A Bayesian multiscale CNN framework to predict local stress fields in structures with microscale features
type: Item
instance of: scholarly article
title: A Bayesian multiscale CNN framework to predict local stress fields in structures with microscale features
author: Vasilis Krokos
author: Viet Bui Xuan
author: Philippe Young
author: P. Kerfriden
author: S. P. A. Bordas
published in: Computational Mechanics
publication date: 2022-03-17T00:00:00Z
full work available at URL: https://arxiv.org/abs/2012.11330
Mathematics Subject Classification ID: 74-XX
zbMATH DE Number: 7492692
zbMATH Keywords: multiscale stress analysis
zbMATH Keywords: convolutional neural network
zbMATH Keywords: surrogate modelling
zbMATH Keywords: Bayesian machine learning
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describes a project that uses: SimNet
describes a project that uses: EGO
describes a project that uses: SESR
describes a project that uses: StressGAN
describes a project that uses: MAP123-EP
describes a project that uses: MAP123-EPF
MaRDI profile type: Publication
OpenAlex ID: W3215227068
Wikidata QID: Q113326574
DOI: 10.1007/S00466-021-02112-3
description: scientific article; zbMATH DE number 7492692