The particulate aerosol deposition (PAD) method is a novel coating process, which has the potential to combine dissimilar ceramic, metallic and polymeric materials in multilayer or composite coating architectures. The development of improved understanding of the deposition mechanisms, influence of precursor powder characteristics and computational process modelling studies are key factors that need to be addressed to achieve widespread exploitation of PAD. The proposed project will develop a surrogate modelling approach to optimise the PAD process in real time, for use in the fabrication of electrically insulating coatings for electromagnetic motors and generators; this will enable the working temperatures of electrical machines and their resulting power density to be significantly increased, for improved efficiency.
The overall aim of the proposed research is to demonstrate the means to monitor the PAD process in real time and to adjust key process parameters to modify the deposition behaviour. This will involve conducting model simulations to describe particulate aerosol flow and the formation of ceramic coatings, coupled with systematic experiments to establish the influence of key process variables on film growth and material properties/microstructure. Subsequently, software will be developed for real-time simulation and control of the deposition process through the development of a surrogate model. Optimised ceramic coatings on metallic conductors will be evaluated in terms of dielectric strength, resistance to partial discharge and resilience to damage during thermal cycling.
This project is part of the MADSIM PhD Training Centre for PhD students at the University of Manchester, for research in mathematical modelling, big data and AI. The project involves collaboration between different departments in the University of Manchester and industrial engagement. MADSIM provides a community for PhD students with common research interests and training opportunities via internal seminars, journal reading groups, and participation in events such as modelling challenges or industrial problem solving
Applicants are expected to hold, or about to obtain, a minimum upper second class undergraduate degree (or equivalent) in Engineering, Materials Science, Physics or Applied Mathematics. Knowledge of programming methods, finite element analysis, modelling/simulation and some practical experience are essential. A Masters degree in a relevant subject, experience in fluid and solid mechanics, and experience with AnsysFluent and/or Comsol are desirable.
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