Numerical modeling of nonlinearity, plasticity and damage in CFRP-woven composites for crash simulations - Université Polytechnique des Hauts-de-France Accéder directement au contenu
Communication Dans Un Congrès Année : 2014

Numerical modeling of nonlinearity, plasticity and damage in CFRP-woven composites for crash simulations

Résumé

Car manufacturers have to develop lightweight structures to limit the weight-increase induced by the new advanced powertrain systems for hybrid and electrical vehicles. Due to their draping, stiffness, improved ductility and damage tolerance properties woven composites are being increasingly used for the design of crash-relevant structural parts. Before an introduction of the strategies and the conditions set by industrial applications, the main current modeling techniques available for composites in the LS-DYNA finite element code featuring with explicit time integration will be discussed. A user defined composite material model (UMAT) characterized by a linear as well as non-linear behavior coupled with a plasticity definition will be then proposed. A maximal stress criterion is used to detect the failure on the ply. Four post-failure damage definitions have been investigated in order to account for the post-failure progressive material degradation. Finally, experimental results on coupons tests are used to identify the macroscopic behavior and the effective properties of the considered material. Experimental impact tests are then used to investigate the post-peak behavior.
Fichier non déposé

Dates et versions

hal-03448572 , version 1 (25-11-2021)

Identifiants

Citer

Olivier Cousigné, David Moncayo, Daniel Coutellier, Pedro P Camanho, Hakim Naceur. Numerical modeling of nonlinearity, plasticity and damage in CFRP-woven composites for crash simulations. 17th International Conference on Composite Structures, Jun 2013, Porto, Portugal. pp.75-88, ⟨10.1016/j.compstruct.2014.04.017⟩. ⟨hal-03448572⟩
22 Consultations
0 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More