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Field
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Modern numerical simulation of spray break-up for gas turbine atomisation applications relies heavily upon the use of primary atomisation models, which predict drop size and position based upon
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evaluation, policy advocacy, or better understanding the contexts and causes of such abuse. The student will use advanced data science and applied statistics to enable combined analysis of different modes
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harness advanced techniques such as machine learning, optimization algorithms, and sensitivity analysis to automate and enhance the mode selection process. The result will be a scalable methodology that
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Supervisory Team: Prof Neil Sandham PhD Supervisor: Neil Sandham Project description: This project is focused on scale-resolving simulations (large-eddy and direct numerical simulation) combined
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, robust/distributed control, data-driven identification/control, numerical optimisation. Strong programming skills in at least two of the following: Julia, MATLAB, C/C++, Python. Demonstrated ability
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to enhance the UK’s energy system resilience through a whole-system analysis approach. Building on the proven WeSIM model, RENEW will upgrade its capabilities to incorporate electrified district heating and
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targets the development of advanced coatings to prevent cell-to-cell propagation during runaway events. It combines experimental studies, numerical modelling, and real-world burner rig testing, culminating
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The Project: Are you passionate about materials science, numerical modelling and materials characterisation techniques? Do you want to work on cutting-edge research that will directly impact nuclear
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research. The student will gain valuable insight into AQP folding and trafficking mechanisms using a range of techniques. Lipidomic analysis will provide understanding of how the membrane environment
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cyclic loading, varied surface conditions, and exposure to gaseous impurities, and advanced numerical modelling (Finite Element Analysis), this project aims to significantly enhance our understanding