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My research focuses on the development of AI-based digital twins for high-speed train rolling stock asset management, promoting a circular economy. This innovative approach aims to maximise resource utilisation and reduce waste, enhancing both sustainability and efficiency in rail operations. As the rail industry moves towards more sustainable practices, effective asset management is critical for optimising performance and minimising environmental impact.
High-speed rail systems play a vital role in sustainable transport; however, they must evolve to meet increasing environmental demands. My work addresses these challenges by equipping rail operators with advanced tools that improve asset management strategies, ultimately contributing to lower greenhouse gas emissions and more responsible resource use. The application of circular economy principles will encourage the railway sector to adopt practices that are both environmentally friendly and economically viable, and I am excited to contribute to Birmingham’s initiatives in sustainable transport and clean energy.
PhD Civil Engineering student at the University of Birmingham
