4.5 Review

A Review of the Application of Machine Learning and Data Mining Approaches in Continuum Materials Mechanics

Related references

Note: Only part of the references are listed.
Article Engineering, Multidisciplinary

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

Zeliang Liu et al.

COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING (2019)

Article Materials Science, Multidisciplinary

Learning to fail: Predicting fracture evolution in brittle material models using recurrent graph convolutional neural networks

Max Schwarzer et al.

COMPUTATIONAL MATERIALS SCIENCE (2019)

Article Materials Science, Multidisciplinary

General Multi-Fidelity Framework for Training Artificial Neural Networks With Computational Models

Roland Can Aydin et al.

FRONTIERS IN MATERIALS (2019)

Article Automation & Control Systems

Application of design of experiments for laser shock peening process optimization

Sergey Chupakhin et al.

INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY (2019)

Article Engineering, Manufacturing

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

Ruben Ibanez et al.

INTERNATIONAL JOURNAL OF MATERIAL FORMING (2019)

Review Computer Science, Interdisciplinary Applications

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

Ruben Ibanez et al.

ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING (2018)

Article Engineering, Multidisciplinary

Data-driven computing in dynamics

T. Kirchdoerfer et al.

INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING (2018)

Article Materials Science, Multidisciplinary

Material structure-property linkages using three-dimensional convolutional neural networks

Ahmet Cecen et al.

ACTA MATERIALIA (2018)

Article Materials Science, Multidisciplinary

CA method with machine learning for simulating the grain and pore growth of aluminum alloys

Yuanyuan Hu et al.

COMPUTATIONAL MATERIALS SCIENCE (2018)

Article Materials Science, Multidisciplinary

Predictive modeling of dynamic fracture growth in brittle materials with machine learning

Bryan A. Moore et al.

COMPUTATIONAL MATERIALS SCIENCE (2018)

Article Materials Science, Multidisciplinary

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

Zijiang Yang et al.

COMPUTATIONAL MATERIALS SCIENCE (2018)

Article Mathematics, Interdisciplinary Applications

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

Wentao Yan et al.

COMPUTATIONAL MECHANICS (2018)

Article Engineering, Mechanical

An online tool for predicting fatigue strength of steel alloys based on ensemble data mining

Ankit Agrawal et al.

INTERNATIONAL JOURNAL OF FATIGUE (2018)

Editorial Material Materials Science, Multidisciplinary

Data-Driven Materials Investigations: The Next Frontier in Understanding and Predicting Fatigue Behavior

Ashley D. Spear et al.

Article Nanoscience & Nanotechnology

Probabilistic design of a molybdenum-base alloy using a neural network

B. D. Conduit et al.

SCRIPTA MATERIALIA (2018)

Article Materials Science, Multidisciplinary

Data-driven reduced-order models for rank-ordering the high cycle fatigue performance of polycrystalline microstructures

Noah H. Paulson et al.

MATERIALS & DESIGN (2018)

Article Multidisciplinary Sciences

Deep reinforcement learning for de novo drug design

Mariya Popova et al.

SCIENCE ADVANCES (2018)

Article Materials Science, Multidisciplinary

Connections Between Topology and Macroscopic Mechanical Properties of Three-Dimensional Open-Pore Materials

Norbert Huber

FRONTIERS IN MATERIALS (2018)

Proceedings Paper Engineering, Manufacturing

Prediction of surface roughness in turning of Ti-6Al-4V using cutting parameters, forces and tool vibration

Neelesh Kumar Sahu et al.

INTERNATIONAL CONFERENCE ON RECENT ADVANCES IN MATERIALS & MANUFACTURING TECHNOLOGIES (2018)

Article Engineering, Chemical

Data science approaches for microstructure quantification and feature identification in porous membranes

Patrick Altschuh et al.

JOURNAL OF MEMBRANE SCIENCE (2017)

Article Engineering, Mechanical

Artificial neural network for correction of effects of plasticity in equibiaxial residual stress profiles measured by hole drilling

Sergey Chupakhin et al.

