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temperature within the engine environment. The aim of the proposed research is to develop modern primary atomisation models which better capture the atomisation physics associated with modern aerospace airblast
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-assurance positioning in safety-critical applications. Cranfield is a specialist postgraduate university that is a global leader for education and transformational research in technology, management, defence
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
engineers detect faults earlier, track system degradation, and make better-informed maintenance decisions. But how can we turn this complex information into something reliable, explainable, and actionable
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industries, including: Aerospace: Faster, more efficient design and real-time condition monitoring for safer aircraft and spacecraft. Civil Engineering: Real-time health monitoring for bridges and skyscrapers
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sustainable engineering strategies to boost their performance to deliver benefits for the environment and society. The outputs of this work will support practitioners in making informed investment decisions
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to an imperfect combustion in engines) and those emitted outside the exhaust (linked to the abrasion of tyres and the wear of brakes). The dynamics of exhaust and non-exhaust pollutants released into the atmosphere
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computing. Current challenges in quantum technology adoption stem from the lack of standardized benchmarking methods and the inherent difficulty in validating quantum devices beyond classical simulation
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this testbed available to users for testing hardware and applications. NPL will lead on the testing and security evaluation of the testbed and collaborate widely on the technology development. The student’s
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We are seeking one enthusiastic and motivated individual to work within the Zero-G AstroLab, School of Engineering, on a project funded by the UK Research and Innovation (UKRI) in planetary defence
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Application deadline: All year round Research theme: Systems and Control How to apply: uom.link/pgr-apply-2425 This 3.5 year PhD project is funded by The School of Engineering and is available