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Thermal Modelling for Next Generation Additive Manufacturing

Department of Mechanical Engineering

About the Project

Combining Additive Manufacturing and thermal modelling expertise in University of Sheffield Department of Mechanical Engineering to take advanced Additive Manufacturing processes to the next level.

Here at the University of Sheffield we have a strong reputation for pushing the boundaries of Additive Manufacturing (AM), and this is an exciting opportunity to join our team of researchers in this area.

AM (often referred to as 3D printing) techniques have made impressive advances since their early use for producing prototypes, but challenges remain in terms of part quality and repeatability. We believe we can push these technologies further, but that to do so we must better understand the intricacies of the processes themselves.

This project will focus on the newly-commercialised High Speed Sintering (HSS) process, in which consecutive layers of polymer powders are melted into the required cross-section through a combination of infra-red energy and an infra-red absorbent ink.

As this is a thermal process, variations in part temperature can affect the properties of the resultant parts. In particular, where the cross-sectional area of a part changes significantly between one layer and the next, the homogeneity of the resultant part can be negatively affected.

During your PhD you will develop a thermal model of the HSS process, allowing us to understand the effects of such geometry variations and to use your model to optimise component design and/or build layout.

Expertise in thermal modelling (e.g. prescribed temperature boundaries, heat flux density at interfaces, convective surface conditions) exists at Sheffield but has not yet been applied to AM.

A core aspect of this PhD research is adapting and transferring this knowledge to the AM field, and discovering its strengths and limitations for improving AM structures built using HSS. The Boundary Element computational modelling approach is expected to be central to this aspect of the research, and newly introduced servers are available to undertake this aspect of the project.

Combining the modelling with experimentation using the HSS facilities provides a strong route for improving HSS build quality through validated predictive modelling.

Funding Notes

1st or 2:1 degree in Engineering, Materials Science, Physics, Chemistry, Applied Mathematics, or other Relevant Discipline.

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