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Field
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these challenges by exploring and developing advanced methodologies for wind turbine drivetrain condition monitoring. The successful candidate will primarily focus on: Signal processing techniques: Developing and
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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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data, energy yield data, condition monitoring system data, nacelle lidar data, maintenance data etc), and decommissioning. Despite the wind energy sector’s success in data collection, significant
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industries, including: Aerospace: Faster, more efficient design and real-time condition monitoring for safer aircraft and spacecraft. Civil Engineering: Real-time health monitoring for bridges and skyscrapers
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the opportunity you’ve been seeking. Join us to tackle some of the most intriguing and impactful challenges in the domain of wind energy, digitalization, and autonomous decision-making. We are looking for a
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of this position will be the investigation of meteorological phenomena impacting the wind energy sector, in particular with respect to wind resources and wind conditions. For example, investigating how large-scale
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Infrared heating heats people and surfaces directly, without heating the air in between. Thus, it is claimed that radiant heating can provide thermal comfort at lower internal air temperatures
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local gas/liquid phase conditions. Whilst direct simulations of breakup are possible, computational cost is high, restricting applications to small sections of geometry and for modest run times
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net zero aviation. This project will explore the science of novel cooling technologies, such as phase change materials and heat transfer enhancement, for the air systems used to condition the turbine
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2026. The UNFoLD lab specialises in the experimental measurements, analysis, and modelling of unsteady vortex-dominated flow phenomena, with applications in bio-inspired propulsion, wind turbine rotor