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limitations in both measurement and modelling techniques. Current in-process measurement methods are restricted to surface-only monitoring devices (e.g., cameras and pyrometers), which fail to capture
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flow visualisation and measurement techniques to study droplet impact under icing conditions to improve icing codes that aid in design and development of ice detection and mitigation system
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that facilitate seamless integration between AI hardware components and embedded systems, ensuring efficient data flow and processing. Cranfield University offers a distinctive research environment renowned for its
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
expertise, access to real-world data, and a clear pathway for the industrial application of research outcomes, ensuring strong alignment with current and future industry needs. A major challenge facing
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maintenance. However, current technologies are relatively slow and not capable enough to provide quick performance, diagnostic and prognostic predictions for real time applications. With the rapid development
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the Project element or equivalent with a minimum 60% overall module average. the potential to engage in innovative research and to complete the PhD within a three-year period of study. a minimum of English
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, these systems serve as complex functional approximators trained over an input-output data set. ‘Second Wave AI’ is the term used to describe the current glut of 'machine learning' style intelligence, where