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Material modeling for parametric, anisotropic finite strain hyperelasticity based on machine learning with application in optimization of metamaterials
Author(s) -
Fernández Mauricio,
Fritzen Felix,
Weeger Oliver
Publication year - 2021
Publication title -
international journal for numerical methods in engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.421
H-Index - 168
eISSN - 1097-0207
pISSN - 0029-5981
DOI - 10.1002/nme.6869
Subject(s) - hyperelastic material , metamaterial , parametric statistics , isotropy , constitutive equation , computer science , lattice (music) , anisotropy , parametric model , deformation (meteorology) , topology (electrical circuits) , nonlinear system , finite element method , artificial intelligence , algorithm , materials science , structural engineering , physics , mathematics , optics , engineering , acoustics , composite material , statistics , combinatorics , quantum mechanics