JOURNAL OF STRAIN ANALYSIS FOR ENGINEERING DESIGN (2017)

Article Multidisciplinary Sciences

Mastering the game of Go without human knowledge

David Silver et al.

NATURE (2017)

Article Chemistry, Analytical

Feed-Forward Neural Network Prediction of the Mechanical Properties of Sandcrete Materials

Panagiotis G. Asteris et al.

SENSORS (2017)

Article Materials Science, Multidisciplinary

Design of a nickel-base superalloy using a neural network

B. D. Conduit et al.

MATERIALS & DESIGN (2017)

Article Engineering, Multidisciplinary

Data Driven Computing with noisy material data sets

T. Kirchdoerfer et al.

COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING (2017)

Article Physics, Fluids & Plasmas

Inferring low-dimensional microstructure representations using convolutional neural networks

Nicholas Lubbers et al.

PHYSICAL REVIEW E (2017)

Article Materials Science, Multidisciplinary

Exploring the microstructure manifold: Image texture representations applied to ultrahigh carbon steel microstructures

Brian L. DeCost et al.

ACTA MATERIALIA (2017)

Article Materials Science, Multidisciplinary

Extracting knowledge from molecular mechanics simulations of grain boundaries using machine learning

Joshua A. Gomberg et al.

ACTA MATERIALIA (2017)

Article Engineering, Manufacturing

Context Aware Machine Learning Approaches for Modeling Elastic Localization in Three-Dimensional Composite Microstructures

Ruoqian Liu et al.

INTEGRATING MATERIALS AND MANUFACTURING INNOVATION (2017)

Article Engineering, Manufacturing

Extraction of Process-Structure Evolution Linkages from X-ray Scattering Measurements Using Dimensionality Reduction and Time Series Analysis

David B. Brough et al.

INTEGRATING MATERIALS AND MANUFACTURING INNOVATION (2017)

Review Materials Science, Multidisciplinary

Microstructure-based knowledge systems for capturing process-structure evolution linkages

David B. Brough et al.

CURRENT OPINION IN SOLID STATE & MATERIALS SCIENCE (2017)

Review Materials Science, Multidisciplinary

Informatics and data science in materials microscopy

Paul M. Voyles

CURRENT OPINION IN SOLID STATE & MATERIALS SCIENCE (2017)

Article Engineering, Manufacturing

Process-Structure Linkages Using a Data Science Approach: Application to Simulated Additive Manufacturing Data

Evdokia Popova et al.

INTEGRATING MATERIALS AND MANUFACTURING INNOVATION (2017)

Article Materials Science, Multidisciplinary

Extraction of reduced-order process-structure linkages from phase-field simulations

Yuksel C. Yabansu et al.

ACTA MATERIALIA (2017)

Article Computer Science, Artificial Intelligence

Time-delayed dynamic neural network-based model for hysteresis behavior of shape-memory alloys

Huanhuan Mai et al.

NEURAL COMPUTING & APPLICATIONS (2016)

Article Materials Science, Multidisciplinary

Statistical construction of 3-D microstructures from 2-D exemplars collected on oblique sections

David M. Turner et al.

ACTA MATERIALIA (2016)

Article Materials Science, Multidisciplinary

Stochastic microstructure characterization and reconstruction via supervised learning

Ramin Bostanabad et al.

ACTA MATERIALIA (2016)

Article Materials Science, Multidisciplinary

Multi-objective optimization of weld geometry in hybrid fiber laser-arc butt welding using Kriging model and NSGA-II

Zhongmei Gao et al.

APPLIED PHYSICS A-MATERIALS SCIENCE & PROCESSING (2016)

Article Materials Science, Multidisciplinary

Prediction of fatigue stress concentration factor using extreme learning machine

Baoxian Wang et al.

COMPUTATIONAL MATERIALS SCIENCE (2016)

Article Materials Science, Multidisciplinary

Image driven machine learning methods for microstructure recognition

Aritra Chowdhury et al.

