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and controlling defects and lay the foundation for a thermal physics-based approach to process qualification. Additive manufacturing (AM) is a rapidly evolving technology that continues to drive
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, ultimately optimising the deposition process. Additive manufacturing (AM) is a rapidly advancing technology, driving numerous innovations and finding diverse applications across industries such as aerospace
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This PhD project will focus on developing, evaluating, and demonstrating a framework of novel hybrid prognostics solution for selected system use case (e.g. clogging filter, linear actuator, lithium
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multitude of disciplines. As this technology becomes more prevalent, understanding the forensic fingerprints of these systems after a damage causing incident is critical to both investigators and engineers in
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-efficient research that prevents fatigue failures has pushed towards integrated computational materials engineering approaches that improve competitiveness. These approaches rely on physics-based models
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cost-effectiveness of forever chemicals removal from water. The model will use experimental data gathered during the project through testing. The successful candidate will work closely with the project
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. It will use signals from different sources—such as radio signals and internal sensors— to maintain robust and accurate PNT, even when satellite signals are weak or missing. A built-in intelligent
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knowledge co-evolution and addressing complex challenges in a super-intelligent society. This project is situated within the rapidly evolving field of Cyber-Physical-Social Systems (CPSS), which is of
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of representative failure models for gear failures causes difficulties in their useful lifetime prediction. Critical operational parameters such as loading, speed and lubrication affect the physics of gear meshing
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Verification Tools: Develop AI algorithms that automate the verification process, ensuring systems meet required safety and performance standards. Health Monitoring Algorithms: Implement AI-based monitoring