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Aviation by 2050. This exciting doctoral project, in collaboration with Rolls-Royce, will develop innovative computer vision methods which when combined with optical flow velocimetry will enable imaging
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on Artificial Intelligence (AI), Deep Reinforcement Learning (DRL), and Predictive Maintenance for optimizing wind turbine performance and reliability. This research will develop an AI-powered wind turbine
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learning, this research contributes to the growing field of digital healthcare, which aims to enhance clinical decision-making and improve patient outcomes. The primary focus of the project is to develop and
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This PhD project will focus on developing, evaluating, and demonstrating a framework of novel hybrid prognostics solution for selected system use case (e.g. clogging filter, linear actuator, lithium
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computational and experimental fluid dynamics in addition to product development. This project falls within the field of fluid dynamics, a discipline central to improving the efficiency of systems that involve
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, in collaboration with Rolls-Royce, will develop novel regenerative pumps to address LH2 pumping requirements in multi-phase flows without flow – speed restrictions through design development
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to identify the material degradation and coatings applications details in extreme environments. A novel techniques/method will be developed with focus on better prediction and more accurate measurement of
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expertise. We link fundamental materials research with manufacturing to develop novel technologies and improve the science base of manufacturing research. The Through-life Engineering Services (TES) Centre
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expertise. We link fundamental materials research with manufacturing to develop novel technologies and improve the science base of manufacturing research. The Through-life Engineering Services (TES) Centre
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University provides an ideal setting for this research, offering a wealth of resources and expertise in engineering and digital technologies. The expected outcome of the project is the development of novel