Model-free data-driven simulation of inelastic materials using structured data sets, tangent space information and transition rules

Finite element solver for data-driven finite strain elasticity

(2021) Auriane Platzer et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

Using neural networks to represent von Mises plasticity with isotropic hardening

(2020) Annan Zhang et al.   INTERNATIONAL JOURNAL OF PLASTICITY

Model-free data-driven computational mechanics enhanced by tensor voting

(2020) Robert Eggersmann et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

Data‐driven solvers for strongly nonlinear material response

(2020) Armin Galetzka et al.   INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING

Data-Driven multiscale modeling in mechanics

(2020) K. Karapiperis et al.   JOURNAL OF THE MECHANICS AND PHYSICS OF SOLIDS

Model-free data-driven methods in mechanics: material data identification and solvers

(2019) Laurent Stainier et al.   COMPUTATIONAL MECHANICS

Model-Free Data-Driven inelasticity

(2019) R. Eggersmann et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

Deep learning predicts path-dependent plasticity

(2019) M. Mozaffar et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Data-Driven Problems in Elasticity

(2018) S. Conti et al.   ARCHIVE FOR RATIONAL MECHANICS AND ANALYSIS

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

(2018) Kun Wang et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

A data-driven approach to nonlinear elasticity

(2018) Lu Trong Khiem Nguyen et al.   COMPUTERS & STRUCTURES

Design of metalloproteins and novel protein folds using variational autoencoders

(2018) Joe G. Greener et al.   Scientific Reports

Machine Learning Models of Plastic Flow Based on Representation Theory

(2018) R. E. Jones et al.   CMES-COMPUTER MODELING IN ENGINEERING & SCIENCES

Using deep neural network with small dataset to predict material defects

(2018) Shuo Feng et al.   MATERIALS & DESIGN

Data-driven computing in dynamics

(2017) T. Kirchdoerfer et al.   INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING

A Manifold Learning Approach to Data-Driven Computational Elasticity and Inelasticity

(2016) Rubén Ibañez et al.   ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING

Data-driven computational mechanics

(2016) T. Kirchdoerfer et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

Neural networks as material models within a multiscale approach

(2009) Jörg F. Unger et al.   COMPUTERS & STRUCTURES

Laser-induced breakdown spectroscopy with artificial neural network processing for material identification

(2009) A. Koujelev et al.   PLANETARY AND SPACE SCIENCE