Impact of operational parameters on fuel consumption of a blast furnace

Abstract Process analyses foster opportunities for identifying losses during the production process and consequently, provide courses of action to enhance the process with operational parameters that are compatible with the targeted results. In this study, a thermochemical model was developed in order to monitor the performance of coke-based blast furnaces, focusing on tools for calculating and graphically displaying parameters that facilitate interpretation of the internal phenomena. To apply the model, a database was prepared based on operational simulations of blast furnaces. The input parameters for the model consisted of the properties and consumption of raw materials and the mass and thermal balances of the process. The thermochemical model is based on the calculation of the degree of reduction of the metallic burden in the preparation zone, defined as the omega factor. It was found that the omega factor varies significantly with the CO/CO2ratio and %H2of the top gas. The results obtained by applying this model were coherent, thus validating it as a predictive tool for assessing the sensitivity of the omega factor, which has a major effect on carbon consumption.

摘要 过程分析能够助力识别生产过程中的损耗，并据此提供优化路径，可借助与目标成果适配的运行参数来改进生产流程。本研究开发了一款热化学模型(thermochemical model)，用于监测焦炭基高炉(coke-based blast furnaces)的运行性能，重点构建可计算并图形化展示参数的工具，以助力内部现象的解析。为应用该模型，本研究基于高炉运行模拟数据构建了专用数据库。该模型的输入参数涵盖原料特性与消耗量，以及生产过程的物料与热平衡数据。该热化学模型以装料区内金属炉料的还原度计算为基础，该还原度被定义为Omega因子(omega factor)。研究发现，Omega因子会随高炉顶煤气的CO/CO₂比值及H₂体积占比发生显著变化。通过该模型得到的结果具备良好一致性，由此验证其可作为评估Omega因子敏感性的预测工具，而Omega因子对碳消耗量具有关键性影响。