15 citations · 15 across the 2 of their papers we have counts for
3 papers
physics.flu-dyn2024★ 15 cited
Model-Based Reinforcement Learning for Control of Strongly-Disturbed Unsteady Aerodynamic Flows
Zhecheng Liu, Diederik Beckers, Jeff D. Eldredge
The intrinsic high dimension of fluid dynamics is an inherent challenge to control of aerodynamic flows, and this is further complicated by a flow's nonlinear response to strong di…
physics.flu-dyn2024
Deep reinforcement learning of airfoil pitch control in a highly disturbed environment using partial observations
Diederik Beckers, Jeff D. Eldredge
This study explores the application of deep reinforcement learning (RL) to design an airfoil pitch controller capable of minimizing lift variations in randomly disturbed flows. The…
physics.flu-dyn2021
Planar potential flow on Cartesian grids
Diederik Beckers, Jeff D. Eldredge
Potential flow has many applications, including the modelling of unsteady flows in aerodynamics. For these models to work efficiently, it is best to avoid Biot-Savart interactions.…