  A data driven finite element method (DDFEM) that accounts for more than two
material state variables has been presented in this work. DDFEM framework is
motivated from (1,2) and can account for multiple state variables, viz.
stresses, strains, strain rates, failure stress, material degradation, and
anisotropy which has not been used before. DDFEM is implemented in the context
of linear elements of a nonlinear elastic solid. The presented framework can be
used for variety of applications by directly using experimental data. This has
been demonstrated by using the DDFEM framework to predict deformation,
degradation and failure in diverse applications including nanomaterials and
biomaterials for the first time. DDFEM capability of predicting unknown and
unstructured dataset has also been shown by using Delaunay triangulation
strategy for scattered data having no structure or order. The framework is able
to capture the strain rate dependent deformation, material anisotropy, material
degradation, and failure which has not been presented in the past. The
predicted results show a very good agreement between data set taken from
literature and DDFEM predictions without requiring to formulate complex
constitutive models and avoiding tedious material parameter identification.
