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thermodynamically. Performance design optimization and advanced performance simulation methods will be investigated, and corresponding computer software will be developed. The research will contribute
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for the collection of data to develop and validate prognostic models for filter degradation. Integrated Drive Generator (IDG) Rig: Simulates the operation of an aircraft's IDG, used to investigate fault detection
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methods in the past. A piece of comprehensive computer software, Pythia with the corresponding capabilities have been developed and tested successfully in several industrial applications. The software can
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partners, (Boeing, BAE Systems, Rolls-Royce, Meggitt, Thales, MOD and Alstom); and from EPSRC. The investment, over the first 5 years of operation, was approaching £10M. We are now in our eighth year of
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electronics, embedded programming, signal processing, vibration measurement and analysis, maintenance engineering, and electro-mechanical engineering. Funding This is a self-funded PhD. Find out more about fees
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to the Net Zero targets. In consultation with the wider CDT community, the work will also include the development of a roadmap for the maturation of the technology and the processes required to have it adopted
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, academia, government, and policy. The interview process is composed of two interviews. Following a first introductory interview (20min), a second online (or face to face if preferred) interview will be
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realistic degradation from corrosion processes. The simulations will be integrated with mesoscale experimental to evaluate the constitutive response of smooth specimens degraded by corrosion. Given
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algorithms are used that allow a computer to process large data-sets and learn patterns and behaviours, thus allowing them to respond when the same patterns are seen in new data. This include 'supervised
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this research is that it should be possible to significantly improve the performance of extreme learning and assure safe and reliable maintenance operation by integrating this prior knowledge into the learning