K-PINN integrates Lattice-Boltzmann kinetics into a U-Net architecture to model droplet wettability on complex surfaces with L2 errors of 0.021-0.026, R² near 0.999, and mass conservation within 1.5% while enabling real-time inference.
Chai, Baochang Shi, B
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A centered coupling scheme for lattice Boltzmann methods solves Biot's poroelasticity model stably for strong coupling and captures discontinuous solutions in consolidation problems.
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Lattice-Boltzmann-Driven Physics-Informed Neural Networks for Droplet Wettability on Rough Surfaces
K-PINN integrates Lattice-Boltzmann kinetics into a U-Net architecture to model droplet wettability on complex surfaces with L2 errors of 0.021-0.026, R² near 0.999, and mass conservation within 1.5% while enabling real-time inference.
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A lattice Boltzmann method for Biot's consolidation model of linear poroelasticity
A centered coupling scheme for lattice Boltzmann methods solves Biot's poroelasticity model stably for strong coupling and captures discontinuous solutions in consolidation problems.