A directional GNN combined with constrained PPO jointly improves flow-field reconstruction accuracy and sensor layout selection in realistic fluid dynamics settings.
We use a cosine annealing learning rate with a starting learning rate at1×10 −4 to an end learning rate at1×10 −5
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Flow Field Reconstruction with Sensor Placement Policy Learning
A directional GNN combined with constrained PPO jointly improves flow-field reconstruction accuracy and sensor layout selection in realistic fluid dynamics settings.