Weak form theory-guided neural network (TgNN-wf) for deep learning of subsurface single- and two-phase flow
Journal of Computational Physics(2021)
Abstract
•Weak form physics constraints are incorporated into a fully-connected neural network to predict future responses.•Domain decomposition reduces computational cost and captures local discontinuity.•Our model shows improved accuracy and robustness to noises compared to strong form theory-guided neural networks.
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Key words
Theory-guided neural network,Weak form,Lagrangian duality,Single-phase flow,Two-phase flow
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