5 papers
Policy-DRIFT: Dynamic Reward-Informed Flow Trajectory Steering
Atharva Mahajan, Abhijeet Vishwasrao, Yuning Wang +1
Skin-friction drag induced by wall-bounded turbulent flows accounts for a substantial fraction of energy consumption across commercial aerospace, wind energy, and marine transport.…
High-lift Wing Separation Control via Bayesian Optimization and Deep Reinforcement Learning
Ricard Montalà, Bernat Font, Oriol Lehmkuhl +2
This study investigates active flow control (AFC) of a 30P30N high-lift wing at a Reynolds number Re = 450,000 and angle of attack = 23 using wallresolved large-edd…
Timescale Separation Enables Deep Reinforcement Learning Control of Rotating Detonation Engine Mode Transitions
Kristian Holme, Jean Rabault, Ricardo Vinuesa +1
Rotating detonation engines (RDEs) are a promising propulsion concept that may offer higher thermodynamic efficiency and specific impulse than conventional systems, but nonlinear p…
Physics-guided surrogate learning enables zero-shot control of turbulent wings
Yuning Wang, Pol Suarez, Mathis Bode +1
Turbulent boundary layers over aerodynamic surfaces are a major source of aircraft drag, yet their control remains challenging due to multiscale dynamics and spatial variability, p…
The HydroGym Reinforcement Learning Platform for Fluid Dynamics
Christian Lagemann, Sajeda Mokbel, Miro Gondrum +18
Modeling and controlling fluids is critical across science and engineering. Effective flow control can increase lift, reduce drag, enhance mixing, and attenuate noise, potentially…