Nuclear fusion as an energy source has the potential to meet our growing demand for a sustainable and green alternative to fossil fuels. While research into fusion energy is an exciting new phase, with the development and construction of test reactors such as STEP in the UK (https://step.ukaea.uk), significant hurdles towards achieving commercial energy production remain.
Particularly challenging is the design of near plasma-facing reactor components. which will experience extreme operating conditions such as high temperatures and irradiation. Currently, liquid metal breeding blanket designs are being developed for use in prototype fusion reactors due to their potential for higher thermal efficiencies. However, magneto-thermo-hydrodynamic (MTHD) interactions occur when the electrically conducting liquid breeder flows in the strong magnetic field that confines the fusion plasma, resulting in increased pressure losses and significant anisotropy of flow distribution. Understanding and predicting these effects is critical for the feasibility and design of liquid metal breeding blanket systems.
In this project, a recently developed MTHD solver for heterogeneous systems with strong property contrast will be extended to fusion applications to provide a high-fidelity simulation assessment of MTHD effects on unsteady flow and heat transfer. Specifically, the effect of property gradients (property jump across liquid-wall boundary as well as temperature dependent property gradients within the liquid), buoyancy-driven convection and time varying magnetic fields will be investigated. This knowledge can provide higher confidence design MTHD guidelines that support a preliminary estimate of MTHD effects in a blanket concept, in terms of pressure drop and flow distribution.
We are seeking an enthusiastic candidate with an interest in computational modelling to join our research team. The project will benefit from affiliation with the Dalton Nuclear Institute and the Henry Royce Institute at the University of Manchester, and from the professional guidance and the significant expertise of leading industrial consultants.
Academic background of candidates
Applicants are expected to hold, or about to obtain, a minimum upper second class undergraduate degree (or equivalent) in applied mathematics, physics, mechanical engineering or a related subject.
At the University of Manchester, we pride ourselves on our commitment to fairness, inclusion and respect in everything we do. We welcome applications from people of all backgrounds and identities and encourage you to bring your whole self to work and study. We will ensure that your application is given full consideration without regard to your race, religion, gender, gender identity or expression, sexual orientation, nationality, disability, age, marital or pregnancy status, or socioeconomic background. All PhD places will be awarded on the basis of merit.