A dissertation submitted to the Faculty of Engineering and the Built
Environment, University of the Witwatersrand, in fulfilment of the
requirements for the degree of Master of Science in Engineering
25 May 2017 / Two of the main contributors to high voltage insulation failure are thermal and
electrical stresses. The failures may be mitigated by using nanodielectrics. The
enhanced effect of nanoparticles in nanodielectrics is attributed to an interaction
zone/interphase around each individual nanoparticle between the nanoparticle and host
polymer. However, particle clumping or agglomerates are a major challenge in
nanodielectric technology. In this work mitigation of the clumping challenges was
explored through Rheology in determining optimal particle loading levels. The
nanodielectrics studies were Boron Nitride and Carbon Nanospheres in Araldite Epoxy.
The rheology results indicated an optimal loading level of 1.09 vol % to 1.35 vol% for
Boron Nitride in Epoxy and 0.33 vol% for Carbon Nanospheres in Epoxy. Microscopy,
dielectric spectroscopy, electrical tree characterisation, thermal expansion and laser
flash analysis were used to validate the efficacy of the rheology results. The results
indicated improved properties of the resultant dielectric such as; increased mechanical
stiffness, increased electrical resistance and the percolation threshold, partial discharge
suppression and increased thermal conductivity at the glass transition temperature. This
study has established a rheology-based technique incorporated in the manufacturing
process to determine the optimal filler loading of C/Epoxy and BN/Epoxy
nanodielectrics. Future work is recommended as investigating either new particle types
such as Sulphur hexafluoride in Carbon Nanospheres or mixtures of Carbon
Nanospheres and Boron Nitiride. / MT 2017
Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:wits/oai:wiredspace.wits.ac.za:10539/23454 |
Date | January 2017 |
Creators | Hank, Andrew Marvin |
Source Sets | South African National ETD Portal |
Language | English |
Detected Language | English |
Type | Thesis |
Format | Online resource (xxvi, 192 leaves), application/pdf, application/pdf |
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