COMPUTATIONAL MATERIALS SCIENCE (2016)

Article Engineering, Multidisciplinary

Data-driven computational mechanics

T. Kirchdoerfer et al.

COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING (2016)

Article Engineering, Multidisciplinary

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

Zeliang Liu et al.

COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING (2016)

Article Materials Science, Multidisciplinary

An extended micromechanics method for probing interphase properties in polymer nanocomposites

Zeliang Liu et al.

JOURNAL OF THE MECHANICS AND PHYSICS OF SOLIDS (2016)

Article Materials Science, Multidisciplinary

Prediction of Compressive Strength of Concrete Using Artificial Neural Network and Genetic Programming

Palika Chopra et al.

ADVANCES IN MATERIALS SCIENCE AND ENGINEERING (2016)

Article Engineering, Manufacturing

Multi-objective optimization of the turning process using a Gravitational Search Algorithm (GSA) and NSGA-II approach

S. Klancnik et al.

ADVANCES IN PRODUCTION ENGINEERING & MANAGEMENT (2016)

Article Computer Science, Artificial Intelligence

Data-driven prognostic method based on Bayesian approaches for direct remaining useful life prediction

A. Mosallam et al.

JOURNAL OF INTELLIGENT MANUFACTURING (2016)

Article Computer Science, Artificial Intelligence

A recurrent neural network for modeling crack growth of aluminium alloy

Linxian Zhi et al.

NEURAL COMPUTING & APPLICATIONS (2016)

Article Materials Science, Multidisciplinary

Representation and calibration of elastic localization kernels for a broad class of cubic polycrystals

Yuksel C. Yabansu et al.

ACTA MATERIALIA (2015)

Review Materials Science, Multidisciplinary

Materials Data Science: Current Status and Future Outlook

Surya R. Kalidindi et al.

ANNUAL REVIEW OF MATERIALS RESEARCH, VOL 45 (2015)

Article Materials Science, Multidisciplinary

A computer vision approach for automated analysis and classification of microstructural image data

Brian L. DeCost et al.

COMPUTATIONAL MATERIALS SCIENCE (2015)

Article Engineering, Multidisciplinary

Computational homogenization of nonlinear elastic materials using neural networks

B. A. Le et al.

INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING (2015)

Review Computer Science, Artificial Intelligence

Deep learning in neural networks: An overview

Juergen Schmidhuber

NEURAL NETWORKS (2015)

Article Multidisciplinary Sciences

A predictive machine learning approach for microstructure optimization and materials design

Ruoqian Liu et al.

SCIENTIFIC REPORTS (2015)

Article Engineering, Manufacturing

Machine learning approaches for elastic localization linkages in high-contrast composite materials

Ruoqian Liu et al.

INTEGRATING MATERIALS AND MANUFACTURING INNOVATION (2015)

Article Materials Science, Multidisciplinary

Calibrated localization relationships for elastic response of polycrystalline aggregates

Yuksel C. Yabansu et al.

ACTA MATERIALIA (2014)

Article Computer Science, Artificial Intelligence

Bead geometry prediction for robotic GMAW-based rapid manufacturing through a neural network and a second-order regression analysis

Jun Xiong et al.

JOURNAL OF INTELLIGENT MANUFACTURING (2014)

Article Computer Science, Artificial Intelligence

An artificial neural network model to characterize porosity defects during solidification of A356 aluminum alloy

Ishita Ghosh et al.

NEURAL COMPUTING & APPLICATIONS (2014)

Article Engineering, Manufacturing

Exploration of data science techniques to predict fatigue strength of steel from composition and processing parameters

Ankit Agrawal et al.

INTEGRATING MATERIALS AND MANUFACTURING INNOVATION (2014)

Article Engineering, Biomedical

Magnesium degradation as determined by artificial neural networks

Regine Willumeit et al.

ACTA BIOMATERIALIA (2013)

Article Engineering, Manufacturing

Novel microstructure quantification framework for databasing, visualization, and analysis of microstructure data

Stephen R. Niezgoda et al.

