This PhD project is focused on investigating the kinetics of oxy-fuel combustion of biomass in the fluidised bed reactor and the feasibility of applying machine learning techniques in carbon capture and storage technologies.

  • Dates2017 - 2021
  • Funded£50,000

Research in this project is focused on experimental studying of air and oxy-fuel combustion of biomass in a fluidised bed reactor and applying machine learning techniques to predict known parameters and estimate unknown parameters in the oxyfuel combustion process.


Impact and findings

An in depth experimental study has been conducted to determine the air and oxy-fuel biomass combustion kinetics in a spout fluidised bed reactor. This research was written up into a journal paper and submitted to the International Journal of Greenhouse Gas Control. Following this, we have begun applying artificial neural networks to this kinetic data to observe if the machine learning can predict the complex kinetic behaviour.

'', EJ. Anthony 2018 (PDF)