Experimental characterization and modeling of the temperature and rate-dependent shear behaviour of powder-impregnated glass fiber/PA66 woven semipregs - Archive ouverte HAL Access content directly
Journal Articles Composites Science and Technology Year : 2019

Experimental characterization and modeling of the temperature and rate-dependent shear behaviour of powder-impregnated glass fiber/PA66 woven semipregs

(1, 2) , (2) , (1) , (2) , (1) , (3)
1
2
3
Olivier de Almeida
Peter Martin
Fabrice Schmidt
Jérôme Bikard
  • Function : Author
  • PersonId : 874470

Abstract

This study focuses on the characterization of the in-plane shear response of a novel powder-impregnated, non-consolidated PA66/glass semipreg to evaluate its forming behaviour. The effects of temperature and rate on the behaviour of the semipreg and the preconsolidated material were investigated using bias-extension tests. Results obtained show an increase in shear stress with decreasing temperature and increasing rate, with the semipreg exhibiting a lower sensitivity to the test speed. An increase of the flow distance to impregnate the yarns, due to intra-ply sliding mechanisms specific to the powder-impregnated semipreg, is observed. A model based on a hypoelastic approach with temperature and rate dependence is proposed to represent the material behaviour. Isothermal simulations of the bias-extension test are conducted. Results show a good agreement between the model and experimental data in terms of force and shear angle prediction.
Fichier principal
Vignette du fichier
experimental-characterization-and-modeling.pdf (2.61 Mo) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-02134092 , version 1 (20-05-2019)

Identifiers

Cite

Theo Baumard, Gary Menary, Olivier de Almeida, Peter Martin, Fabrice Schmidt, et al.. Experimental characterization and modeling of the temperature and rate-dependent shear behaviour of powder-impregnated glass fiber/PA66 woven semipregs. Composites Science and Technology, 2019, 180, pp.23-32. ⟨10.1016/j.compscitech.2019.05.011⟩. ⟨hal-02134092⟩
106 View
100 Download

Altmetric

Share

Gmail Facebook Twitter LinkedIn More