4.7 Article

Numerical prediction for viscoelasticity of woven carbon fiber reinforced polymers (CFRPs) during curing accounting for variation of yarn angle caused by preforming

Journal

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.compositesa.2023.107631

Keywords

Polymer-matrix composites (PMCs); Stress relaxation; Finite element analysis (FEA); Cure

Ask authors/readers for more resources

Existing methods for modeling viscoelasticity of woven composites during curing lack accuracy in numerical simulation due to neglecting interaction among yarns and considering preforming effects. In this paper, a novel geometric modeling method involving finite element analysis (FEA) and element mapping is proposed to accurately simulate the stress relaxation of woven carbon fiber reinforced composites (CFRPs). Experimental validation indicates that this approach can effectively capture the viscoelastic response of woven CFRPs under complex processing conditions.
To model viscoelasticity of woven composites during curing, existing methods were mostly derived by directly mixing the material models for constituents and neglecting interaction among yarns, causing inaccuracy in numerical simulation. In addition, the preforming effects, which exist for production of parts with complex geometry, on curing of woven composites were rarely considered. In this paper, a novel geometric modeling method, involving finite element analysis (FEA) and element mapping, was first established to obtain voxel mesh for non-orthogonal representative volume element (RVE) structures. Through integration of the thermoviscoelastic constitutive models and voxel mesh, FEA was conducted to predict stress relaxation of woven CFRPs with varying yarn angles and degrees of curing (DOCs). Experimental validation indicates that the FEA can capture viscoelastic response of woven CFRPs with different yarn angles and DOCs with around 4.96 % average weighed error, meaning the new approach can virtually characterize viscoelasticity of woven composites under complex processing conditions.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available