Project Grant 2247005

This National Science Foundation award provides $267,114 to the University of California, Los Angeles through December 2025 to advance research on estimating and controlling gust-induced aerodynamics. The project aims to develop reinforcement learning techniques to mitigate the challenges posed by large-amplitude fluid disturbances, or gusts, encountered by energy and propulsion systems with lifting surfaces such as wind turbines, aircraft, and turbomachinery. Researchers will leverage prior computational and experimental work on unsteady aerodynamics to estimate coherent vortex structures in flows during wing or blade encounters with gusts using limited sensor data. Experiments and simulations across a range of Reynolds numbers will explore gust physics and the influence of pitching on encounters to inform reinforcement learning training of gust interaction control in a laboratory setting. This work supports the NSF Engineering program's goal of fostering innovation in engineering research areas critical to national economic strength and quality of life.