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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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, enabling early detection of damage. Renewable Energy: Rapid, optimized design of wind turbine blades and structures for greener energy. Microstructures: Accurate, efficient analysis of devices like MEMS
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within the University. The activity spans across land, off-shore, marine, air and space power and propulsion applications, with a particular specialisation in gas turbine engineering. This exciting project
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for the next generation of thermal barrier coatings (TBCs) for aero-engines. The PhD Project Advanced TBCs are used in critical aeroengine components (e.g., Ni superalloy turbine blades) to ensure a reliable and
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2026. The UNFoLD lab specialises in the experimental measurements, analysis, and modelling of unsteady vortex-dominated flow phenomena, with applications in bio-inspired propulsion, wind turbine rotor
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., Ni superalloy turbine blades) to ensure a reliable and highly efficient operation. TBCs are crucial to ensure the safe and high-performance operation of such critical parts under extreme temperatures
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for next-generation gas turbines. These geometries pose manufacturing challenges, particularly regarding heat transfer, microstructure evolution, and defect prevention. Building on recent doctoral research
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type of non-grouted rock anchor for use with floating offshore wind turbines. The successful candidates will join a vibrant research group at Trinity College Dublin, working at the cutting edge
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control laws into Trent gas turbine engines and developed algorithms monitoring fleets of 100s of engines flying all around the world. During the PhD, you will have the opportunity to deeply engage with
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This project focuses on reducing aerofoil broadband noise, specifically turbulence–leading edge interaction noise and trailing edge self-noise, commonly encountered in aero-engines, wind turbines