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Field
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Computational Fluid Dynamics (CFD) to diagnose the air quality status of those spaces (presence of pollutants, ventilation, humidity) and to propose measures to improve it. Such measures might imply retrofitting
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these robots utilise electronic, chemical, pressure, magnetic, or thermal mechanisms, with the current generation having significant drawbacks, including low energy efficiency, high operating voltage
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join a vibrant, supportive research community (around 20-25 people involved in fluids modelling research). Collaborate with the Leonardo Centre for Tribology: Work with top researchers on experimental
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hypothesis of the proposed research is by use of intelligent and integrated control of the input power electronics, fluid handling, and thermal control in a holistic approach, current efficiency and lifespan
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Current modelling and simulations require either generic assumptions to be made for fluid dynamic based modelling leading to inaccuracies between modelled and experimental data or, intense
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are invited for a full-time Research Assistantship for a period of six months. This project focuses on reducing aerofoil broadband noise, specifically turbulence–leading edge interaction noise and trailing edge
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We are seeking a highly creative and motivated Postdoctoral Research Assistant/Associate to join the Machine Learning Group in the Department of Engineering, University of Cambridge, UK. This
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, in collaboration with Rolls-Royce, will develop novel regenerative pumps to address LH2 pumping requirements in multi-phase flows without flow – speed restrictions through design development
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accuracy is still limited. In contrast, computational fluid dynamics (CFD) models can capture the arc physics and molten pool dynamics, including arc energy transfer and liquid metal convection within
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an underlying foil structure which acts as a supporting spring. This project concerns journal AFBs and associated nonlinear vibration issues. As with all fluid bearings, rotor systems fitted with journal AFBs