A non-overlapping Schwarz hybrid FE-NO framework with Point-DeepONet enables efficient, geometry-flexible simulations of solid mechanics by reducing interface iterations and enforcing mechanical consistency through analytical strain-stress derivation.
Title resolution pending
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
A one-step flow matching model using transformer in VAE latent space with non-Gaussian source and auxiliary networks generates accurate high-resolution path-dependent stress fields, achieving 6-7x CPU and ~100x GPU speedup over FEM.
citing papers explorer
-
A Non-Overlapping Schwarz Hybrid Finite Element-Neural Operator Framework for Solid Mechanics on Irregular Domains
A non-overlapping Schwarz hybrid FE-NO framework with Point-DeepONet enables efficient, geometry-flexible simulations of solid mechanics by reducing interface iterations and enforcing mechanical consistency through analytical strain-stress derivation.