A physics-informed neural network trained only on PDE residuals, with each time window initialized from a steady-state solution, reproduces single-phase pipe flow and enables model predictive control without labeled data.
IEEE Transactions on Neural Networks and Learning Systems 33, 2615–2629
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Physics-Informed Neural Networks for Control of Single-Phase Flow Systems Governed by Partial Differential Equations
A physics-informed neural network trained only on PDE residuals, with each time window initialized from a steady-state solution, reproduces single-phase pipe flow and enables model predictive control without labeled data.