Background: I have graduated from Newcastle University with an MEng in Mechanical Engineering. For my dissertation, I had designed and manufactured a domestic scale wind turbine test rig for the purpose of determining the power characteristics of various blade designs assembled in different configurations. My placements during this time included working in the offshore industry, designing and manufacturing subsea working systems and testing equipment.
Research Interests: Harnessing the use of big data and the ability to perform analysis that can extract useful information has become a powerful tool in many industries that extends to the offshore wind industry. As a result, I have developed an interest in working on applying machine learning and artificial intelligence techniques for the purpose of component fault prediction, diagnostic or design optimisation. My other interest also includes designing and developing robotic systems that can autonomously monitor the health of wind turbine components and assemblies, diagnosing any faults if necessary.
Why you applied for the Aura CDT: The Aura CDT PhD scholarship is a perfect opportunity to fuel my interest and drive my ambition in pursuing a career in the offshore wind energy sector. This is in part due to the ability to work with and gain industrial contacts. As well as this, the opportunity to take part in a taught program allows the necessary theoretical knowledge to be gained whilst at the same time strengthening my understanding of the challenges that exist in the sector, which is ideal before undertaking a PhD.
I will be investigating Grey-box models for life-time assessment of composite wind turbine components at the University of Sheffield.
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