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Learning the Macroscopic Flow Model of Short Fiber Suspensions from Fine-Scale Simulated Data

Fiber–fiber interaction plays an important role in the evolution of fiber orientation in semi-concentrated suspensions. Flow induced orientation in short-fiber reinforced composites determines the anisotropic properties of manufactured parts and consequently their performances. In the case of dilute...

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Autores principales: Yun, Minyoung, Argerich Martin, Clara, Giormini, Pierre, Chinesta, Francisco, Advani, Suresh
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7516452/
https://www.ncbi.nlm.nih.gov/pubmed/33285805
http://dx.doi.org/10.3390/e22010030
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author Yun, Minyoung
Argerich Martin, Clara
Giormini, Pierre
Chinesta, Francisco
Advani, Suresh
author_facet Yun, Minyoung
Argerich Martin, Clara
Giormini, Pierre
Chinesta, Francisco
Advani, Suresh
author_sort Yun, Minyoung
collection PubMed
description Fiber–fiber interaction plays an important role in the evolution of fiber orientation in semi-concentrated suspensions. Flow induced orientation in short-fiber reinforced composites determines the anisotropic properties of manufactured parts and consequently their performances. In the case of dilute suspensions, the orientation evolution can be accurately described by using the Jeffery model; however, as soon as the fiber concentration increases, fiber–fiber interactions cannot be ignored anymore and the final orientation state strongly depends on the modeling of those interactions. First modeling frameworks described these interactions from a diffusion mechanism; however, it was necessary to consider richer descriptions (anisotropic diffusion, etc.) to address experimental observations. Even if different proposals were considered, none of them seem general and accurate enough. In this paper we do not address a new proposal of a fiber interaction model, but a data-driven methodology able to enrich existing models from data, that in our case comes from a direct numerical simulation of well resolved microscopic physics.
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spelling pubmed-75164522020-11-09 Learning the Macroscopic Flow Model of Short Fiber Suspensions from Fine-Scale Simulated Data Yun, Minyoung Argerich Martin, Clara Giormini, Pierre Chinesta, Francisco Advani, Suresh Entropy (Basel) Article Fiber–fiber interaction plays an important role in the evolution of fiber orientation in semi-concentrated suspensions. Flow induced orientation in short-fiber reinforced composites determines the anisotropic properties of manufactured parts and consequently their performances. In the case of dilute suspensions, the orientation evolution can be accurately described by using the Jeffery model; however, as soon as the fiber concentration increases, fiber–fiber interactions cannot be ignored anymore and the final orientation state strongly depends on the modeling of those interactions. First modeling frameworks described these interactions from a diffusion mechanism; however, it was necessary to consider richer descriptions (anisotropic diffusion, etc.) to address experimental observations. Even if different proposals were considered, none of them seem general and accurate enough. In this paper we do not address a new proposal of a fiber interaction model, but a data-driven methodology able to enrich existing models from data, that in our case comes from a direct numerical simulation of well resolved microscopic physics. MDPI 2019-12-24 /pmc/articles/PMC7516452/ /pubmed/33285805 http://dx.doi.org/10.3390/e22010030 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Yun, Minyoung
Argerich Martin, Clara
Giormini, Pierre
Chinesta, Francisco
Advani, Suresh
Learning the Macroscopic Flow Model of Short Fiber Suspensions from Fine-Scale Simulated Data
title Learning the Macroscopic Flow Model of Short Fiber Suspensions from Fine-Scale Simulated Data
title_full Learning the Macroscopic Flow Model of Short Fiber Suspensions from Fine-Scale Simulated Data
title_fullStr Learning the Macroscopic Flow Model of Short Fiber Suspensions from Fine-Scale Simulated Data
title_full_unstemmed Learning the Macroscopic Flow Model of Short Fiber Suspensions from Fine-Scale Simulated Data
title_short Learning the Macroscopic Flow Model of Short Fiber Suspensions from Fine-Scale Simulated Data
title_sort learning the macroscopic flow model of short fiber suspensions from fine-scale simulated data
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7516452/
https://www.ncbi.nlm.nih.gov/pubmed/33285805
http://dx.doi.org/10.3390/e22010030
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