A review of artificial neural networks in the constitutive modeling of composite materials

Learning constitutive relations using symmetric positive definite neural networks

(2021) Kailai Xu et al.   JOURNAL OF COMPUTATIONAL PHYSICS

A micromechanics-based artificial neural networks model for elastic properties of short fiber composites

(2021) N. Mentges et al.   COMPOSITES PART B-ENGINEERING

Metamaterials with a controllable thermal-mechanical stability: Mechanical designs, theoretical predictions and experimental demonstrations

(2021) Huabin Yu et al.   COMPOSITES SCIENCE AND TECHNOLOGY

Learning composite constitutive laws via coupling Abaqus and deep neural network

(2021) Fei Tao et al.   COMPOSITE STRUCTURES

Multiscale modeling of the effective thermal conductivity of 2D woven composites by mechanics of structure genome and neural networks

(2021) Xin Liu et al.   INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER

Physics-Informed Artificial Neural Network Approach for Axial Compression Buckling Analysis of Thin-Walled Cylinder

(2020) Fei Tao et al.   AIAA JOURNAL

Generative Deep Neural Networks for Inverse Materials Design Using Backpropagation and Active Learning

(2020) Chun‐Teh Chen et al.   Advanced Science

Data-Driven Finite Elasticity

(2020) S. Conti et al.   ARCHIVE FOR RATIONAL MECHANICS AND ANALYSIS

Experimental and analytical investigation of the bending behaviour of 3D-printed bio-based sandwich structures composites with auxetic core under cyclic fatigue tests

(2020) Khawla Essassi et al.   COMPOSITES PART A-APPLIED SCIENCE AND MANUFACTURING

Mechanical response of negative stiffness truncated-conical shell systems: experiment, numerical simulation and empirical model

(2020) Xiaojun Tan et al.   COMPOSITES PART B-ENGINEERING

Deep material network with cohesive layers: Multi-stage training and interfacial failure analysis

(2020) Zeliang Liu   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

FEA-Net: A physics-guided data-driven model for efficient mechanical response prediction

(2020) Houpu Yao 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

Exploring elastoplastic constitutive law of microstructured materials through Artificial Neural Network (ANN) — a mechanistic-based data-driven approach

(2020) Hang Yang et al.   JOURNAL OF APPLIED MECHANICS-TRANSACTIONS OF THE ASME

Learning Nonlinear Constitutive Laws Using Neural Network Models Based on Indirectly Measurable Data

(2020) Xin Liu et al.   JOURNAL OF APPLIED MECHANICS-TRANSACTIONS OF THE ASME

Prediction of composite microstructure stress-strain curves using convolutional neural networks

(2020) Charles Yang et al.   MATERIALS & DESIGN

Theory-guided machine learning for damage characterization of composites

(2020) Navid Zobeiry et al.   COMPOSITE STRUCTURES

An efficient multiscale surrogate modelling framework for composite materials considering progressive damage based on artificial neural networks

(2020) Shibo Yan et al.   COMPOSITES PART B-ENGINEERING

An intelligent nonlinear meta element for elastoplastic continua: deep learning using a new Time-distributed Residual U-Net architecture

(2020) Arnd Koeppe et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

Micromechanics-based surrogate models for the response of composites: A critical comparison between a classical mesoscale constitutive model, hyper-reduction and neural networks

(2020) I.B.C.M. Rocha et al.   EUROPEAN JOURNAL OF MECHANICS A-SOLIDS

A neural network constitutive model for hyperelasticity based on molecular dynamics simulations

(2020) Ingyun Chung et al.   INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING

A multi-fidelity competitive sampling method for surrogate-based stacking sequence optimization of composite shells with multiple cutouts

(2020) Kuo Tian et al.   INTERNATIONAL JOURNAL OF SOLIDS AND STRUCTURES

Neural network constitutive model for crystal structures

(2020) Sunyoung Im et al.   COMPUTATIONAL MECHANICS

A recurrent neural network-accelerated multi-scale model for elasto-plastic heterogeneous materials subjected to random cyclic and non-proportional loading paths

(2020) Ling Wu et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

Physics-informed multi-LSTM networks for metamodeling of nonlinear structures

(2020) Ruiyang Zhang et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

Topology optimization of 2D structures with nonlinearities using deep learning

(2020) Diab W. Abueidda et al.   COMPUTERS & STRUCTURES

Learning constitutive relations from indirect observations using deep neural networks

(2020) Daniel Z. Huang et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Deep convolutional neural networks in structural dynamics under consideration of viscoplastic material behaviour

