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Towards an accurate pressure estimation in injection molding simulation using surrogate modeling

Article dans une revue avec comité de lecture
Author
SAAD, Sandra
211916 Laboratoire Angevin de Mécanique, Procédés et InnovAtion [LAMPA]
356027 Robert Bosch Gmbh [Schwieberdingen]
SINHA, Alankar
CRUZ, Camilo
86289 Laboratoire Procédés et Ingénierie en Mécanique et Matériaux [PIMM]
356027 Robert Bosch Gmbh [Schwieberdingen]
ccAMMAR, Amine
211916 Laboratoire Angevin de Mécanique, Procédés et InnovAtion [LAMPA]
ccREGNIER, Gilles
86289 Laboratoire Procédés et Ingénierie en Mécanique et Matériaux [PIMM]

URI
http://hdl.handle.net/10985/23263
DOI
10.1007/s12289-022-01717-0
Date
2022-10
Journal
International Journal of Material Forming

Abstract

The computational cost of high-fidelity injection molding simulations has been growing in the past years making it more and more challenging to use them for performing analyses such as optimizations or uncertainty quantification. Surrogate modeling offers a cheaper way to realize such studies and has been gaining attention in the field of injection molding simulation. In this work, we propose to compare three surrogate modeling techniques along with two design of experiment methods in their ability to predict the pressure signal at a surface node in a Moldflow simulation by varying process and modeling parameters. A Sobol sensitivity analysis is performed to study the contribution of the varied parameters on the pressure results. In addition, one of the generated models is used along with experimental pressure sensor data to improve the pressure estimation by calibrating the heat transfer coefficients during filling and packing as well as the pressure-dependency coefficient in the Cross-WLF viscosity model. This resulted in major improvements of the pressure predictions for all 27 considered cases in comparison to using the default heat transfer coefficients and viscosity model parameter.

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

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