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-informed data analytics tools for the predictive maintenance (PdM) strategy applications to high-value critical assets. Among others, the recently developed Physics-informed Neural Network (PINN) technique
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) under the supervision of Dr. Elina Spyrou . Summary of Project: Power systems are at the core of the transition to net-zero energy systems, and they have to transform in two ways. First, their generation
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critical to ensuring the longevity and safety of fusion reactors. This PhD project focuses on developing an integrated framework that combines cutting-edge computational models, including Monte Carlo
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requirements. Build appropriate networks within the team. See full advert for full information. Education, qualifications and experience Essential MSc degree in a relevant discipline to the project: social
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of Science and Technology (proud member of the Alan Turing University Network) and be supervised by leading experts in machine learning for healthcare. You will also be affiliated to the School of Health
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demonstrate the utility of an adaptive mesh refinement approach in interface resolving Computational Fluid Dynamics (CFD) simulations of flow boiling at conditions relevant to nuclear thermal hydraulics
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: this provides capability for accurate and fast modelling of urban drainage, handling the full complexity of flow paths on impermeable surfaces, green space, buildings, pipe networks and BGI features
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complimentary computational studies to predict the intake aerodynamic characteristics and aid in the experiment design. This position is part of the CDT in Net Zero Aviation, which offers a modular, cohort-based
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net zero aviation. This project will explore the science of novel cooling technologies, such as phase change materials and heat transfer enhancement, for the air systems used to condition the turbine
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work on the INSTINCT-MB programme, which brings together teams based at Newcastle University, The Institute of Cancer Research and University College London. The programme will generate a wide range of