Solution and Parameter Identification of a Fixed-Bed Reactor Model for Catalytic CO<sub>2</sub> Methanation Using Physics-Informed Neural Networks
In this study, we develop physics-informed neural networks (PINNs) to solve an isothermal fixed-bed (IFB) model for catalytic CO<sub>2</sub> methanation. The PINN includes a feed-forward artificial neural network (FF-ANN) and physics-informed constraints, such as governing equations, bou...
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| Auteurs principaux: | , |
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| Format: | article |
| Langue: | EN |
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MDPI AG
2021
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| Accès en ligne: | https://doaj.org/article/8254ad25d9df4ed28af83cf6d35c0818 |
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