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captured either by globally over refining the mesh, which is computationally expensive and environmentally inefficient, or by running multiple successive simulations to iteratively adjust the mesh. Both
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emerged to make meshing more flexible by allowing elements to span across multiple CAD faces without explicitly modifying the geometry. However, these ideas have not yet been developed in high-order
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of operating reliably under severe thermal and chemical conditions. This will involve a combination of computational modelling, system design, and experimental testing to develop and optimise the printing
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allowing elements to span across multiple CAD faces without explicitly modifying the geometry. However, these ideas have not yet been developed in high-order settings, where curved elements, geometric
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requirements. The resulting tools will support automated mesh generation and adaptation, reduce manual tuning and improve the reliability of simulations involving geometry driven behaviour across multiple
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across multiple locations. This includes enabling real-time monitoring of electrical energy generated by solar panels, stored in battery power storage systems, and utilised for charging e-bikes and e
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change, market dynamics, and daily grid variations. These factors contribute to heightened structural and control complexity, along with multiple layers of uncertainty. In this context, Hybrid Power Plants
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their operational reliability. The PhD student will combine mathematical models, in-house laboratory tests in a wind-wave-current flume (https://research.ncl.ac.uk/amh/ ) and numerical methodology to quantify
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within a BSc/MSc thesis project. · Ability to effectively and reliably coordinate with the supervisor and multiple collaborators Language skills · Good level both written and spoken
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assessment and certification framework, leveraging multiple data sources and probabilistic reliability analysis to predict both current and future safety levels. This project contributes to designing future