Speaker
Description
In a blast furnace, hot pressurized air is forced into a packed coke bed where it combusts, generating hot reducing gases for liquid iron production. Stable operation of the furnace requires careful balancing of many operational conditions. Blast furnaces are very resource intensive, and any changes in operating conditions can take hours to produce results. Currently, operators generally rely on established rules of thumb to estimate the response of the furnace to changing conditions, but these rules can be limited in scope and often cannot account for the implementation of new process parameters such as novel injected fuels.
A software was developed to predict blast furnace performance based on pre-calculated simulations of furnace operation. This software uses datasets generated through the application of High-Performance Computing (HPC) to Computational Fluid Dynamics (CFD) of the blast furnace. While CFD allows researchers to determine the likely outcomes of operational changes with reasonable accuracy, the time required to complete a single simulation is typically on the order of days to a week. With this in mind, a large range of data sets were pre-simulated to determine key trends using CFD, comparable to rules of thumb for individual parameters.
The simulator software uses interpolation to create a set of equations relating all of the simulated operating conditions as input variables to specific output variables, such as coke rate, top gas temperature, gas utilization, and pressure drop. This tool can quickly and accurately predict the impacts of changing operating conditions within a given range, providing operators with a limited “what-if” scenario evaluation capability. A feature also exists to return the lowest possible coke rate based on a set of constraints. This allows operators to aim for reduced operating costs and lower carbon emissions from the blast furnace.