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Field
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Fuel Rig with Five Degradation Faults: Simulates various degradation scenarios in unmanned aerial vehicle (UAV) fuel systems, enabling research into fault detection, isolation, and prognostics. Machine
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Degradation Faults: Simulates various degradation scenarios in unmanned aerial vehicle (UAV) fuel systems, enabling research into fault detection, isolation, and prognostics. Machine Fault Simulator
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suite of specialised facilities: UAV Fuel Rig with Five Degradation Faults: Simulates various degradation scenarios in unmanned aerial vehicle (UAV) fuel systems, enabling research into fault detection
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, thesis) Copy of Bachelor’s degree and overview of grades (e.g. ‘Transcript of Records’) Copy of Master’s degree and overview of grades Contact details of 2-3 referees who are familiar with your scientific
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MRI, echocardiography, and CT. Another promising approach is the use of cardiac digital twins—mathematical models that simulate a patient’s heart to allow the design and in silico testing of novel
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MRI, echocardiography, and CT. Another promising approach is the use of cardiac digital twins—mathematical models that simulate a patient’s heart to allow the design and in silico testing of novel
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response timelines. Building on this foundation, the project will apply scenario modelling and simulation techniques to investigate emergency event propagation, routing strategies, vehicle-task assignment
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Centre offers access to a suite of specialised facilities: UAV Fuel Rig with Five Degradation Faults: Simulates various degradation scenarios in unmanned aerial vehicle (UAV) fuel systems, enabling
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: Computational Modelling: Employing simulation tools (e.g., GEANT4, light transport) to explore novel metamaterial designs, predict performance, and optimise key parameters such as timing resolution, light yield
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the molten pool. However, these models are computationally intensive and impractical for widespread simulations of large-scale part deposition. This project aims to develop a novel FEA-based approach