Humans have always developed tools or technologies to help us surmount challenges. Obstacles encourage people to innovate. The airfoil design problem—where an engineer works to build a shape with desired characteristics, such as maximizing lift while minimizing drag—presents an opportunity for innovation. Researchers at the National Renewable Energy Laboratory (NREL) are building computational tools using artificial intelligence (AI) that can help optimize airfoil design for wind turbine blades, aircraft wings, and fan blades in natural gas turbines.

“Wind turbine airfoil and blade design is a complex, interdisciplinary process that must balance a wide range of objectives in the shifting landscape of customer demands, policy regulations, and technological innovations,” said Andrew Glaws, an NREL computational science researcher working to pave the way for improved airfoil designs. “Further, design iterations must move extremely quickly to keep pace with the market. To achieve all of this, designers use cheap, low-fidelity tools to rapidly create and assess new designs. Our work seeks to inject higher fidelity insights (e.g., nonlinear aerodynamic effects) into the design process without affecting their tight timelines.”

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https://www.nrel.gov/news/program/2023/invertible-neural-network-tool-helps-optimize-airfoil-design.html