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in conjunction with the industry partner, this PhD project aims to develop a reliable numerical modelling framework capable of: (i) simulating coupled heat and fluid flow within deep geothermal
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waves still remains a challenging and important research topic, with applications ranging from modelling tsunamis, rogue waves, and ice floes to informing ship design and coastal management. The accurate
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workflows rely heavily on geometric de-featuring, an expert-driven, manual, and time-consuming process used to simplify CAD models so that meshing tools can cope with small-scale features such as fillets and
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of the vibrational energy. This project is intended to perform numerical analysis and modelling aimed at the optimisation and development of effective friction dampers. The research studies on friction damping will be
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will develop and evaluate new approaches to predicting current and future population exposure to such hazards by combining numerical modelling and remote sensing of river migration, with machine learning
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of the following: numerical methods, high-performance computing (HPC), Computational Fluid Dynamics (CFD), applied mathematics, physics, engineering or subsurface flow modelling. Enthusiasm
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necessarily require formal education in geotechnics. Applicants with a background in mechanical/materials engineering or alternatively mathematics/computer science with an interest in numerical modelling
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matrix functions. These computational problems are central to many scientific and engineering applications, including quantum mechanics, materials science, and weather/climate modelling. Numerical methods
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Fully-funded 4-year PhD Studentship (UK Home fee status): Numerical simulation of boiling flows for high heat flux fusion components Aim and Objectives This project aims to develop a high-fidelity
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). Additional project costs will also be provided. Overview We are seeking a highly motivated PhD candidate with interests and skills in computational modelling and simulations, fluid dynamics, mechanical