Numerical simulation and predictive modeling of an inextensible filament in two-dimensional viscous shear flow using the immersed boundary/coarse-graining method and artificial neural networks
type: Item
instance of: scholarly article
title: Numerical simulation and predictive modeling of an inextensible filament in two-dimensional viscous shear flow using the immersed boundary/coarse-graining method and artificial neural networks
author: Magdalini Ntetsika
author: P. Papadopoulos
published in: Computer Methods in Applied Mechanics and Engineering
publication date: 2022-11-11T00:00:00Z
Mathematics Subject Classification ID: 74F10
Mathematics Subject Classification ID: 74-10
zbMATH DE Number: 7614979
zbMATH Keywords: fluid-structure interaction
zbMATH Keywords: low-Reynolds number flow
zbMATH Keywords: inextensible filaments
zbMATH Keywords: immersed boundary method
zbMATH Keywords: coarse-graining
zbMATH Keywords: artificial neural networks
describes a project that uses: ElemStatLearn
describes a project that uses: Scikit
MaRDI profile type: Publication
full work available at URL: j.cma.2022.115589
OpenAlex ID: W4296536337
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cites work: Q5396710
cites work: The elements of statistical learning. Data mining, inference, and prediction
DOI: 10.1016/J.CMA.2022.115589
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description: scientific article; zbMATH DE number 7614979