A macro-scale approach to computational fluid dynamics modelling of the reduction of manganese ore by hydrogen

The carbonaceous reduction of manganese ore is an energy-intensive process that releases large amounts of pollutant gases. In an attempt to circumvent the greenhouse gas emissions, this research investigates hydrogen as an alternative reductant. The reduction of manganese ore with hydrogen results in the structural changes in the intermediate products, which might limit the diffusion of the reactant gases through the pores. Computational fluid dynamics (CFD) models capture the structural changes and predict the rate controlling mechanism and this is key in designing the prereduction reactors. The current work uses CFD models to predict the degree of reduction in a shaft furnace under hydrogen reducing conditions. Manganese ore is described as a collection of scalar and tensor fields such as thermal conductivity of the porous medium, density, and viscous resistance. The results indicate that advection contributes significantly towards the overall transport of hydrogen to the reaction sites. Porosity of the final product was found to be higher than porosity of the raw material.