Kaloedes, D, 1997. Evaluation of fibres and transverse composites using advanced acoustic emission signal processing. MPhil, Nottingham Trent University.
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Abstract
Acoustic Emission (AE) has been established during recent years as a convenient method for determining the fracture characteristics of both transverse fibre-reinforced composite materials (TFRC) and fibre bundles under tensile testing. Degradation of these materials is by propagation of a range of defects which ultimately control failure. AE events were easily detected and distinguished from each other by either relative Peak amplitude (AMP) or ringdown counts (RDC) using simple piezoelectric transducers as detectors and advanced signal processing. Stress-strain data were also simultaneously recorded and then correlated to AE data.
For the first part of this investigation an AE technique has been employed to deduce information regarding the level of adhesion and the strength of the bond between glass or Kevlar fibres and polyester resin matrix. Composites provide a strong, lightweight material suitable for engineering applications. Since composite materials used for engineering applications are manufactured by cross-ply methods, transverse failure is an important damage mechanism in controlling the initiation of damage in a complete composite. Different treatments such as post-curing of the composite material and ultrasound treatment of the Kevlar fibres, with the specimen subjected to transverse tension, showed different characteristics for the interfacial strength and the associated AE events. The pattern of AE indicates the fact that resin toughness has increased due to post-cure. The severity of these AE events was examined although this measure was not conclusive in identifying differences in AE data due to different source mechanisms. Weibull plots derived from the composite tensile test involving AE data, were also employed. This particular application of the statistics does not bear a fundamental relationship to the microscopic damage mechanisms and was applied in an empirical way. The AE related Weibull parameters proved sensitive to material condition, due to cure, post cure and resin-fibre adhesion modification. Pattern Recognition was also considered with regard to quantification and identification of damage.
For the second part of this investigation, AE has been used in order to monitor the strength of glass and carbon fibres bundles under tension. Generally, when testing materials using AE, the relationship between the source excitation and the detected stress wave is complex. The mode of failure in this case was mainly one kind (fracture transverse to the fibre axis). Bundles of different types have been strained to failure in order to investigate the relationship between AE data and fibre strength. Where appropriate the statistical distribution of mechanical failure was characterised using three different statistical techniques. By using mainly the AE ringdown counts, these methods have been able to predict the behaviour of such bundles under tension and therefore describe their strength distribution. Two parameter Weibull distribution function , two parameter lognormal function and quantile distribution function provided the means for characterising the failure of these bundles. AE has proved useful in monitoring the exact time and load of fibre breaks, since the breaking of each individual fibre is accompanied by an associated AE signal.
Generally the AE data were used to study aspects of material failure. The analysis techniques based on AE, proved effective, bearing in mind the relative uncertainties during manufacturing and testing processes. AE has proved an effective method of monitoring composite failure and fibre fracture. The results allow transverse composite and fibre bundle failure to be characterised using various statistical approaches. The simplicity of the instrumentation establishes AE as a useful technique with broad application to materials characterisation having a number of advantages over both conventional ultrasonic and radiographic methods.
Item Type: | Thesis |
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Creators: | Kaloedes, D. |
Date: | 1997 |
ISBN: | 9781369325263 |
Identifiers: | Number Type PQ10290277 Other |
Divisions: | Schools > School of Science and Technology |
Record created by: | Linda Sullivan |
Date Added: | 24 Jun 2021 15:53 |
Last Modified: | 15 Nov 2023 15:52 |
URI: | https://irep.ntu.ac.uk/id/eprint/43221 |
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