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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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sources compared with gas turbines, etc. The aim of this PhD research is to develop novel performance simulation capabilities to support the analysis and optimization for sCO2 power generation systems
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intelligent systems aim to optimize power usage without compromising performance, employing strategies like power-aware computing and thermal-aware optimization. These systems are crucial in extending
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FPGA/ASIC architectures that dynamically reconfigure based on AI workloads, optimizing performance, energy efficiency, and functionality. 3- Intelligent Interface Design: Create smart interfaces
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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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, and more efficient operations. After all, the greenest energy is the one that’s not spent – and this project aims to unlock just that by refining the way we design and optimize airfoils. The focus
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. Green Aviation Operations and Infrastructure. Aviation Environmental, Commercialisation & Socio-Economic Aspects. The CDT in Net Zero Aviation is the world’s first Centre of Excellence for Net Zero
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through advanced modelling and simulation. A key objective is to validate and optimize poroelastic finite element models of brain tissue, making them more accurate and clinically relevant. Additionally
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. Green Aviation Operations and Infrastructure. Aviation Environmental, Commercialisation & Socio-Economic Aspects. The CDT in Net Zero Aviation is the world’s first Centre of Excellence for Net Zero
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image velocimetry approaches. This enhanced understanding is crucial for optimizing performance, and educate the design of future architectures. Additionally, the research accelerates the design and