5 papers
High-lift Wing Separation Control via Bayesian Optimization and Deep Reinforcement Learning
Ricard MontalÃ, 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-ed…
Atmospheric boundary layer over urban roughness: validation of large-eddy simulation
Ming Teng, Josep M. Duró Diaz, Ernest Mestres +3
The study presents wall-modeled large-eddy simulations (LES) characterizing the flow features of a neutral atmospheric boundary layer over two urban-like roughness geometries: an a…
Differentially heated turbulent channel flow two-point correlations
Marina Garcia-Berenguer, Lucas Gasparino, Oriol Lehmkuhl +1
This study analyzes the behavior of a differentially heated channel flow by means of a direct numerical simulations (DNS) with variable thermophysical properties under low-speed co…
Turbulent Boundary Layer in a 3-Element High-LiftWing: Coherent Structures Identification
Ricard MontalÃ, Benet Eiximeno, Arnau Miró +2
A wall-resolved large-eddy simulation (LES) of the fluid flow around a 30P30N airfoil is conducted at a Reynolds number of Rec=750,000 and an angle of attack (AoA) of 9 degrees. Th…
Towards Active Flow Control Strategies Through Deep Reinforcement Learning
Ricard MontalÃ, Bernat Font, Pol Suárez +3
This paper presents a deep reinforcement learning (DRL) framework for active flow control (AFC) to reduce drag in aerodynamic bodies. Tested on a 3D cylinder at Re = 100, the DRL a…