Article (Scientific journals)
Comparison of stochastic and interval methods for uncertainty quantification of metal forming processes
Arnst, Maarten; Ponthot, Jean-Philippe; Boman, Romain
2018In Comptes Rendus Mécanique, 346 (8), p. 634-646
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Keywords :
Metal forming; Uncertainty quantification; Stochastic methods; Interval methods; Sensitivity analysis; Parameter study
Abstract :
[en] Various sources of uncertainty can arise in metal forming processes, or their numerical simulation, or both, such as uncertainty in material behavior, process conditions, and geometry. Methods from the domain of uncertainty quantification can help assess the impact of such uncertainty on metal forming processes and their numerical simulation, and they can thus help improve robustness and predictive accuracy. In this paper, we compare stochastic methods and interval methods, two classes of methods receiving broad attention in the domain of uncertainty quantification, through their application to a numerical simulation of a sheet metal forming process.
Disciplines :
Mechanical engineering
Author, co-author :
Arnst, Maarten ;  Université de Liège - ULiège > Département d'aérospatiale et mécanique > Computational and stochastic modeling
Ponthot, Jean-Philippe  ;  Université de Liège - ULiège > Département d'aérospatiale et mécanique > LTAS-Mécanique numérique non linéaire
Boman, Romain  ;  Université de Liège - ULiège > Département d'aérospatiale et mécanique > Département d'aérospatiale et mécanique
Language :
English
Title :
Comparison of stochastic and interval methods for uncertainty quantification of metal forming processes
Publication date :
August 2018
Journal title :
Comptes Rendus Mécanique
ISSN :
1631-0721
Publisher :
Elsevier Masson, Paris, France
Special issue title :
Computational modeling of material forming processes
Volume :
346
Issue :
8
Pages :
634-646
Peer reviewed :
Peer Reviewed verified by ORBi
Available on ORBi :
since 18 July 2018

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