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Author

John Hecht

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Sep 2026

Physics-Informed Neural Network Surrogates for Chemical Processes Governed by Partial Differential Equations: From Static Simulation to Real-Time Applications

Two Physics-Informed Neural Network (PINN)-based surrogate frameworks tailored to distinct applications achieving speedups exceeding three orders of magnitude over a conventional numerical solver, with sub-percent mean absolute percentage errors and strong generalization to extrapolated inputs beyond their training dom...

Sepehr Aarabi Dahej, Anthony W. K. Quarshie, C. L. Swartz et al. · 0 citations

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