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Eighty years of the finite element method: Birth, evolution, and future
This document presents comprehensive historical accounts on the developments of finite
element methods (FEM) since 1941, with a specific emphasis on developments related to …
element methods (FEM) since 1941, with a specific emphasis on developments related to …
Discovering plasticity models without stress data
We propose an approach for data-driven automated discovery of material laws, which we
call EUCLID (Efficient Unsupervised Constitutive Law Identification and Discovery), and we …
call EUCLID (Efficient Unsupervised Constitutive Law Identification and Discovery), and we …
Development of interpretable, data-driven plasticity models with symbolic regression
In many applications, such as those which drive new material discovery, constitutive models
are sought that have three characteristics:(1) the ability to be derived in automatic fashion …
are sought that have three characteristics:(1) the ability to be derived in automatic fashion …
Integrated Finite Element Neural Network (I-FENN) for non-local continuum damage mechanics
We present a new Integrated Finite Element Neural Network framework (I-FENN), with the
objective to accelerate the numerical solution of nonlinear computational mechanics …
objective to accelerate the numerical solution of nonlinear computational mechanics …
[HTML][HTML] Automated identification of linear viscoelastic constitutive laws with EUCLID
We extend EUCLID, a computational strategy for automated material model discovery and
identification, to linear viscoelasticity. For this case, we perform a priori model selection by …
identification, to linear viscoelasticity. For this case, we perform a priori model selection by …
Derivation of heterogeneous material laws via data-driven principal component expansions
A new data-driven method that generalizes experimentally measured and/or computational
generated data sets under different loading paths to build three dimensional nonlinear …
generated data sets under different loading paths to build three dimensional nonlinear …
MAP123: A data-driven approach to use 1D data for 3D nonlinear elastic materials modeling
Solving three-dimensional boundary-value engineering problems numerically requires
material laws. However, it is difficult to build the material laws in three dimension, since the …
material laws. However, it is difficult to build the material laws in three dimension, since the …
[HTML][HTML] Machine learning based modeling of path-dependent materials for finite element analysis
Geological materials typically demonstrate a nonlinear and path-dependent behavior.
Recently, data-driven techniques have emerged as a promising alternative to the traditional …
Recently, data-driven techniques have emerged as a promising alternative to the traditional …
Structural-Genome-Driven computing for composite structures
The aim of this work is to propose a new approach, named Structural-Genome-Driven (SGD)
computing, for composite structures, where the structural-genome database is collected …
computing, for composite structures, where the structural-genome database is collected …
Data-oriented constitutive modeling of plasticity in metals
Constitutive models for plastic deformation of metals are typically based on flow rules
determining the transition from elastic to plastic response of a material as function of the …
determining the transition from elastic to plastic response of a material as function of the …