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the manufacturing process. The embedded optical fibre sensing will be used in conjunction with advanced numerical models for monitoring of composites manufacturing and structural performance. Motivation High
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chemical processes, such as artificial photosynthesis. It relies on the combination of bulk photophysical processes and surface chemical processes within complex composite nanostructures, the interplay
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continuous-fibre-reinforced polymers (composites) under monotonic and cyclic loading, in particular using acoustic emission and thermography. Derivation of service life models for composites. Involvement in
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to small batches. This PhD will pioneer the transition from laboratory-scale demonstrations to scalable, manufacturable acoustic structuring of polymers, representing a step change in composite processing
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(matrix, advanced, and composite) and data export. Experience with Workday security model and Business Objects. Experience with Workday HCM/FIN and/or Student. And/or Demonstrated experience with Workday
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Do you have a strong technical background in Machine Learning and Numerical Modelling? Are you interested in working with industry to develop Machine Learning methodologies and protocols needed
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activities: · Understanding/simulating the diffusion paths and cavitation in thermoplastic liners. · Multi-physics simulation of the diffusion process in thermoplastic orthotropic composites
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This project focuses on understanding and modelling interfaces in multifunctional composite structures that combine mechanical load-bearing capacity with energy storage. You will study how electrochemical
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of PAEK (Polyaryletherketone) and PEKK (Polyetherketoneketone) polymers, and their composites with carbon fibre, using the CFAM platform. Forming Process Optimisation: Systematically exploring and
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This project focuses on understanding and modelling interfaces in multifunctional composite structures that combine mechanical load-bearing capacity with energy storage. You will study how electrochemical