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Title: Fibre orientation and breakage in glass fibre reinforced polymer composite systems : experimental validation of models for injection mouldings : validation of short and long fibre prediction models within Autodesk Simulation Moldflow Insight 2014
Author: Parveen, Bushra
ISNI:       0000 0004 7227 1352
Awarding Body: University of Bradford
Current Institution: University of Bradford
Date of Award: 2014
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End-gated and centre gated mouldings have been assessed with varying thickness and sprue geometries for the centre gate. Alternative image analysis techniques are used to measure the orientation and length of injection moulded short and long fibres composite components. The fibre orientation distribution (FOD) measurements for both geometries have been taken along the flow path. In shear flow the FOD changes along the flow path, however the FOD remains relatively constant during expansion flow. The core width and FOD at the skin within a long glass fibre (LGF) specimen is different in comparison to a short glass fibre (SGF) specimen. Fibre length measurements have been taken from the extrudate, sprue and 2 positions within the centre gate cavity. The size of the sprue has little influence on fibre breakage if the moulding is more than 1 mm thick The SGF FOD prediction models within Autodesk Simulation Moldflow Insight 2014 (ASMI) have been validated against measured SGF data. At present, by default, the models over-predict the < cos2θ > for most geometries. When the coefficients are tailored for each model, drastic improvements are seen in the FOD prediction. The recently developed SGF RSC model accurately predicts the FOD in shear, in a thin geometry, whereas the Folgar-Tucker model predicts the FOD accurately in expansion flow. The measured LGF fibre length distribution (FLD) and FOD have been validated against the LGF prediction models. The LGF models are currently under predicting the breakage and over-predicting < cos2θ >. The breakage prediction improves if measured FLD of the extrudate is input into the model.
Supervisor: Not available Sponsor: Autodesk Ltd
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Fibre ; Orientation ; Length ; Prediction ; Modelling ; Moldflow ; Long fibre ; Short fibre ; Injection moulding ; Glass fibre ; Reinforced polymer composite systems