Self-attention mechanisms are used to build mesh-preserving neural surrogates that approximate PFEM dynamics for free-surface flows, delivering accurate transient predictions and improved scalability on 2D and 3D benchmarks.
Com- puter Methods in Applied Mechanics and Engineering449, 118476 (2026)
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
A GNN surrogate with geometry-conditioned anisotropic message passing and autoregressive residual training produces competitive forecasts of gas saturation and liquid density for CO2 storage on the SPE11A benchmark with moderate cumulative errors over long horizons.
citing papers explorer
-
Attention mechanism for scalable mesh-based neural surrogates of free-surface fluids
Self-attention mechanisms are used to build mesh-preserving neural surrogates that approximate PFEM dynamics for free-surface flows, delivering accurate transient predictions and improved scalability on 2D and 3D benchmarks.