INTEGRATING MATERIALS AND MANUFACTURING INNOVATION (2013)

Article Materials Science, Multidisciplinary

Formulation and calibration of higher-order elastic localization relationships using the MKS approach

Tony Fast et al.

ACTA MATERIALIA (2011)

Article Mathematics, Applied

Improved non-dominated sorting genetic algorithm (NSGA)-II in multi-objective optimization studies of wind turbine blades

Long Wang et al.

APPLIED MATHEMATICS AND MECHANICS-ENGLISH EDITION (2011)

Article Biophysics

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

Ridha Hambli et al.

BIOMECHANICS AND MODELING IN MECHANOBIOLOGY (2011)

Article Engineering, Mechanical

A neural network approach to fatigue life prediction

Joao Carlos Figueira Pujol et al.

INTERNATIONAL JOURNAL OF FATIGUE (2011)

Article Materials Science, Multidisciplinary

Microstructure Informatics Using Higher-Order Statistics and Efficient Data-Mining Protocols

Surya R. Kalidindi et al.

Article Engineering, Mechanical

Prognostic modelling options for remaining useful life estimation by industry

J. Z. Sikorska et al.

MECHANICAL SYSTEMS AND SIGNAL PROCESSING (2011)

Article Computer Science, Interdisciplinary Applications

Lifetime prediction using accelerated test data and neural networks

S. Freitag et al.

COMPUTERS & STRUCTURES (2009)

Article Engineering, Multidisciplinary

Modeling of materials with fading memory using neural networks

Markus Oeser et al.

INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING (2009)

Article Engineering, Mechanical

Comparative study between ANN models and conventional equations in the analysis of fatigue failure of GFRP

Raimundo Carlos Silverio Freire Junior et al.

INTERNATIONAL JOURNAL OF FATIGUE (2009)

Article Materials Science, Multidisciplinary

Delineation of the space of 2-point correlations in a composite material system

S. R. Niezgoda et al.

ACTA MATERIALIA (2008)

Article Materials Science, Multidisciplinary

Microstructure reconstructions from 2-point statistics using phase-recovery algorithms

David T. Fullwood et al.

ACTA MATERIALIA (2008)

Article Engineering, Mechanical

Artificial neural networks in spectrum fatigue life prediction of composite materials

Anastasios P. Vassiopoulos et al.

INTERNATIONAL JOURNAL OF FATIGUE (2007)

Article Materials Science, Multidisciplinary

Identification of viscoplastic material parameters from spherical indentation data: Part I. Neural networks

E Tyulyukovskiy et al.

JOURNAL OF MATERIALS RESEARCH (2006)

Article Materials Science, Multidisciplinary

Identification of viscoplastic material parameters from spherical indentation data:: Part II.: Experimental validation of the method

D Klötzer et al.

JOURNAL OF MATERIALS RESEARCH (2006)

Article Materials Science, Multidisciplinary

Classification and reconstruction of three-dimensional microstructures using support vector machines

V Sundararaghavan et al.

COMPUTATIONAL MATERIALS SCIENCE (2005)

Article Engineering, Multidisciplinary

Numerical implementation of a neural network based material model in finite element analysis

YMA Hashash et al.

INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING (2004)

Article Computer Science, Artificial Intelligence

Real-time computing without stable states:: A new framework for neural computation based on perturbations

W Maass et al.

NEURAL COMPUTATION (2002)

Article Multidisciplinary Sciences

Identification of elastic-plastic material parameters from pyramidal indentation of thin films

N Huber et al.

PROCEEDINGS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES (2002)

Article Computer Science, Artificial Intelligence

A fast and elitist multiobjective genetic algorithm: NSGA-II

K Deb et al.

IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION (2002)

Article Computer Science, Artificial Intelligence

Random forests

L Breiman

MACHINE LEARNING (2001)

Article Engineering, Multidisciplinary

A neural network tool for identifying the material parameters of a finite deformation viscoplasticity model with static recovery

N Huber et al.

COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING (2001)