SIGNALAI·May 26, 2026, 4:00 AMSignal0Short term

WINO: A Weak-Form Physics Informed Neural Operator for Hyperelasticity on Variable Domains

Source: arXiv cs.LG

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WINO: A Weak-Form Physics Informed Neural Operator for Hyperelasticity on Variable Domains

arXiv:2605.24651v1 Announce Type: cross Abstract: We propose a Weak-form Physics-Informed Neural Operator (WINO), a data-free framework that combines the efficiency of neural operators with the geometric flexibility of the $\varphi$-finite element method ($\varphi$-FEM). $\varphi$-FEM is an unfitted method that accommodates geometric variations without body-fitted meshes, where the domain geometry is represented by the level-set function $\varphi$. To impose the boundary conditions, Dirichlet problems adopt the $\varphi$-FEM lifting so only the homogeneous displacement contribution is learned,

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