• français
    • English
    français
  • Login
Help
View Item 
  •   Home
  • Laboratoire Angevin de Mécanique, Procédés et InnovAtion (LAMPA)
  • View Item
  • Home
  • Laboratoire Angevin de Mécanique, Procédés et InnovAtion (LAMPA)
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

Shrinkage porosity prediction empowered by physics-based and data-driven hybrid models

Article dans une revue avec comité de lecture
Author
ccNOURI, Madyen
211916 Laboratoire Angevin de Mécanique, Procédés et InnovAtion [LAMPA]
ccARTOZOUL, Julien
211916 Laboratoire Angevin de Mécanique, Procédés et InnovAtion [LAMPA]
CAILLAUD, Aude
211916 Laboratoire Angevin de Mécanique, Procédés et InnovAtion [LAMPA]
ccAMMAR, Ammar
211916 Laboratoire Angevin de Mécanique, Procédés et InnovAtion [LAMPA]
CHINESTA, Francisco
86289 Laboratoire Procédés et Ingénierie en Mécanique et Matériaux [PIMM]
KÖSER, Ole
564849 ESI Group [ESI Group]

URI
http://hdl.handle.net/10985/23271
DOI
10.1007/s12289-022-01677-5
Date
2022-03-25
Journal
International Journal of Material Forming

Abstract

Several defects might affect a casting part and degrade its quality and the process efficiency. Porosity formation is one of the major defects that can appear in the resulting product. Thus, several research studies aimed at investigating methods that minimize this anomaly. In the present work, a porosity prediction procedure is proposed to assist users at optimizing porosity distribution according to their application. This method is based on a supervised learning approach to predict shrinkage porosity from thermal history. Learning data are generated by a casting simulation software operating for different process parameters. Machine learning was coupled with a modal representation to interpolate thermal history time series for new parameters combinations. By comparing the predicted values of local porosity to the simulated results, it was demonstrated that the proposed model is efficient and can open perspectives in the casting process optimization.

Files in this item

Name:
LAMPA_IJMF_AMMAR_2022.pdf
Size:
3.664Mb
Format:
PDF
View/Open

Collections

  • Laboratoire Angevin de Mécanique, Procédés et InnovAtion (LAMPA)
  • Laboratoire Procédés et Ingénierie en Mécanique et Matériaux (PIMM)

Related items

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

  • Modelling of shrinkage formation in casting by the phase field method 
    Article dans une revue avec comité de lecture
    JALOULI, Zahra; CAILLAUD, Aude; ARTOZOUL, Julien; ccAMMAR, Amine; EL-ABIDI, Ahmed; FETTAH, Ahmed (Springer Science and Business Media LLC, 2021-01-05)
    Most commercial softwares simulating casting process use a scalar field to quantify the shrinkage on final parts. The repartition of this scalar is used to localize shrinkage in the part. In this work, the objective is ...
  • On the solution of the heat equation in very thin tapes 
    Article dans une revue avec comité de lecture
    PRULIERE, Etienne; CHINESTA, Francisco; AMMAR, Amine; LEYGUE, Adrien; POITOU, Arnaud (Elsevier, 2012)
    This paper addresses two issues usually encountered when simulating thermal processes in forming processes involving tape-type geometries, as is the case of tape or tow placement, surface treatments, / The first issue ...
  • On the effective conductivity and the apparent viscosity of a thin rough polymer interface using PGD‐based separated representations 
    Article dans une revue avec comité de lecture
    AMMAR, Amine; GHNATIOS, Chady; DELPLACE, Frank; BARASINSKI, Anais; DUVAL, Jean-Louis; CUETO, Elias; CHINESTA, Francisco (Wiley, 2020)
    Composite manufacturing processes usually proceed from preimpregnated preforms that are consolidated by simultaneously applying heat and pressure, so as to ensure a perfect contact compulsory for making molecular diffusion ...
  • On the space-time separated representation of integral linear viscoelastic models 
    Article dans une revue avec comité de lecture
    AMMAR, Amine; ZGHAL, Ali; MOREL, Franck; CHINESTA, Francisco (Elsevier Masson, 2015)
    The analysis of materials mechanical behavior involves many computational challenges. In this work, we are addressing the transient simulation of the mechanical behavior when the time of interest is much larger than the ...
  • Separated representation of incremental elastoplastic simulations 
    Communication avec acte
    NASRI, Mohamed Aziz; AGUADO, Jose Vicente; AMMAR, Amine; CUETO, Elias; CHINESTA, Francisco; MOREL, Franck; ROBERT, Camille; EL AREM, Saber (Key Engineering Materials, 2015)
    Forming processes usually involve irreversible plastic transformations. The calculation in that case becomes cumbersome when large parts and processes are considered. Recently Model Order Reduction techniques opened new ...

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