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We are looking for a highly motivated candidate to pursue a PhD programme titled "CFD-informed finite element analysis for thermal control in wire-arc directed energy deposition." This research
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. Working at the intersection of water engineering, environmental microbiology, robotics, and lifecycle analysis, you will evaluate autonomous underwaterskimming robots that minimise energy use and chemical
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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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simulations and finite element analysis, with high-heat flux electron beam experiments. The research will simulate and replicate steady, cyclic, and transient thermal loads to better understand PFM behaviour
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simulations for AI model validation. ✔ Artificial Intelligence (AI) & Deep Reinforcement Learning (DRL) for energy optimization ✔ Predictive Maintenance & Failure Analysis using Machine Learning and Physics
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fields, and risk damaging the part during fabrication. Finite element analysis (FEA) models, while capable of delivering detailed spatiotemporal distributions of thermal variables, suffer from limited
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should have some experience in setting up experimental trials and/or modelling. Previous experience of water quality sampling and analysis is recommended but not essential. The candidate should be self
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flow regime ranging from steady laminar to unsteady turbulent configurations, there is also potential to extend the analysis to compressible flows and structural analysis. This research is highly
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the experiment design, impact analysis and icing code droplet impact solver refinement. The main impact of the work will be to provide droplet impact data and analysis at high speeds which are closer to real-time
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high temperature corrosion rate involving mathematical models validated through simulation, experiments and analysis. Gas Turbines are used as a multipurpose power source in various applications like aviation, power