A machine learning strategy for computing interface curvature in front-tracking methods

DOI10.1016/j.jcp.2021.110860OpenAlexW3215773989MaRDI QIDQ2134723

Cassio M. Oishi, Hugo L. França

Publication date: 3 May 2022

Published in: Journal of Computational Physics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jcp.2021.110860

zbMATH Keywords

curvaturefront-trackingmachine learningfree surface flowsmarker-and-cell

Mathematics Subject Classification ID

Basic methods in fluid mechanics (76Mxx) Multiphase and multicomponent flows (76Txx) Fluid mechanics (76-XX)

Related Items (2)

Error-correcting neural networks for two-dimensional curvature computation in the level-set method ⋮ Machine learning algorithms for three-dimensional mean-curvature computation in the level-set method

Uses Software

• FronTier

Cites Work

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• Numerical Models of Surface Tension
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• A Two-Dimensional Second Order Conservative Front-Tracking Method with an Original Marker Advection Approach Based on Jump Relations
• Normal and oblique drop impact of yield stress fluids with thixotropic effects
• An Effective Implementation of Surface Tension Using the Marker and Cell Method for Axisymmetric and Planar Flows
• A front-tracking method for the computations of multiphase flow.

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