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Enhancing metal-forming predictions with VR-infused digital twin models

Communication avec acte
Author
ccURIBE, David
107452 Laboratoire de Conception Fabrication Commande [LCFC]
ccBAUDOUIN, Cyrille
107452 Laboratoire de Conception Fabrication Commande [LCFC]
ccLOCARD, Yoan
211916 Laboratoire Angevin de Mécanique, Procédés et InnovAtion [LAMPA]
ccDURAND, Camille
107452 Laboratoire de Conception Fabrication Commande [LCFC]
ccBIGOT, Regis
107452 Laboratoire de Conception Fabrication Commande [LCFC]

URI
http://hdl.handle.net/10985/25188
DOI
10.21741/9781644903131-254
Date
2024-05

Abstract

This article presents a two-step method to enhance metal-forming predictions by integrating Virtual Reality (VR) into Digital Twin models, focusing on single-blow cold copper upsetting operations. The process begins with developing a real-time predictive surrogate model that considers actual process parameters, acting as a crucial link between conventional numerical simulations and immediate decision-making. Subsequently, the surrogate model is integrated into a realistic VR environment, aligned with the experimental forging setup. The study underscores the need and potential advantages of real-time digital twins in the forging field, emphasizing the bridging capability between numerical simulations and instant decision-making through predictive modeling and immersive virtual environments.

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  • Laboratoire Angevin de Mécanique, Procédés et InnovAtion (LAMPA)
  • Laboratoire de Conception Fabrication Commande (LCFC)

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    Communication avec acte
    URIBE, David; ccDURAND, Camille; ccBAUDOUIN, Cyrille; KRUMPIPE, Pierre; ccBIGOT, Regis (Springer Nature Switzerland, 2023-08)
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  • Enhancing data representation in forging processes: Investigating discretization and R-adaptivity strategies with Proper Orthogonal Decomposition reduction 
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