Analysis Of Transport Phenomena In Submerged Arc Furnace For Ferrochrome Production

Ferrochrome is the major chromium source for stainless steel production, and submerged-arc furnaces (SAF) are most commonly utilised to smelt chromite ores into ferrochrome by using suitable carbonaceous reductants such as coke. Because of the complexity of feed structure and electrical-thermal-chemical interactions, there exist large gradients and wide distributions of temperature, mineralogy and other process variables in the furnace. This leads to various zones in the furnace, and different reduction mechanisms. Control of the furnace is thus often difficult due to the complicated physical and chemical situations in the furnace. The temperature profile in the submerged arc furnace has a great influence on the reduction rate and the production efficiency. Therefore, the energy generation through electrical arcs submerged in the solid feed and its distribution within the packed bed play an important role. In the present paper, an overall process model is illustrated to simulate inter-linked transport processes of fluid flow, heat transfer and reduction kinetics within the submerged arc furnace. The application of reaction kinetic data to simulate the chromite pellet/lumpy ore reduction with CO gas is presented and further adjusted to provide a submodel for a flow and heat transfer simulation for the packed bed by using computational fluid dynamics (CFD) technique. The comprehensive process model is aimed to simulate materials and gas flow, temperature and energy distribution throughout the furnace system. A preliminary model for gas flow and temperature distribution for the upper part of a 20 MW furnace (the packed bed) for high carbon ferrochrome production has been developed under simplified conditions. The integration of the reaction kinetic model into process simulation, and the future vision for a more comprehensive process modelling are discussed. It is expected that better understanding of the furnace insights through process modelling will help process optimisation and furnace control.