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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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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
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applied research, the IVHM 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
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advanced simulation methods, including Reynolds-Averaged Navier-Stokes (RANS), Direct Numerical Simulations (DNS), and/or Large Eddy Simulations (LES), will be employed to accurately model the complex flow
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-on experience with real-world SCADA data, industry collaboration with RES Group, and training in high-fidelity simulation environments (OpenFAST, Digital Twin technology). This opportunity is ideal for those
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AI-Driven Digital Twin for Predictive Maintenance in Aerospace – In Partnership with Rolls-Royce PhD
at scale? Digital twins offer a promising foundation, but to truly support engineering decisions, they need to go beyond simulation and begin to interpret and reason about the systems they represent
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simulations, covering a range of typical part geometries and deposition strategies, complemented by experimental validation. • Developing an efficient method for converting partial surface temperature data
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Cranfield University and Magdrive will study plume effects of Magdrive's dynamic pulsed plasma thruster on relevant targets. Simulation of plasma expansion and condensation in the space environment will be
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. The project is co-sponsored by Spirent Communications, a world leader in navigation and testing technology. Spirent will provide advanced simulation tools, expert support, and industry placements to help make
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simulating fluid networks and dynamic phenomena for assessing different solutions is a necessity The overall aim of this project is to improve the confidence in fuel system design process for ultra-efficient