regression and the hyperbolic truncation scheme are used to accelerate the uncertainty propagation and the optimization process.