Closure models for under-resolved PDEs can be trained on synthetic manufactured solutions, and the learned corrections generalize from forced to unforced equations.
Scientific multi-agent reinforcement learning for wall-models of turbulent flows
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Reinforcement Learning Closures for Underresolved Partial Differential Equations using Synthetic Data
Closure models for under-resolved PDEs can be trained on synthetic manufactured solutions, and the learned corrections generalize from forced to unforced equations.