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Title: Damage characterisation of 3D woven glass-fibre reinforced composites under fatigue loading using X-ray computed tomography
Author: Yu, Bo
ISNI:       0000 0004 5369 4341
Awarding Body: University of Manchester
Current Institution: University of Manchester
Date of Award: 2015
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In the advanced polymer composites reinforced by 3D woven fibre architectures, tows areinterlaced into through-thickness direction to overcome the problems encountered in theapplications of traditional 2D laminates, such as poor interlaminar toughness anddelamination resistance. The understanding of the influence of fibre architectures on thefatigue performance of 3D woven composites is essential in providing guide for the designof fibre architecture. This PhD project is an in-depth study into the fatigue damagemechanisms of 3D woven composites reinforced by two kinds of fibre architectures,namely, 3D modified layer-to-layer (MLL) and 3D angle-interlocked (AI). 3D X-raycomputed tomography (CT) has been used as the main tool to non-destructively evaluateand quantify the evolution of fatigue damage, with an attempt to link macro behaviour withlocal micro (damage) microstructure. Part I is focused on a post-failure study on both typesof materials to identify their respective failure mechanism, using the combination of 2D(optical surface and SEM cross-sectional) imaging and 3D (X-ray CT) imaging. Somecharacteristic features are found in both materials: firstly, fatigue damage progresses by theinitiation of transverse cracks within weft yarns and subsequent propagation as interfacialdebonding crack until the catastrophic failure occurs in a localised area; secondly, bothmaterials display a high resistance to ultimate failure. However, a distinctive damage modeobserved in MLL composites is the extensive development of debonding cracks, whichresult in larger scale of damage (~10μm) than those in AI composites (1-2 μm). Part IIpresents an investigation of evolution of fatigue damage in 3D woven MLL compositesfollowed by an X-ray time-lapse experiment. An innovative algorithm was developed toenable automatic classification of damage, providing insight into the competition andinteraction of different damage modes. Fatigue damage is regularly distributed throughoutfatigue life, with a geometrical dependency on the repeating unit cells. Damageinteractions have been identified, indicating a high level of damage tolerance. Aquantitative analysis has been carried out to examine and compare the growth of differenttypes of damage as a function of fatigue cycles. Transverse cracks initiate at almost thebeginning the fatigue life (0.1%) and govern the growth of weft/binder debonds, but don’tcompromise fatigue life, whereas interply debonds have a large growth towards the end offatigue life and facilitate the ultimate failure. Other types of damage occurring in the resinhave a trivial effect on the fatigue life. Part III carries out a systematic study to find out thebest approach to detect the fatigue damage in the 3D AI composites. Different strategieshave been employed in each scan, including imaging the cracks with the load applied, withcontrast enhanced by phases contrast and staining. The image contrast was not effectivelyenhanced by applying phase contrast imaging, but significantly improved by staining. Withthe application of in-situ loading, the visibility of transverse cracks is highly improved,while longitudinal debonding cracks still cannot be resolved. Overall, the best approachwas found to be high resolution ROI (region of interest) scanning in combination withstaining, in terms of practical feasibility, scan time and image quality.
Supervisor: Withers, Philip Sponsor: University of Manchester ; China Scholarship Council
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Fatigue ; X-ray computed tomography ; 3D woven composite