Predictive emission monitoring system for gas turbine

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In the first year the student will work on developing a solid understanding of core principles governing the operations of gas turbines and how data-driven models that use machine learning approaches can be used in the context of this problem. In the second year, the student will consider established physical models of gas turbine operations and how novel approaches can be developed to leverage the vast amount of gas turbine operational data that combined can provide accurate predictions of emissions. In the third year the investigations will focus on developing novel and generalisable machine learning approaches that can extract good representations, which coupled with physical models can provide accurate predictions across different real-life settings. In the fourth year, the student will carry on extensive validation experiments across a few gas-turbine models, whilst also writing-up the PhD thesis (last six months).