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Lehmkuhl, Oriol

  1. Deep-reinforcement-learning-based separation control in a two-dimensional airfoil
    2025/02/24 by Xavier Garcia, Arnau Miró, Garcia, Xavier +13 · 4 citations
    Engineering · Physics and Astronomy · #Plasma and Flow Control in Aerodynamics #Fluid Dynamics and Turbulent Flows #Model Reduction and Neural Networks
  2. Deep reinforcement learning for flow control exploits different physics for increasing Reynolds-number regimes
    2022/11/04 by Pau Varela, Varela, Pau, Pol Suárez +15 · 2 citations
    Engineering · Physics and Astronomy · #FOS: Physical sciences #Fluid Dynamics (physics.flu-dyn) #Fluid Dynamics and Turbulent Flows #Fluid Dynamics and Vibration Analysis #Model Reduction and Neural Networks
  3. Towards Active Flow Control Strategies Through Deep Reinforcement Learning
    2024/11/08 by Montalà, Ricard, Font, Bernat, Suárez, Pol +3 · 2 citations
    #FOS: Computer and information sciences #FOS: Physical sciences #Fluid Dynamics (physics.flu-dyn) #Machine Learning (cs.LG)
  4. Can Explicit Subgrid Models Enhance Implicit LES Simulations? A GPU-Oriented High-Order-Solver Perspective
    2025/12/04 by Rubio, Gonzalo, Ntoukas, Gerasimos, Chávez-Módena, Miguel +5 · 1 citation
    #FOS: Mathematics #FOS: Physical sciences #Fluid Dynamics (physics.flu-dyn) #Numerical Analysis (math.NA)
  5. Atmospheric boundary layer over urban roughness: validation of large-eddy simulation
    2025/02/19 by Ming Teng, Teng, Ming, Ernest Mestres +8 · 1 citation
    Earth and Planetary Sciences · Environmental Science · #Aeolian processes and effects #FOS: Physical sciences #Fluid Dynamics (physics.flu-dyn) #Urban Heat Island Mitigation #Wind and Air Flow Studies