Browsing Department of Computational and Data Sciences (CDS) by Subject "Anisotropic Permeability"
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Structure-Preserving Physics-Informed Neural Networks for Anisotropic Porous Media with Pressure Dependent Viscosity
Modeling flow through porous media with realistic physical constraints remains a longstanding challenge in subsurface engineering. Anisotropy in permeability, pressure-dependent viscosity, and non-negativity requirements ...

