Shrinkage porosity prediction empowered by physics-based and data-driven hybrid models
Article dans une revue avec comité de lecture
Date
2022-03-25Journal
International Journal of Material FormingRésumé
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.
Fichier(s) constituant cette publication
Cette publication figure dans le(s) laboratoire(s) suivant(s)
Documents liés
Visualiser des documents liés par titre, auteur, créateur et sujet.
-
Article dans une revue avec comité de lectureJALOULI, Zahra; CAILLAUD, Aude; ARTOZOUL, Julien;
AMMAR, 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 ... -
Article dans une revue avec comité de lectureGRMELA, Miroslav; MAITREJEAN, Guillaume;
CHINESTA SORIA, Francisco;
AMMAR, Amine (Springer Verlag, 2013)
Smoluchowski kinetic equation governing the time evolution of the pair correlation function of rigid sphericalparticles suspended in a Newtonian fluid is extended to include particle migration. The extended kinetic equation ... -
Article dans une revue avec comité de lectureALFARO, Icíar; GONZALEZ, David; BORDEU, Felipe; LEYGUE, Adrien;
AMMAR, Amine;
CUETO, Elias;
CHINESTA SORIA, Francisco (Springer Verlag, 2014)
Simulation of all phenomena taking place in a surgical procedure is a formidable task that involves, when possible, the use of supercomputing facilities over long time periods. However, decision taking in the operating ... -
Article dans une revue avec comité de lectureAGHIGHI, Mohammad Saeid;
AMMAR, Amine; METIVIER, Christel; NORMANDIN, Magdeleine;
CHINESTA SORIA, Francisco (Elsevier, 2013)
This paper focuses on the non-incremental solution of transient coupled non-linear models, in particular the one related to the Rayleigh–Bénard flow problem that models natural thermal convection. For this purpose we are ... -
Article dans une revue avec comité de lectureAGHIGHI, Mohammad Saeid;
AMMAR, Amine; METIVIER, Christel;
CHINESTA SORIA, Francisco (Emerald, 2015)
Purpose – The purpose of this paper is to focus on the advanced solution of the parametric non-linear model related to the Rayleigh-Benard laminar flow involved in the modeling of natural thermal convection. This flow is ...