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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
at scale? Digital twins offer a promising foundation, but to truly support engineering decisions, they need to go beyond simulation and begin to interpret and reason about the systems they represent
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and heat transfer in geothermal systems under high-pressure and high-temperature conditions relevant to AGS. • Developing high-fidelity direct numerical simulation (DNS) models to map
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candidate will drive the development of the FSI CMF model to simulate the effect of fluid-solid coupling on the vibration of the structure. The successful candidate will work with the multidisciplinary
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explore or optimise the flexible structures and manufacturing process of Litz wires. This studentship offers the opportunity for the PhD student to lead the development of innovative simulation tools
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simulations, covering a range of typical part geometries and deposition strategies, complemented by experimental validation. • Developing an efficient method for converting partial surface temperature data
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only for up to 4 years full-time or up to a maximum of 6 years if studying on a part-time (0.5 FTE) basis How to apply: Send a copy of your CV and a 300-word statement about why you are interested in
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nonlinear effects. These nonlinear effects will be generalised via correction terms discovered by machine learning from a large numerical simulated dataset. This dataset also allows for extending the theory
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Cranfield University and Magdrive will study plume effects of Magdrive's dynamic pulsed plasma thruster on relevant targets. Simulation of plasma expansion and condensation in the space environment will be
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alongside numerical simulations relying on high-performance computing and reduced order modelling. We aim to gain new insights about the physical coherent structures which are most relevant to viscoelastic
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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