Thermal Barrier Coatings (TBC) are used to shield hot sections of gas turbine engines, helping to prevent the melting of metallic surfaces. TBC is a sophisticated layered system that can be divided into top coat, bond coat, and the super-alloy substrate. The highly heterogeneous microstructure of the TBC consists of defects such as pores, voids, and cracks of different sizes, which determine the coating’s final thermal and mechanical properties. The service lives of the coatings are dependent on these parameters.
These coatings act as a defensive shield to protect the substrate from oxidation and corrosion caused by elevated temperatures. Yttria Stabilized Zirconia (YSZ) is the preferred thermal barrier coating for gas turbine engine applications. There are a certain number of deposition techniques that are used to deposit the thermal coating layer on the substrate; commonly used techniques are Air Plasma Sprayed (APS) or Electron Beam Physical Vapour Deposition (EB-PVD).
The objective of this thesis is to model an optimized TBC that can be used on next-generation turbine engines. Modelling is performed to calculate the effective thermal conductivity of the YSZ coating deposited by EB-PVD by considering the effect of defects, porosities, and cracks. Bruggeman’s asymmetrical model was chosen as it can be extended for various types of porosities present in the material. The model is used as an iterative approach of a two-phase model and is extended up to a five-phase model. The results offer important information about the influence of randomly oriented defects on the overall thermal conductivity. The modelled microstructure can be fabricated with similar composition to have an enhanced thermal insulation.
The modelling results are subsequently compared with existing theories published in previous works and experiments. The modelling approach developed in this work could be used as a tool to design the porous microstructure of a coating.
Identifer | oai:union.ndltd.org:uottawa.ca/oai:ruor.uottawa.ca:10393/37035 |
Date | January 2017 |
Creators | Ghai, Ramandeep Singh |
Contributors | Baddour, Natalie |
Publisher | Université d'Ottawa / University of Ottawa |
Source Sets | Université d’Ottawa |
Language | English |
Detected Language | English |
Type | Thesis |
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