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Found 3 papers, 1 papers with code
Uncertainty Quantification for Transport in Porous media using Parameterized Physics Informed neural Networks
We demonstrate the approach with the immiscible two phase flow displacement (Buckley-Leverett problem) in heterogeneous porous medium.
Machine Learning in Heterogeneous Porous Materials
The "Workshop on Machine learning in heterogeneous porous materials" brought together international scientific communities of applied mathematics, porous media, and material sciences with experts in the areas of heterogeneous materials, machine learning (ML) and applied mathematics to identify how ML can advance materials research.
Physics Informed Deep Learning for Transport in Porous Media. Buckley Leverett Problem
From a very limited dataset, the model learns the parameters of the governing equation and is able to provide an accurate physical solution, both in terms of shock and rarefaction.
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