Inferring incompressible two-phase flow fields from the interface motion using physics-informed neural networks
In this work, physics-informed neural networks are applied to incompressible two-phase flow problems. We investigate the forward problem, where the governing equations are solved from initial and boundary conditions, as well as the inverse problem, where continuous velocity and pressure fields are i...
Main Authors: | Aaron B. Buhendwa, Stefan Adami, Nikolaus A. Adams |
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Format: | Article |
Language: | English |
Published: |
Elsevier
2021-06-01
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Series: | Machine Learning with Applications |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S2666827021000104 |
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