Modelling of Multiphase Flow in Ironmaking Blast Furnace

Influence of blast volume on hot blast distribution rule around the hearth circumferentially

Based on Ansteel’s new No. 5 blast furnace (BF), the distribution rule of hot blast on the circumference of blast furnace hearth under different blast volume was studied. The results show that, the blast volume distribution rule is similar under different blast volumes, that is, there are four regions with large blast volumes at the 0°, 90°, 180° and 270° positions of the bustle pipe. Under different blast volumes, the difference of blast volume near 90° and 270° is close to 0, which has a minor effect on the uneven distribution of gas flow and circumferential asymmetry of packed bed in BF. However, the blast volume of the tuyere near the 180° is always larger than that of the tuyere near 0°, and with the increase of blast volume from 4600 to 5000 nm3/min, this difference keeps increasing, 0.69 to 0.95 nm3/min. This phenomenon will lead to an increase in the coke consumption on the 180° side, and cause a higher descending velocity of coke than that on the 0° side, this difference increases from 0.39 to 0.54 m, which could further result in the unevenness of blast volume distribution and the circumferential asymmetry of packed bed in BF. Comparing with the actual production in Ansteel, the results obtained in this work are in good agreement with the phenomenon in practical production.

A Multiobjective Evolutionary Nonlinear Ensemble Learning With Evolutionary Feature Selection for Silicon Prediction in Blast Furnace

In the blast furnace ironmaking process, accurate prediction of silicon content in molten iron is of great significance for maintaining stable furnace conditions, improving hot metal quality, and reducing energy consumption. However, most of the current research works employ linear correlation coefficient methods to select input features in modeling, which may not fully take the nonlinear and coupling relationships between features into account. Therefore, this article considers the input feature selection issue of silicon content prediction model from a new perspective and proposes a multiobjective evolutionary nonlinear ensemble learning model with evolutionary feature selection mechanism (MOENE-EFS), in which extreme learning machine is adopted as the base learner. MOENE-EFS takes the input feature scheme of each base learner as well as their network structure and parameters as decision variables and proposes a modified nondominated sorting differential evolution algorithm to optimize two conflicting objectives, i.e., accuracy and diversity of base learners, simultaneously. Through the optimization, a set of Pareto optimal base learners with high accuracy and strong diversity can be obtained. Moreover, different from the linear ensemble methods commonly used in classical evolutionary ensemble learning, this article proposes a nonlinear ensemble method to combine the obtained base learners based on differential evolution. Experimental results indicate that the two proposed strategies, i.e., evolutionary feature selection and nonlinear ensemble, are very effective in improving the accuracy and stability of the prediction model. MOENE-EFS also outperforms the other prediction models in both benchmark data and practical industrial data. Furthermore, analysis on the input features of all Pareto optimal base learners shows that the evolutionary feature selection is capable of selecting essential features and is consistent with human experience, which indicates it is a promising method to deal with the input feature selection issue in silicon content prediction.

Modeling and Optimization of Biochar Injection into Blast Furnace to Mitigate the Fossil CO2 Emission

Most modern blast furnaces (BFs) operate with Pulverized Coal Injection (PCI), but renewable and carbon neutral biochar could be applied to reduce the fossil CO2 emission in the short term. In the present study, heat and mass balance-based model (MASMOD) is applied to evaluate the potential of biochar in partial and full replacement of injected pulverized coal (PC) in the ironmaking BF. The impact of biochar injection on the raceway adiabatic flame temperature (RAFT) and top gas temperature (TGT) is evaluated. Three grades of biochar, produced from the pyrolysis of sawdust, were evaluated in this study. The total carbon content was 79.2%, 93.4% and 89.2% in biochar 1, 2 and 3, respectively, while it was 81.6% in the reference PC. For each type of biochar, 6 cases were designed at different injection levels from 30 kg/tHM up to 143 kg/tHM, which represent 100% replacement of PC in the applied case, while the top charged coke is fixed in all cases as reference. The oxygen enrichment, RAFT, and TGT are fixed for certain cases, and have been calculated by MASMOD in other cases to identify the optimum level of biochar injection. The MASMOD calculation showed that as the injection rate of biochar 1 and biochar 2 increased, the RAFT increased by ~190 °C, while TGT decreased by ~45 °C at 100% replacement of PC with biochar. By optimizing the moisture content of biochar and the oxygen enrichment in the blast, it is possible to reach 100% replacement of PC without much affecting the RAFT and TGT. Biochar 3 was able to replace 100% of PC without deteriorating the RAFT or TGT.

Behavior of the Free Surface of Two-Phase Fluid Flow Near the Taphole in a Tank

The present study numerically investigated the deformation of the free-surface of two-phase fluid flow in a tank which is considered as a simplified blast furnace hearth. Actually, the fluids existing in a blast furnace hearth are gas, slag and hot metal from top to bottom. However, the present study considered only gas and cold molten iron in the tank. The porosity is considered as a substitute for void volume formed by the packed bed of the particles such as cokes. The single-phase flow and two-phase fluids flow without the porosity are analyzed for comparison. The porosity contributed the free surface to forming a viscous finger near the taphole. The axi-symmetry nature of the interface of two-phase fluids flow in the cylindrical tank is broken by viscous finger as the interface instability by the gas entrainment into taphole, which has been identified by the visualization of the free surface formation. The acceleration of the free surface falling velocity and the outflow near the taphole are associated by the viscous finger by the gas entrainment. The dimensionless gas break-through time is linear with respect to the porosity magnitude.