• français
    • English
    français
  • Login
Help
View Item 
  •   Home
  • Laboratoire Procédés et Ingénierie en Mécanique et Matériaux (PIMM)
  • View Item
  • Home
  • Laboratoire Procédés et Ingénierie en Mécanique et Matériaux (PIMM)
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

Learning the macroscopic flow model of short fiber suspensions from fine-scale simulated data

Type
Articles dans des revues avec comité de lecture
Author
YUN, Minyoung
86289 Laboratoire Procédés et Ingénierie en Mécanique et Matériaux [PIMM]
ARGERICH MARTIN, Clara
86289 Laboratoire Procédés et Ingénierie en Mécanique et Matériaux [PIMM]
GIORMINI, Pierre
86289 Laboratoire Procédés et Ingénierie en Mécanique et Matériaux [PIMM]
CHINESTA, Francisco
86289 Laboratoire Procédés et Ingénierie en Mécanique et Matériaux [PIMM]
ADVANI, Suresh G.
93432 University of Delaware [Newark]

URI
http://hdl.handle.net/10985/18464
DOI
10.3390/e22010030
Date
2020
Journal
Entropy

Abstract

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.

Files in this item

Name:
PIMM_E_2020_YUN.pdf
Size:
696.5Kb
Format:
PDF
Description:
Article
View/Open

Collections

  • Laboratoire Procédés et Ingénierie en Mécanique et Matériaux (PIMM)

Related items

Showing items related by title, author, creator and subject.

  • 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 (MDPI AG, 2020)
    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 ...
  • Nonlinear Regression Operating on Microstructures Described from Topological Data Analysis for the Real-Time Prediction of Effective Properties 
    YUN, Minyoung; ARGERICH, Clara; CUETO, Elias; DUVAL, Jean Louis; CHINESTA, Francisco (MDPI, 2020)
    Real-time decision making needs evaluating quantities of interest (QoI) in almost real time. When these QoI are related to models based on physics, the use of Model Order Reduction techniques allows speeding-up calculations, ...
  • Tape surfaces characterization with persistence images 
    FRAHI, Tarek; ARGERICH, Clara; YUN, Minyoung; FALCO, Antonio; BARASINSKI, Anais; CHINESTA, Francisco (American Institute of Mathematical Sciences (AIMS), 2020)
    The aim of this paper is to leverage the main surface topological descriptors to classify tape surface profiles, through the modelling of the evolution of the degree of intimate contact along the consolidation of pre-impregnated ...
  • Code2vect: An efficient heterogenous data classifier and nonlinear regression technique 
    ARGERICH MARTÍN, Clara; IBÁÑEZ PINILLO, Rubén; BARASINSKI, Anaïs; CHINESTA, Francisco (ELSEVIER, 2019)
    The aim of this paper is to present a new classification and regression algorithm based on Artificial Intelligence. The main feature of this algorithm, which will be called Code2Vect, is the nature of the data to treat: ...
  • Effects of material and process parameters on in-situ consolidation 
    LEÓN, Angel; ARGERICH MARTÍN, Clara; BARASINSKI, Anaïs; SOCCARD, Eric; CHINESTA, Francisco (Springer, 2019)
    Automated tape placement - ATP - is a recent manufacturing technology for composite materials. Therefore, a correct modeling of the multi-physical process is critical in order to make possible in-situ consolidation. In ...

Browse

All SAMCommunities & CollectionsAuthorsIssue DateCenter / InstitutionThis CollectionAuthorsIssue DateCenter / Institution

Newsletter

Latest newsletterPrevious newsletters

Statistics

Most Popular ItemsStatistics by CountryMost Popular Authors

ÉCOLE NATIONALE SUPERIEURE D'ARTS ET METIERS

  • Contact
  • Mentions légales

ÉCOLE NATIONALE SUPERIEURE D'ARTS ET METIERS

  • Contact
  • Mentions légales