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? Mechanical seals are critical components in high-pressure storage solutions for hydrogen and carbon capture technologies. In this project, you will: Develop a 3D Digital Model: Create an advanced computational
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combining high-fidelity computational modelling with artificial intelligence to overcome key barriers in performance. The investigation will focus on optimising core gas exchange and combustion processes
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challenging properties of uncertainty, irregularity and mixed-modality. It will examine a range of models and techniques that go beyond Markovian approaches, including state-space models, tensor networks, and
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mixed-modality. It will examine a range of models and techniques that go beyond Markovian approaches, including state-space models, tensor networks, and machine learning frameworks such as recurrent
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needs. While muscle imaging from well-characterised patients and transcriptomic technologies provide rich data, these remain under-utilised for predictive modelling. Using machine learning, this project
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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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Project Description: Within aircraft jet engines, high-pressure turbine (HPT) blades are exposed to combustion gases requiring complex cooling strategies. Prediction of turbine heat transfer is
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EPSRC iCASE PhD studentship with SLB - Computational modelling of advanced geothermal systems School of Mechanical, Aerospace and Civil Engineering PhD Research Project Directly Funded UK Students
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there are concerns about the new impacts that this will introduce. Battery electric vehicles (BEVs) typically require six times as many minerals as their internal combustion engine (ICE) counterparts, and thus a
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rate). Overview Hydrogen combustion offers a lower environmental impact and higher energy efficiency than traditional fossil fuels, with applications in aerospace as well as power generation sectors