Enhanced physics‐informed neural networks for hyperelasticity
Sign Up to like & getrecommendations! Published in 2022 at "International Journal for Numerical Methods in Engineering"
DOI: 10.1002/nme.7176
Abstract: Physics‐informed neural networks have gained growing interest. Specifically, they are used to solve partial differential equations governing several physical phenomena. However, physics‐informed neural network models suffer from several issues and can fail to provide accurate… read more here.
Keywords: informed neural; neural networks; physics; loss ... See more keywords
A 3-field formulation for strongly transversely isotropic compressible finite hyperelasticity
Sign Up to like & getrecommendations! Published in 2017 at "Computer Methods in Applied Mechanics and Engineering"
DOI: 10.1016/j.cma.2016.10.032
Abstract: Abstract A Hu–Washizu type 3-field virtual work principle for strongly transversely isotropic compressible finite hyperelasticity is developed, implemented and verified. The independent variables are: the stretch, its energy conjugate uniaxial tension and the displacement. The… read more here.
Keywords: isotropic compressible; field; formulation; hyperelasticity ... See more keywords