About the Project
HydroGym is a transparent, extensible & comprehensive platform for applying reinforcement learning to fluid dynamics flow control. With environments ranging from canonical benchmarks to turbulent flows, HydroGym provides a standardized Gymnasium-compatible interface for training RL agents on challenging CFD problems.
Diverse Environments
88 pre-configured environments across 6 CFD solvers. Flow environments are supported by multiple backends: Finite Element (Firedrake), Lattice Boltzmann (MAIA LBM), Finite Volume (MAIA FV), Spectral Element (NEK5000), and fully Differentiable solvers (JAX-Fluids)
Scalable Implementation
Highly optimized GPU & CPU backends for efficient RL deployment ranging from local workstations to exascale HPC systems
Research Ready
Includes checkpoints, observation strategies, and reward formulations managed by a complementary HuggingFace repository. Gymnasium-compatible API works with Stable-Baselines3, RLlib, and other RL libraries
Join researchers training flow-control agents on canonical benchmarks in minutes.
NACA 0012 AirfoilZero shot evaluation at Rec = 200,000. Drag reduction trained on channel flow of Reτ = 206, and evaluated on a large scale airfoil.
Fluidic PinballMulti-body wake interactions at Re = 30 - 150. Coordinated control of three cylinders demonstrates chaos suppression.
Turbulent Boundary LayerReinforcement learning agent performs net power savings with travelling wave control for Reτ = 200, 1550, and 2200
Cylinder2D & 3D flows at Re = 100 - 3,900. Drag reduction via rotation and jet actuation. Achieves more than 20% drag reduction.
Turbulent Channel Flow (Differentiable)Wall-shear stress reduction at Reτ = 180. Gradient-enhanced training with JAX for efficient optimization.
NACA 0012 AirfoilGust mitigation at Re = 100 - 50,000. Transverse gust encounters with load alleviation strategies.
Kolmogorov Flow (Differentiable)Extreme event mitigation in 2D turbulence. Control energy bursts and enhance mixing efficiency.
Open Cavity FlowShear layer stabilization at Re = 4,140 - 7,500. Acoustic feedback disruption through leading-edge control.