Arnab Hazra

PhD thesis

Computational simulation of zero-carbon fuel-air reacting flows using machine learning frameworks

The proposed research aims to accelerate the adoption of zero-carbon fuels for cleaner power generation. I plan to develop high-fidelity computational simulations of turbulent reacting flows by integrating established physics-based methods with suitable machine-learning frameworks. It aims to identify promising approaches from published research and improve their predictive accuracy, numerical robustness, and computational efficiency. These methods will be validated against well-characterised experimental studies to ensure that their predictions remain physically reliable. The validated tools will then be used to explore practical "what if" scenarios relevant to next-generation power systems, including how variations in fuel composition and operating conditions influence combustion performance, stability, and emissions. By enabling complex combustion processes to be modelled more accurately and efficiently, this research will improve understanding of zero-carbon fuel behaviour and support the design of safer, cleaner, and more efficient power-generation technologies.

Who or what inspired you to pursue your research interests?

My interest in CFD began during my first year at the undergraduate. I was fascinated by the idea that computation could predict complex fluid behaviour without relying entirely on experiments. Later during my professional career, I became more aware of the environmental impact of carbon emissions. Losing a beloved neighbour to lung cancer at that time made my desire to contribute to a healthier future even more personal. I was drawn to machine learning because of its potential to reduce the computational demands of high-fidelity simulations and provide faster predictions for practical engineering applications. My research brings these interests together, allowing me to use my training in computational fluid dynamics and machine learning to help develop cleaner power-generation technologies and contribute to a greener world.