Abstract
Tuyere core drillings give a unique opportunity to probe the blast furnace and detect changes in both physical and chemical conditions of its high-temperature region. In this paper the findings from drill cores taken from a blast furnace are used to characterize the internal state of the furnace hearth, quantified by an erosion model estimating the available hearth volume. The complex relation is studied by entertaining neural network models using different combinations of inputs consisting of the extent of the distinct tuyere-level zones (raceway, bird's nest, dead man, etc.) of the core samples. The resulting model can be used to gain knowledge of the relation between tuyere level conditions and hearth states, and to classify the findings from future core drillings. The results also throw light on possible reasons for thermal cycles observed in the hearth of the furnace studied.
