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.
arXiv preprint arXiv:2412.18362 , year=
2 Pith papers cite this work. Polarity classification is still indexing.
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EqGINO adds a spectral isotropy prior to FNOs to guarantee discrete equivariance and enable generalization to continuous SE(3) transformations on 3D PDEs with limited training data.
citing papers explorer
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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.
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EqGINO: Equivariant Geometry-Informed Fourier Neural Operators for 3D PDEs
EqGINO adds a spectral isotropy prior to FNOs to guarantee discrete equivariance and enable generalization to continuous SE(3) transformations on 3D PDEs with limited training data.