All Outputs (3)

Modelling of a post-combustion CO₂ capture process using neural networks (2015)
Journal Article
Li, F., Zhang, J., Oko, E., & Wang, M. (2015). Modelling of a post-combustion CO₂ capture process using neural networks. Fuel, 151, 156-163. https://doi.org/10.1016/j.fuel.2015.02.038

This paper presents a study of modelling post-combustion CO₂ capture process using bootstrap aggregated neural networks. The neural network models predict CO₂ capture rate and CO₂ capture level using the following variables as model inputs: inlet flu... Read More about Modelling of a post-combustion CO₂ capture process using neural networks.

Neural network approach for predicting drum pressure and level in coal-fired subcritical power plant (2015)
Journal Article
Oko, E., Wang, M., & Zhang, J. (2015). Neural network approach for predicting drum pressure and level in coal-fired subcritical power plant. Fuel, 151, 139-145. https://doi.org/10.1016/j.fuel.2015.01.091

There is increasing need for tighter controls of coal-fired plants due to more stringent regulations and addition of more renewable sources in the electricity grid. Achieving this will require better process knowledge which can be facilitated through... Read More about Neural network approach for predicting drum pressure and level in coal-fired subcritical power plant.

Study of power plant, carbon capture and transport network through dynamic modelling and simulation (2015)
Thesis
Oko, E. (2015). Study of power plant, carbon capture and transport network through dynamic modelling and simulation. (Thesis). University of Hull. Retrieved from https://hull-repository.worktribe.com/output/4216833

The unfavourable role of CO₂ in stimulating climate change has generated concerns as CO₂ levels in the atmosphere continue to increase. As a result, it has been recommended that coal-fired power plants which are major CO₂ emitters should be operated... Read More about Study of power plant, carbon capture and transport network through dynamic modelling and simulation.