Deep learning of interfacial curvature: a symmetry-preserving approach for the volume of fluid method

DOI10.1016/j.jcp.2023.112110arXiv2206.06041OpenAlexW4362608082MaRDI QIDQ6158093

Philip L.-F. Liu, Asim Önder

Publication date: 31 May 2023

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

Full work available at URL: https://arxiv.org/abs/2206.06041

zbMATH Keywords

machine learningtwo-phase flowssurface-tension modelingVOF-PLIC method

Mathematics Subject Classification ID

Basic methods in fluid mechanics (76Mxx) Multiphase and multicomponent flows (76Txx) Incompressible viscous fluids (76Dxx)

Cites Work

• Unnamed Item
• On the properties and limitations of the height function method in two-dimensional Cartesian geometry
• A mesh-decoupled height function method for computing interface curvature
• An accurate adaptive solver for surface-tension-driven interfacial flows
• A continuum method for modeling surface tension
• Reconstructing volume tracking
• A second order coupled level set and volume-of-fluid method for computing growth and collapse of vapor bubbles.
• Second-order accurate volume-of-fluid algorithms for tracking material interfaces
• Consistent and symmetry preserving data-driven interface reconstruction for the level-set method
• Accurate and efficient surface reconstruction from volume fraction data on general meshes
• Validation of volume-of-fluid OpenFOAM{\circledR} isoAdvector solvers using single bubble benchmarks
• NPLIC: a machine learning approach to piecewise linear interface construction
• Computing interface curvature from volume fractions: a machine learning approach
• On the combined effects of surface tension force calculation and interface advection on spurious currents within volume of fluid and level set frameworks
• Interface reconstruction with least-squares fit and split advection in three-dimensional Cartesian geometry
• A hybrid inference system for improved curvature estimation in the level-set method using machine learning
• Quantitative benchmark computations of two-dimensional bubble dynamics
• Motion of two superposed viscous fluids
• Neural Networks and Deep Learning
• Numerical Models of Surface Tension
• Interface reconstruction with least-square fit and split Eulerian-Lagrangian advection
• A Deep Learning Approach for the Computation of Curvature in the Level-Set Method
• A wave generation toolbox for the open‐source CFD library: OpenFoam®

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