(2020) Marcus Stoffel et al.   MECHANICS RESEARCH COMMUNICATIONS

Ultra-low density architectured metamaterial with superior mechanical properties and energy absorption capability

(2020) Qingsong Wang et al.   COMPOSITES PART B-ENGINEERING

A machine learning framework for predicting the shear strength of carbon nanotube-polymer interfaces based on molecular dynamics simulation data

(2020) Aowabin Rahman et al.   COMPOSITES SCIENCE AND TECHNOLOGY

A Newton solver for micromorphic computational homogenization enabling multiscale buckling analysis of pattern-transforming metamaterials

(2020) S.E.H.M. van Bree et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

A systematic review of convolutional neural network-based structural condition assessment techniques

(2020) Sandeep Sony et al.   ENGINEERING STRUCTURES

A wavelet-based learning approach assisted multiscale analysis for estimating the effective thermal conductivities of particulate composites

(2020) Hao Dong et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

Thermodynamics-based Artificial Neural Networks for constitutive modeling

(2020) Filippo Masi et al.   JOURNAL OF THE MECHANICS AND PHYSICS OF SOLIDS

Neural network based constitutive modeling of nonlinear viscoplastic structural response

(2019) Marcus Stoffel et al.   MECHANICS RESEARCH COMMUNICATIONS

Application of artificial neural networks to map the mechanical response of a thermoplastic elastomer

(2019) Alejandro E. Rodríguez-Sánchez et al.   Materials Research Express

Machine-learning based temperature- and rate-dependent plasticity model: Application to analysis of fracture experiments on DP steel

(2019) Xueyang Li et al.   INTERNATIONAL JOURNAL OF PLASTICITY

A unified framework for the multi-scale computational homogenisation of 3D-textile composites

(2019) Z. Ullah et al.   COMPOSITES PART B-ENGINEERING

Transfer learning of deep material network for seamless structure–property predictions

(2019) Zeliang Liu et al.   COMPUTATIONAL MECHANICS

Derivation of heterogeneous material laws via data-driven principal component expansions

(2019) Hang Yang et al.   COMPUTATIONAL MECHANICS

Clustering discretization methods for generation of material performance databases in machine learning and design optimization

(2019) Hengyang Li et al.   COMPUTATIONAL MECHANICS

A cooperative game for automated learning of elasto-plasticity knowledge graphs and models with AI-guided experimentation

(2019) Kun Wang et al.   COMPUTATIONAL MECHANICS

Model-Free Data-Driven inelasticity

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

Stress Field Prediction in Cantilevered Structures Using Convolutional Neural Networks

(2019) Zhenguo Nie et al.   JOURNAL OF COMPUTING AND INFORMATION SCIENCE IN ENGINEERING

Multi-Fidelity Physics-Constrained Neural Network and Its Application in Materials Modeling

(2019) Dehao Liu et al.   JOURNAL OF MECHANICAL DESIGN

Exploring the 3D architectures of deep material network in data-driven multiscale mechanics

(2019) Zeliang Liu et al.   JOURNAL OF THE MECHANICS AND PHYSICS OF SOLIDS

Multiscale analysis of woven composite structures in MSC.Nastran

(2019) Xin Liu et al.   ADVANCES IN ENGINEERING SOFTWARE

Additive manufacturing of polymer composites: Processing and modeling approaches

(2019) A. El Moumen et al.   COMPOSITES PART B-ENGINEERING

A unified approach for thermoelastic constitutive modeling of composite structures

(2019) Xin Liu et al.   COMPOSITES PART B-ENGINEERING

Predicting the effective thermal conductivity of composites from cross sections images using deep learning methods

(2019) Qingyuan Rong et al.   COMPOSITES SCIENCE AND TECHNOLOGY

Bayesian inference of non-linear multiscale model parameters accelerated by a Deep Neural Network

(2019) Ling Wu et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

A deep energy method for finite deformation hyperelasticity

(2019) Vien Minh Nguyen-Thanh et al.   EUROPEAN JOURNAL OF MECHANICS A-SOLIDS

A hybrid approach to simulate the homogenized irreversible elastic–plastic deformations and damage of foams by neural networks

(2019) Christoph Settgast et al.   INTERNATIONAL JOURNAL OF PLASTICITY

A Convolutional Neural Network for Impact Detection and Characterization of Complex Composite Structures

(2019) Iuliana Tabian et al.   SENSORS

Mechanical design and multifunctional applications of chiral mechanical metamaterials: A review

