Background: I graduated from the University of Hull in 2020 with an integrated Masters degree in Physics. My final year MPhys project entailed memristor circuit design and modelling for low power electronics and artificial intelligence computing applications.
Research Interests: My research interests include improving the power output of current renewable energy sources and designing new low power options to help reduce waste.
Why you applied for the Aura CDT: I applied to the Aura CDT as I have very strong ambitions to be a researcher in the renewable energy sector. I enjoy research and am very interested in doing research that makes a difference, especially in such a vital area that has impact on climate change. I believe that an Aura CDT studentship is my best opportunity to gain the skills and training I require to achieve my career ambitions. In addition, I would be actively contributing to finding and developing new solutions that help the environment.
My project is concerning the operation and maintenance of the blades of a wind turbine. This will involve the design and concept of novel low powered high-performance neuromorphic circuits for aiding wind turbine blade monitoring. This will be done using a relatively new circuit element called a memristor to act as a synapse in a neural network that will be able to take input signals from sensors on the turbine blade and make a prediction as to when the blade will encounter a fault such that predictive maintenance can be performed, reducing the cost of operation.
The operation and maintenance are a large expense in the life of a wind turbine, and so making accurate predictions to when a blade will fault can lead to significant savings, reducing the costs for a wind farm and brining the cost of electricity down.
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