Statistical characterization and reconstruction of heterogeneous microstructures using deep neural network

DOI10.1016/j.cma.2020.113516zbMath1506.74233OpenAlexW3096491245MaRDI QIDQ2020836

Song Cen, Shaoqing Cui, Jinlong Fu, Chen-Feng Li

Publication date: 26 April 2021

Published in: Computer Methods in Applied Mechanics and Engineering (Search for Journal in Brave)

Full work available at URL: https://cronfa.swan.ac.uk/Record/cronfa55670/Download/55670__18678__b5c2e882e0cb411da11c8290f3137a4c.pdf

zbMATH Keywords

random microstructureheterogeneous materialstatistical equivalencecharacterization and reconstructionphysical property

Mathematics Subject Classification ID

Artificial neural networks and deep learning (68T07) Micromechanics of solids (74M25) Stochastic and other probabilistic methods applied to problems in solid mechanics (74S60)

Related Items (3)

Hierarchical reconstruction of 3D well-connected porous media from 2D exemplars using statistics-informed neural network ⋮ Uncertainty quantification of microstructure variability and mechanical behavior of additively manufactured lattice structures ⋮ Stochastic reconstruction of 3D microstructures from 2D cross-sectional images using machine learning-based characterization

Uses Software

• darch
• TauFactor
• PRMLT

Cites Work

• Porous structure reconstruction using convolutional neural networks
• 3D numerical reconstruction of well-connected porous structure of rock using fractal algorithms
• New algorithms for virtual reconstruction of heterogeneous microstructures
• Statistical reconstruction and Karhunen-Loève expansion for multiphase random media
• Reducing the Dimensionality of Data with Neural Networks
• Markov Random Field Modeling in Image Analysis
• The Lattice Boltzmann Method
• Unnamed Item
• Unnamed Item

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