Comparison of calculated equilibrium and operation data for blast furnace with focus on silicon

Abstract

An investigation of reactions involving blast furnace hot metal, slag and gas at equilibrium was carried out. Performed calculations were based on estimated total gas pressures, measured temperatures and hot metal and slag compositions. Calculated element contents of liquid phases were found to be very similar to their corresponding values determined through measurement when formation of the gas phase was suppressed. This resulted in higher equilibrium CO partial pressures compared to the measured total gas pressure in the bustle ring. When only equilibrium conditions were considered, the predicted amount of silicon was much higher than the measured. A comparison of activity coefficients of elements in the hot metal using different calculation models was also carried out. Two different models based on dilute solutions were compared with the TCFe3 database developed for the software Thermo-Calc, which can handle higher alloying concentrations. Considerably different calculation results were found among the different models studied.

Investigation into the Cause of Spontaneous Emulsification of a Free Steel Droplet; Validation of the Chemical Exchange Pathway

“…From Table VII the surface area of the drop stays relatively constant through the first 3 samples 6 to 8 mm 2 , followed by an increase by an order of magnitude to 65.75 mm. [2] This increase in area is very similar to that seen in the previous study [1] ; however there is a delay of~30 seconds. This is clearly seen in the normalized area curves displayed in Figure 7.…”

“…MANY steps in the process of steel making rely on the transfer of elements from metal to slag; a few examples are silica removal in the blast furnace, [2] sulfur in the desulfurization pre-treatment, [3] and phosphorus removal during steelmaking in the basic oxygen furnace (BOF). [4] In the case of phosphorus refining in the BOF, much work has been carried out on the thermodynamic equilibrium between the metal and slag, [5][6][7] giving evidence to the kinetic inhibition of the potential partition possible.…”

Blast Furnace System Modeling by Multivariate Phase Space Reconstruction and Neural Networks

“…Table IV illustrates that, when the embedding dimension is small, there are more false nearest neighbors; however, the number of false nearest neighbors decreases dramatically as the dimension increases. As the dimension increases from (4, 3) to (4,4) or (5,3), the number of false nearest neighbors increases from 23 to 49, and the percentage of false nearest neighbors are 2.25% and 4.8%, respectively, which is smaller than the threshold d = 5%. The geometric structure of the blast furnace system is sufficiently spanned when m1 = 4, m2 = 3, so the embedding dimension is determined as m1 = 4, m2 = 3.…”

“…A comprehensive review of the mechanistic models is presented in . In contrast, with the rapid development of computer technology and data mining techniques, data‐driven models have been extensively explored . Most of the data‐driven models are focused on developing predictive models for silicon content in hot metal (denoted by [Si]), which is the main quality index and indication of thermal state in the blast furnace.…”