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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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operation of autonomous systems in complex, real-world conditions. This PhD project aims to develop resilient Position, Navigation and Timing (PNT) systems for autonomous transport, addressing a critical
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. The integration of AI into hardware not only enhances performance but also reduces energy consumption, addressing the growing demand for sustainable and efficient computing solutions. This PhD project delves
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. Understanding the process of droplet impact and freezing dynamics at high airspeeds, on textured and non-textured surfaces is critical to deciphering the physics behind ice adhesion and accretion. Previous work
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temperatures in modern Gas Turbines. During the operation of gas turbines, such high temperatures are coupled with the impurities or ash compounds like Sulphur, halides, sodium and vanadium. In certain cases
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. The rapidly growing space satellite industry will need novel high-performance materials for superior space debris impact resistance. Our novel composites materials developed in this project will
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and brain tissue mechanics to improve stroke treatment. Stroke is a leading cause of death and disability worldwide, making advancements in its diagnosis and treatment highly relevant. Computational
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novel methodology for designing and assessing highly integrated fuel systems for ultra-efficient propulsion systems fuelled by SAF. The assessment will be done in terms of performance, operation and
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for determining engine performance and can have a notable impact on engine and in-flight testing which are central to the development of future NetZero propulsion systems. You’ll join the wider CDT
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will use advanced unsteady computational fluid dynamic methods for the analysis of coupled intake/fan configurations in crosswind and high-incidence conditions. The research will adopt these methods