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Research theme: Fluid Mechanics, Machine Learning, Ocean Waves, Ocean Environment, Renewable Energy, Nonlinear Systems How to apply: How many positions: 1 Funding will cover UK tuition fees and tax
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Fully-funded PhD Studentship: Adaptive Mesh Refinement for More Efficient Predictions of Wall Boiling Bubble Dynamics This exciting opportunity is based within the Fluids and Thermal Engineering
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overcomes the geographic limitations of conventional systems, enabling global scalability and accessibility. Using advanced computational fluid dynamics (CFD) approaches, the project is aimed at advancing
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research team. Good knowledge and experience in heat and mass transfer is essential and proficiency in the use of Computational Fluid Dynamics will be considered an advantage. The student will benefit from
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fluid or as individual particles; moreover, complex chemical reactions can occur between species in the plasma. Modelling a plasma is accordingly a very complex and challenging task. The objective
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Current modelling and simulations require either generic assumptions to be made for fluid dynamic based modelling leading to inaccuracies between modelled and experimental data or, intense
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nanosheets, nanotubes, etc) or hybrid (e.g. boron carbon nitride). Similarly, while water is the most studied coolant liquid, realistic applications involve dielectric fluids (e.g. benzene, pentane). Molecular
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hypothesis of the proposed research is by use of intelligent and integrated control of the input power electronics, fluid handling, and thermal control in a holistic approach, current efficiency and lifespan
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analytical models, then informing a refined acoustic model taking both into account with data-driven approaches. This research is inherently multidisciplinary, lying at the interface of fluid and solid
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fluid dynamics (CFD) simulations, Finite Element Analysis, manage and execute the procurement of the build, run the aerothermal testing and process and communicate the results. The skills, qualifications