(2019) Wenwang Wu et al.   MATERIALS & DESIGN

Initial failure strength prediction of woven composites using a new yarn failure criterion constructed by deep learning

(2019) Xin Liu et al.   COMPOSITE STRUCTURES

Constitutive modeling for time- and temperature-dependent behavior of composites

(2019) Orzuri Rique et al.   COMPOSITES PART B-ENGINEERING

Compressive behavior of stretched and composite microlattice metamaterial for energy absorption applications

(2019) Mahmoud M. Osman et al.   COMPOSITES PART B-ENGINEERING

MAP123: A data-driven approach to use 1D data for 3D nonlinear elastic materials modeling

(2019) Shan Tang et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

Accelerating multiscale finite element simulations of history-dependent materials using a recurrent neural network

(2019) F. Ghavamian et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

An adaptive domain-based POD/ECM hyper-reduced modeling framework without offline training

(2019) I.B.C.M. Rocha et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

A composite neural network that learns from multi-fidelity data: Application to function approximation and inverse PDE problems

(2019) Xuhui Meng et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Deep learning predicts path-dependent plasticity

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

Neural network assisted multiscale analysis for the elastic properties prediction of 3D braided composites under uncertainty

(2018) Georgios Balokas et al.   COMPOSITE STRUCTURES

The influence of laminate stacking sequence on ballistic limit using a combined Experimental/FEM/Artificial Neural Networks (ANN) methodology

(2018) J.A. Artero-Guerrero et al.   COMPOSITE STRUCTURES

Multiscale surrogate modelling of the elastic response of thick composite structures with embedded defects and features

(2018) Bassam El Said et al.   COMPOSITE STRUCTURES

First-ply failure prediction of glass/epoxy composite pipes using an artificial neural network model

(2018) J.Y. Ang et al.   COMPOSITE STRUCTURES

Direct numerical simulation of 3D woven textile composites subjected to tensile loading: An experimentally validated multiscale approach

(2018) Deepak K. Patel et al.   COMPOSITES PART B-ENGINEERING

Deep learning approaches for mining structure-property linkages in high contrast composites from simulation datasets

(2018) Zijiang Yang et al.   COMPUTATIONAL MATERIALS SCIENCE

Data-driven multi-scale multi-physics models to derive process–structure–property relationships for additive manufacturing

(2018) Wentao Yan et al.   COMPUTATIONAL MECHANICS

Microstructural material database for self-consistent clustering analysis of elastoplastic strain softening materials

(2018) Zeliang Liu et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

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

Development of an ABAQUS plugin tool for periodic RVE homogenisation

(2018) Sadik L. Omairey et al.   ENGINEERING WITH COMPUTERS

Two-stage data-driven homogenization for nonlinear solids using a reduced order model

(2018) Felix Fritzen et al.   EUROPEAN JOURNAL OF MECHANICS A-SOLIDS

A general multiscale framework for the emergent effective elastodynamics of metamaterials

(2018) A. Sridhar et al.   JOURNAL OF THE MECHANICS AND PHYSICS OF SOLIDS

Convolutional neural networks for automated damage recognition and damage type identification

(2018) Ceena Modarres et al.   Structural Control & Health Monitoring

Artificial neural networks and intelligent finite elements in non-linear structural mechanics

(2018) Marcus Stoffel et al.   THIN-WALLED STRUCTURES

Experimental assessment of the mechanical behaviour of 3D woven composite T-joints

(2018) Shibo Yan et al.   COMPOSITES PART B-ENGINEERING

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

(2018) Zeliang Liu et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

Predicting the effective thermal conductivities of composite materials and porous media by machine learning methods

(2018) Han Wei et al.   INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER

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

(2018) Xiaoxin Lu et al.   COMPUTATIONAL MECHANICS

Hybrid constitutive modeling: data-driven learning of corrections to plasticity models

(2018) Rubén Ibáñez et al.   International Journal of Material Forming

Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations

(2018) M. Raissi et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Smart finite elements: A novel machine learning application

(2018) German Capuano et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

Structural vibration-based classification and prediction of delamination in smart composite laminates using deep learning neural network

(2018) Asif Khan et al.   COMPOSITES PART B-ENGINEERING

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

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

Constitutive modeling of damageable brittle and quasi-brittle materials

(2017) Liang Zhang et al.   INTERNATIONAL JOURNAL OF SOLIDS AND STRUCTURES

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

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

Computation of the effective mechanical properties including nonclassical moduli of 2.5D and 3D interlocks by micromechanical approaches

