From virtual clustering analysis to self-consistent clustering analysis: a mathematical study
type: Item
instance of: scholarly article
title: From virtual clustering analysis to self-consistent clustering analysis: a mathematical study
zbMATH Open document ID: 1471.74079
author: Lei Zhang
author: Wing K. Liu
author: Shaoqiang Tang
published in: Computational Mechanics
publication date: 2018-12-05T00:00:00Z
Mathematics Subject Classification ID: 74S99
Mathematics Subject Classification ID: 74Q99
Mathematics Subject Classification ID: 68T05
zbMATH DE Number: 6989148
zbMATH Keywords: numerical homogenization
zbMATH Keywords: convergence
zbMATH Keywords: machine learning
zbMATH Keywords: Lippmann-Schwinger equation
zbMATH Keywords: Saint-Venant principle
MaRDI profile type: Publication
full work available at URL: s00466-018-1573-x
OpenAlex ID: W2791175628
Wikidata QID: Q113327257
cites work: Q5198904
cites work: Multiscale Modeling and Simulation of Composite Materials and Structures
cites work: Multiscale Methods
cites work: Nonuniform transformation field analysis
cites work: The reduced model multiscale method (R3M) for the nonlinear homogenization of hyperelastic media at finite strains
cites work: Self-consistent clustering analysis: an efficient multi-scale scheme for inelastic heterogeneous materials
cites work: Microstructural material database for self-consistent clustering analysis of elastoplastic strain softening materials
cites work: Mathematical foundations of the immersed finite element method
DOI: 10.1007/S00466-018-1573-X
description: scientific article; zbMATH DE number 6989148