Abstract Machine learning (ML) has been increasingly used to aid aerodynamic shape
optimization (ASO), thanks to the availability of aerodynamic data and continued …

Automated design synthesis has the potential to revolutionize the modern engineering
design process and improve access to highly optimized and customized products across …

Aerodynamic optimization based on computational fluid dynamics (CFD) is a powerful
design approach because it significantly reduces the design time compared with the human …

Surrogate-based optimization has been used in aerodynamic shape optimization, but it has
been limited due to the curse of dimensionality. Although a large number of variables are …

Global optimization of aerodynamic shapes usually requires a large number of expensive
computational fluid dynamics simulations because of the high dimensionality of the design …

Generative design provides a promising algorithmic solution for mass customization of
products, improving both product variety and design efficiency. However, the current …

Airfoil design and surrogate modeling for performance prediction based on deep learning
method | Physics of Fluids | AIP Publishing Skip to Main Content Umbrella Alt Text Umbrella Alt …

Deep generative models are proven to be a useful tool for automatic design synthesis and
design space exploration. When applied in engineering design, existing generative models …

Low-Reynolds-number high-lift airfoil design is critical to the performance of unmanned
aerial vehicles (UAV). However, since laminar-to-turbulent transition dominates the …

The use of computational fluid dynamics (CFD) to optimize the aerodynamic shape of rotor
airfoils with the aim of suppressing dynamic stall is computationally expensive and …