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Title: Race-track modelling and variability in RTM for advanced composites structures
Author: Koutsonas, Spiridon
ISNI:       0000 0004 5365 1106
Awarding Body: University of Nottingham
Current Institution: University of Nottingham
Date of Award: 2015
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The Resin Transfer Moulding (RTM) process is one of the most common manufacturing routes for composites. The challenge in the present work is to be able to predict the flow behaviour in order to manufacture advanced composites truss structures. To that end, there is a lack of an advanced simulation tool capable to predict void formations for the manufacture of three dimensional, multi-layer woven textile composites like the Advanced Composites Truss Structure (ACTS) generic node TSB-funded project that is presented in this thesis. Industrial experience has shown that during mould filling, due to race-tracking and stochastic variability in the material properties, the filling patterns and arising cycle times are rarely the same between a given set of apparently identical mouldings. The objectives of this thesis were 2D, 3D racetrack prediction of textile reinforcements for RTM processes and 3D variability prediction at the component scale. A model that predicts the resin rich zone along a component edge was developed for this purpose. The issue of 2D, 3D racetrack prediction was firstly investigated along a 90° edge for three different geometry, architectures and material preforms, on a generic composite node 3D. Variability was also investigated through the same CAD model with the use of the FE/CV technique. A novel numerical approach for 3D FE CAD modelling was developed in order to predict race-tracking and variability for advanced composites structures. A stochastic analysis technique was developed to account for the effect of node variability during the fabrication process by RTM. The study based on this technique provided important insights into flow filling variations, voidage formation and optimization on a generic advanced composite truss structure. The model developed from this work can be used to account for the effects of race-tracking and variability on any other composite component at the macroscale level. The predicted race-track and variability data can complement experimental data in order to enhance flow simulations at the component scale.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: TA Engineering (General). Civil engineering (General)