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Found 4 papers, 1 papers with code
Geometry-aware framework for deep energy method: an application to structural mechanics with hyperelastic materials
In this work, we introduce a novel physics-informed framework named the Geometry-Aware Deep Energy Method (GADEM) for solving structural mechanics problems on different geometries.
Fixed-budget online adaptive learning for physics-informed neural networks. Towards parameterized problem inference
We show that FBOAL is able to identify the high-gradient locations and even give better predictions for some physical fields than the classical PINNs with collocation points sampled on a pre-adapted finite element mesh built thanks to numerical expert knowledge.
Continuous Methods : Adaptively intrusive reduced order model closure
Reduced order modeling methods are often used as a mean to reduce simulation costs in industrial applications.
Physics-informed neural networks for non-Newtonian fluid thermo-mechanical problems: an application to rubber calendering process
We also investigate the capability of PINNs to identify unknown physical parameters from the measurements captured by sensors.
