TCF3DBothEnv

class fluidgym.envs.tcf.TCF3DBothEnv(resolution_y: int, resolution_x_z: int, L: float, D: float, actor_size: int, reynolds_number_wall: float, adaptive_cfl: float, step_length: float, episode_length: int, local_obs_window: int, local_reward_weight: float, use_marl: bool, C_smag: float = 0.0, use_van_driest: bool = False, init_with_noise: bool = True, dtype: dtype = torch.float32, cuda_device: device | None = None, debug: bool = False, load_initial_domain: bool = True, load_domain_statistics: bool = True, randomize_initial_state: bool = True, enable_actions: bool = True, differentiable: bool = False)[source]

Bases: TCF3DBottomEnv

Environment for turbulent channel flow control with both walls actuated.

The first half of the agents control the bottom wall, while the second half control the top wall.

References

[1] T. R. Bewley, P. Moin, and R. Temam, “DNS-based predictive control of turbulence: an optimal benchmark for feedback algorithms,” J. Fluid Mech., vol. 447, pp. 179-225, Nov. 2001, doi: 10.1017/S0022112001005821.

property n_agents: int: The number of agents in the environment.

property tau_ref: float: Reference overall wall shear stress for normalization.