AI Control to Reduce Aircraft Mid-Air Stalls and Drops cover art

AI Control to Reduce Aircraft Mid-Air Stalls and Drops

AI Control to Reduce Aircraft Mid-Air Stalls and Drops

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 A recent study explored using artificial intelligence to mitigate dangerous airflow detachment on aircraft wings. Researchers at KTH Royal Institute of Technology and the Barcelona Supercomputing Center tested a deep reinforcement learning (DRL) system to optimise synthetic jets that manipulate airflow. The AI learned to control these jets more effectively than periodic activation, reducing turbulence separation bubbles by 9%. This approach aims to prevent stalls and improve aircraft control by maintaining proper airflow, crucial when the wing is at a high angle of attack. The study underscores the potential of AI in enhancing aerodynamics and energy efficiency in aviation.

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