(2016) Y. Rahali et al.   COMPOSITES PART B-ENGINEERING

Characterization of thermoelectric properties of multifunctional multiscale composites and fiber-reinforced composites for thermal energy harvesting

(2016) Dae Han Sung et al.   COMPOSITES PART B-ENGINEERING

Comparison of modelling using regression techniques and an artificial neural network for obtaining the static modulus of elasticity of Pinus radiata D. Don. timber by ultrasound

(2016) Alberto García-Iruela et al.   COMPOSITES PART B-ENGINEERING

Data-driven computational mechanics

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

Self-consistent clustering analysis: An efficient multi-scale scheme for inelastic heterogeneous materials

(2016) Zeliang Liu et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

Optimization of geometrical parameters in a specific composite lattice structure using neural networks and ABC algorithm

(2016) M. Sadegh Yazdi et al.   Journal of Mechanical Science and Technology

A unified theory for constitutive modeling of composites

(2016) Wenbin Yu   Journal of Mechanics of Materials and Structures

Multiscale metallic metamaterials

(2016) Xiaoyu Zheng et al.   NATURE MATERIALS

Minimum-weight design for three dimensional woven composite stiffened panels using neural networks and genetic algorithms

(2015) Xinwei Fu et al.   COMPOSITE STRUCTURES

Damage classification in carbon fibre composites using acoustic emission: A comparison of three techniques

(2015) John P. McCrory et al.   COMPOSITES PART B-ENGINEERING

Failure analysis of fiber-reinforced composite laminates subjected to biaxial loads

(2015) Hsuan-Teh Hu et al.   COMPOSITES PART B-ENGINEERING

Computational homogenization of nonlinear elastic materials using neural networks

(2015) B. A. Le et al.   INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING

Progressive damage and failure response of hybrid 3D textile composites subjected to flexural loading, part I: Experimental studies

(2015) Dianyun Zhang et al.   INTERNATIONAL JOURNAL OF SOLIDS AND STRUCTURES

Progressive damage and failure response of hybrid 3D textile composites subjected to flexural loading, part II: Mechanics based multiscale computational modeling of progressive damage and failure

(2015) Dianyun Zhang et al.   INTERNATIONAL JOURNAL OF SOLIDS AND STRUCTURES

Prediction of impact damage tolerance of drop impacted WGFRP composite by artificial neural network using acoustic emission parameters

(2014) P. Ramasamy et al.   COMPOSITES PART B-ENGINEERING

Modeling techniques for predicting the mechanical properties of woven-fabric textile composites: a Review

(2013) A. Dixit et al.   MECHANICS OF COMPOSITE MATERIALS

Multiobjective optimization of composite cylindrical shells for strength and frequency using genetic algorithm and neural networks

(2013) Karim Garmsiri et al.   SCIENCE AND ENGINEERING OF COMPOSITE MATERIALS

Optimization of composite stiffened panels under mechanical and hygrothermal loads using neural networks and genetic algorithms

(2012) L. Marín et al.   COMPOSITE STRUCTURES

Triaxial test results for fibre-reinforced composites: The Second World-Wide Failure Exercise benchmark data

(2012) MJ Hinton et al.   JOURNAL OF COMPOSITE MATERIALS

Multiscale methodology for bone remodelling simulation using coupled finite element and neural network computation

(2010) Ridha Hambli et al.   Biomechanics and Modeling in Mechanobiology

Artificial Neural Networks in numerical modelling of composites

(2009) M. Lefik 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

Multi-scale computational homogenization: Trends and challenges

(2009) M.G.D. Geers et al.   JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS

Hybrid computational strategy based on ANN and GAPS: Application for identification of a non-linear model of composite material

(2008) David Hicham Bassir et al.   COMPOSITE STRUCTURES

Self-learning simulation method for inverse nonlinear modeling of cyclic behavior of connections

(2008) Gun Jin Yun et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

Variational asymptotic homogenization of heterogeneous electromagnetoelastic materials

(2008) Tian Tang et al.   INTERNATIONAL JOURNAL OF ENGINEERING SCIENCE

Variational asymptotic micromechanics modeling of heterogeneous piezoelectric materials

(2008) Tian Tang et al.   MECHANICS OF MATERIALS

Crushing behavior of laterally compressed composite elliptical tubes: Experiments and predictions using artificial neural networks

(2007) El-Sadig Mahdi et al.   COMPOSITE STRUCTURES

A new neural network-based model for hysteretic behavior of materials

(2007) Gun Jin Yun et al.   INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING