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will deliver a model that integrates water quality to predict PFAS behaviour in GAC filters. The model will give water companies a practical tool to forecast GAC bed life under different water qualities
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of £25,805 per year, plus additional funds of £7,000 a year for travel, conferences and research equipment. This project is co- funded by an external government partner. UAS are becoming useful tools across a
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AI techniques for damage analysis in advanced composite materials due to high velocity impacts - PhD
energy systems. The global focus on safety, predictive maintenance, and lifecycle cost reduction. The rising availability of high-fidelity NDT data and accessible machine learning tools. In summary
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