4.7 Article

Understanding and predicting defect formation in automated fibre placement pre-preg laminates

Journal

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.compositesa.2017.08.008

Keywords

Composite manufacturing simulation; Consolidation; Gaps and overlaps; Wrinkles

Funding

  1. UK Engineering Physical Sciences Research Council (EPSRC) Centre for Innovative Manufacturing in Composites project Defect Generation Mechanisms in Thick and Variable Thickness Composite Parts Understanding, Predicting and Mitigation (DefGen) [EP/1033513/1]
  2. EPSRC [EP/I033513/1] Funding Source: UKRI

Ask authors/readers for more resources

Fibre path defects are detrimental to the structural integrity of composite components and need to be minimised through process optimization. This requires understanding of the uncured pre-preg material, which is influenced by multiple process parameters, and sophisticated multi-scale modelling tools. Even though the capabilities of process modelling techniques have been improved over the past decades, the occurrence of localised wrinkles remains challenging to predict. One of the processes known to influence the formation of fibre path defects is the consolidation of laminates manufactured by automated fibre placement. The particular focus of this paper is to understand how out-of-plane wrinkles form during debulking and autoclave curing of laminates with embedded gaps and overlaps between the deposited tapes. Predictions are made using a novel modelling framework and validated against micro-scale geometry characterisation of artificially manufactured samples. The paper demonstrates the model's ability to predict consolidation defects for the latest generation of toughened pre-pregs. (C) 2017 The Author(s). Published by Elsevier Ltd.

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