Project overview
Floating offshore wind farms rely on accurate models of the winds, waves, and currents. Prior to construction these inform design of the platforms and turbines, and throughout the wind farm's life they are necessary to plan inspection and maintenance operations. This engineering internship will assess new wave modelling methods at proposed offshore wind farm sites in the Celtic Sea. Using data collected from these sites, the intern will be responsible for extending a machine learning wave forecasting methodology beyond averaged statistical parameters to operating with spectral data, providing a more complete wave forecast that can better guide engineering decisions.
Dr Ajit Pillai is a senior lecturer in Autonomous Systems and Robotics and RAEng Research Fellowship awardee developing and deploying optimization algorithms to aid in the design of offshore renewable energy devices and arrays.
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Reece Richards is a Renewable Energy Engineering undergraduate at The University of Exeter, passionate about the global transition to green energy. Particularly fascinated by research and development within the marine and offshore wind sector, Reece is excited with the prospects that machine learning can bring to the field.
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As a mature student, Peter Jenkin is interested in sustainable industry and programming for assessment of renewables' designs.
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