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

FEM-Cluster based reduction method for efficient numerical prediction of effective properties of heterogeneous material in nonlinear range

(2019) Gengdong Cheng et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

Principle of cluster minimum complementary energy of FEM-cluster-based reduced order method: fast updating the interaction matrix and predicting effective nonlinear properties of heterogeneous material

(2019) Yinghao Nie et al.   COMPUTATIONAL MECHANICS

Fast calculation of interaction tensors in clustering-based homogenization

(2019) Lei Zhang et al.   COMPUTATIONAL MECHANICS

Self-consistent clustering analysis for multiscale modeling at finite strains

(2019) Cheng Yu et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

Data-Driven Microstructure and Microhardness Design in Additive Manufacturing Using a Self-Organizing Map

(2019) Zhengtao Gan et al.   Engineering

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

(2018) Ahmet Cecen et al.   ACTA MATERIALIA

Improving direct physical properties prediction of heterogeneous materials from imaging data via convolutional neural network and a morphology-aware generative model

(2018) Ruijin Cang et al.   COMPUTATIONAL MATERIALS SCIENCE

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

(2018) Zijiang Yang et al.   COMPUTATIONAL MATERIALS SCIENCE

From virtual clustering analysis to self-consistent clustering analysis: a mathematical study

(2018) Shaoqiang Tang et al.   COMPUTATIONAL MECHANICS

Data-Driven Mechanistic Modeling of Influence of Microstructure on High-Cycle Fatigue Life of Nickel Titanium

(2018) Orion L. Kafka et al.   JOM

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

Establishing structure-property localization linkages for elastic deformation of three-dimensional high contrast composites using deep learning approaches

(2018) Zijiang Yang et al.   ACTA MATERIALIA

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

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

A nonlinear manifold-based reduced order model for multiscale analysis of heterogeneous hyperelastic materials

(2016) Satyaki Bhattacharjee et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Computational homogenization of nonlinear elastic materials using neural networks

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

Deep learning in neural networks: An overview

(2015) Jürgen Schmidhuber   NEURAL NETWORKS

Stress-related topology optimization via level set approach

(2011) Xu Guo et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING