Weak form theory-guided neural network (TgNN-wf) for deep learning of subsurface single- and two-phase flow
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Publication:2131089
DOI10.1016/j.jcp.2021.110318OpenAlexW3084119156MaRDI QIDQ2131089
Publication date: 25 April 2022
Published in: Journal of Computational Physics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2009.04543
Artificial intelligence (68Txx) Numerical methods for partial differential equations, initial value and time-dependent initial-boundary value problems (65Mxx) Miscellaneous topics in partial differential equations (35Rxx)
Related Items (2)
Surrogate and inverse modeling for two-phase flow in porous media via theory-guided convolutional neural network ⋮ A connection element method: both a new computational method and a physical data-driven framework -- take subsurface two-phase flow as an example
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