A rapid flow assessment tool for automated dry fibre preforms – a numerical and experimental study

Shafique, Usman (2022) A rapid flow assessment tool for automated dry fibre preforms – a numerical and experimental study. PhD thesis, University of Nottingham.

[img]
Preview
PDF (Thesis - as examined) - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
Available under Licence Creative Commons Attribution.
Download (16MB) | Preview

Abstract

Automated dry fibre placement (ADFP) has gained the attention of the aerospace industry in the past few years. The preforms produced by ADFP are manufactured into composite parts by liquid composite moulding (LCM) processes. In contrast to manual preforming, this automated process reduces the required time and improves quality of layup. Whereas, LCM offers low cost manufacturing, making it an excellent selection when producing large parts. Due to high compaction of unidirectional fibres during the deposition process and binder presence, the preforms are produced with high fibre volume fractions. This decreases the permeability of these preforms and effects the overall fill time during LCM. During the deposition process defects are induced into the preforms from machine inaccuracy, variability in material and poor adhesion. This results in the formation of inter-tow or inter-course gaps and overlaps.

Since gaps are inevitable in ADFP preforms, they have sometimes been intentionally programmed and placed into preform to avoid overlaps. These gaps form a vascular network of gaps within the preform and act as flow channels. This effects the overall permeability of ADFP preforms by enhancing the flow during LCM.

In this thesis, conventional methods employed to predict permeability of such preforms are compared with the experimental results on meso-scale and macro-scale level. The results showed that the percentage difference between experimental and analytical results is increased up to 165% on macro-scale and lowest in case of the only tow results (45%). In either cases the difference between results are significant. Therefore a novel method to characterize flow behaviour in a preform with gap networks of any complexity is developed. This is achieved by producing a gap network based on real preform data acquired from the deposition rig, development of numerical model based on pipe network approach to compute flow rates across the network and visualization of flow behaviour in preform through homogenised velocity mapping.

This approach facilitated the successful reconstruction of geometries of preform reported in literature. Lower difference in comparison to the experimental permeability was found: 50% for nominal model where 1mm gap width is assigned across the preform and 19% for averaged model where 0.8mm averaged gap width was used. The numerical model was able to process 4300 gaps in under 6 minutes and enables a user to execute the network model as soon as the preform data file is ready and predict the averaged preform permeability while the preform is being prepared for LCM and make the relevant changes to achieve lower fill times. Moreover, the low computational times for this numerical model enables flow characterization of each preform produced. This eliminates the need of conventional time consuming and expensive steps such as XCT, microscopy to accesses limited preform data and produce a working mesh to enable 2D or 3D flow simulation.

Item Type: Thesis (University of Nottingham only) (PhD)
Supervisors: Turner, Thomas
Evans, Anthony
Harper, Lee
Keywords: Composite materials; Manufacturing processes; Aerospace materials; Automated preforming; Permeability
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
Faculties/Schools: UK Campuses > Faculty of Engineering > Department of Mechanical, Materials and Manufacturing Engineering
Item ID: 71871
Depositing User: Shafique, Mr Usman
Date Deposited: 07 Jun 2024 14:16
Last Modified: 07 Jun 2024 14:16
URI: https://eprints.nottingham.ac.uk/id/eprint/71871

Actions (Archive Staff Only)

Edit View Edit View