Geometric deep learning for computational mechanics. I: Anisotropic hyperelasticity (Q2021107)

scientific article

Language	Label	Description	Also known as
English	Geometric deep learning for computational mechanics. I: Anisotropic hyperelasticity	scientific article

Statements

instance of

scholarly article

0 references

title

Geometric deep learning for computational mechanics. I: Anisotropic hyperelasticity (English)

0 references

0 references

0 references

0 references

Computer Methods in Applied Mechanics and Engineering

0 references

publication date

26 April 2021

0 references

full work available at URL

https://arxiv.org/abs/2001.04292

0 references

zbMATH Keywords

geometric machine learning

0 references

graph

0 references

polycrystals

0 references

microstructures

0 references

anisotropic energy functional

0 references

phase-field fracture

0 references

describes a project that uses

0 references

0 references

0 references

0 references

0 references

0 references

0 references

0 references

0 references

0 references

MaRDI publication profile

0 references

cites work

A Continuum Model for Void Nucleation by Inclusion Debonding

0 references

Modification of the Gurson model for shear failure

0 references

Cam-Clay plasticity. I: Implicit integration of elasto-plastic constitutive relations

0 references

A computational procedure for rate-independent crystal plasticity.

0 references

Computational thermomechanics of crystalline rock. I: A combined multi-phase-field/crystal plasticity approach for single crystal simulations

0 references

A multiscale overlapped coupling formulation for large-deformation strain localization

0 references

ILS-MPM: an implicit level-set-based material point method for frictional particulate contact mechanics of deformable particles

0 references

Data-driven computational mechanics

0 references

Model-free data-driven inelasticity

0 references

A physics-constrained data-driven approach based on locally convex reconstruction for noisy database

0 references

Q5243583

0 references

A framework for data-driven analysis of materials under uncertainty: countering the curse of dimensionality

0 references

Data-Driven Self-consistent Clustering Analysis of Heterogeneous Materials with Crystal Plasticity

0 references

Meta-modeling game for deriving theory-consistent, microstructure-based traction-separation laws via deep reinforcement learning

0 references

An updated Lagrangian LBM-DEM-FEM coupling model for dual-permeability fissured porous media with embedded discontinuities

0 references

Estimation of Separating Planes between Touching 3D Objects Using Power Watershed

0 references

Large-scale 3D random polycrystals for the finite element method: generation, meshing and remeshing

0 references

Q3093326

0 references

A multiscale multi-permeability poroplasticity model linked by recursive homogenizations and deep learning

0 references

Q2934059

0 references

Artificial neural networks in numerical modelling of composites

0 references

A deep material network for multiscale topology learning and accelerated nonlinear modeling of heterogeneous materials

0 references

A data-driven computational homogenization method based on neural networks for the nonlinear anisotropic electrical response of graphene/polymer nanocomposites

0 references

Learning constitutive relations from indirect observations using deep neural networks

0 references

A new constitutive framework for arterial wall mechanics and a comparative study of material models

0 references

Computational homogenization of nonlinear elastic materials using neural networks

0 references

Machine learning materials physics: integrable deep neural networks enable scale bridging by learning free energy functions

0 references

Machine learning materials physics: surrogate optimization and multi-fidelity algorithms predict precipitate morphology in an alternative to phase field dynamics

0 references

Neural network with unbounded activation functions is universal approximator

0 references

\(\mathrm{SO}(3)\)-invariance of informed-graph-based deep neural network for anisotropic elastoplastic materials

0 references

Plasticity

0 references

Quantitative measure of nonconvexity for black-box continuous functions

0 references

FFT-based solver for higher-order and multi-phase-field fracture models applied to strongly anisotropic brittle materials

0 references

Q5843952

0 references

Computational Statistics

0 references

Metrics for 3D rotations: comparison and analysis

0 references

Q5642104

0 references

Cam-Clay plasticity. IV: Implicit integration of anisotropic bounding surface model with nonlinear hyperelasticity and ellipsoidal loading function

0 references

Q3093216

0 references

Strain- and stress-based continuum damage models. I. Formulation

0 references

Efficient and accurate two-scale FE-FFT-based prediction of the effective material behavior of elasto-viscoplastic polycrystals

0 references

The variational approach to fracture

0 references

A phase-field description of dynamic brittle fracture

0 references

A phase field model for rate-independent crack propagation: robust algorithmic implementation based on operator splits

0 references

Dynamic crack propagation based on loss of hyperbolicity and a new discontinuous enrichment

0 references

A comparative study on finite element methods for dynamic fracture

0 references

Q4040797

0 references

Spectral Theory and Analysis

0 references

Identifiers

zbMATH Open document ID

1506.74504

0 references

DOI

10.1016/j.cma.2020.113299

0 references

Mathematics Subject Classification ID

0 references

0 references

0 references

0 references

0 references

0 references

0 references

0 references

Sitelinks

Mathematics(1 entry)

mardi Publication:2021107