Learning constitutive models from microstructural simulations via a non-intrusive reduced basis method: extension to geometrical parameterizations
type: Item
instance of: scholarly article
title: Learning constitutive models from microstructural simulations via a non-intrusive reduced basis method: extension to geometrical parameterizations
author: Theron Guo
author: Francesco A. B. Silva
author: Karen Veroy
author: Ondřej Rokoš
published in: Computer Methods in Applied Mechanics and Engineering
publication date: 2022-11-11T00:00:00Z
full work available at URL: https://arxiv.org/abs/2206.13627
Mathematics Subject Classification ID: 74-10
Mathematics Subject Classification ID: 74M25
Mathematics Subject Classification ID: 74Q15
zbMATH DE Number: 7614996
zbMATH Keywords: reduced order modeling
zbMATH Keywords: geometrical transformation
zbMATH Keywords: proper orthogonal decomposition
zbMATH Keywords: computational homogenization
zbMATH Keywords: Gaussian process regression
zbMATH Keywords: shape optimization
describes a project that uses: F3DAM
describes a project that uses: FFTHomPy
describes a project that uses: GAUSSIAN
describes a project that uses: MOOSE
describes a project that uses: PyTorch
describes a project that uses: GPy
describes a project that uses: redbKIT
describes a project that uses: GitHub
MaRDI profile type: Publication
OpenAlex ID: W4283723537
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DOI: 10.1016/J.CMA.2022.115636
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