Enhancing data representation in forging processes: Investigating discretization and R-adaptivity strategies with Proper Orthogonal Decomposition reduction - Archive ouverte HAL
Article Dans Une Revue Finite Elements in Analysis and Design Année : 2024

Enhancing data representation in forging processes: Investigating discretization and R-adaptivity strategies with Proper Orthogonal Decomposition reduction

Résumé

Effective data reduction techniques are crucial for enhancing computational efficiency in complex industrial processes such as forging. In this study, we investigate various discretization and mesh adaptivity strategies using Proper Orthogonal Decomposition (POD) to optimize data reduction fidelity in forging simulations. We focus particularly on r-adaptivity techniques, which ensure a consistent number of elements throughout the field representation, filling a gap in existing research that predominantly concentrates on h-adaptivity. Our investigation compares isotropic mesh approaches with anisotropic mesh adaptations, including gradient-based, isolines-based, and spring-energy-based methods. Through numerical simulations and analysis, we demonstrate that these anisotropic techniques provide superior fidelity in representing deformation fields compared to isotropic meshes. These improvements are achieved while maintaining a similar level of model reduction efficiency. This enhancement in representation leads to improved data reduction quality, forming the foundation for data-driven models. This research contributes to advancing the understanding of mesh adaptivity approaches and their potential applications in data-driven modeling across various industrial domains.
Fichier principal
Vignette du fichier
LCFC_FINEL_2024_URIBE.pdf (7.1 Mo) Télécharger le fichier
Origine Publication financée par une institution
Licence

Dates et versions

hal-04816366 , version 1 (03-12-2024)

Licence

Identifiants

Citer

David Uribe, Camille Durand, Cyrille Baudouin, Régis Bigot. Enhancing data representation in forging processes: Investigating discretization and R-adaptivity strategies with Proper Orthogonal Decomposition reduction. Finite Elements in Analysis and Design, 2024, 242, pp.104276. ⟨10.1016/j.finel.2024.104276⟩. ⟨hal-04816366⟩
0 Consultations
0 Téléchargements

Altmetric

Partager

More