CO/CO₂Computational Modeling Studies Of The Sintering Process For Carbon Efficiency Optimization

In order to achieve green manufacturing, reducing pollution emissions is the main theme of the iron and steel industry. Carbon is a major source of energy in the steel production process, so how to optimize the utilization of carbon, and how to effectively control of the conversion and emissions of carbon in the production process, which are the key issue of Green Manufacturing. By these means, it improves the energy efficiency of the iron and steel industry and reduces pollution emissions.Sintering process is an important process in the production of iron and steel metallurgy, and the carbonaceous fuel consumption accounted for8%to10%in the steel production process. The sintering process carbon gas emissions CO/CO2can solid carbon in the reaction sintering process combustion efficiency, and the value can calculate carbon consumption. Therefore, it is important to study sintering process CO/CO2modeling to achieve the optimization of the carbon efficiency of the iron and steel industry.The sintering process is a complex industrial process. It is nonlinear, and some parameters are difficult to detect interference factors. On the basis of the sintering process physical and chemical reactions and the mechanism of carbon flow, through the analysis of production data and carbon gas emissions content measurements of the sintering process, the author presents a CO/CO2computational modeling methods of sintering process, which blend of mathematical modeling and neural network modeling mechanism. By these means, it can calculate CO/CO2in the sintering process.First, according to the principle of carbon flow balance and carbon combustion reaction mechanism and limestone decomposition mechanism, the author can draw carbon gas emissions CO/CO2process parameters of affect the sintering process, and the establishment of the association between the main influence parameter and CO/CO2model; Second, because the simple mechanistic model is difficult to accurately describe the carbon gas emissions, so the author combine with the process of production data and the carbon gas detection data, and establish a CO/CO2computational modeling methods which based on mathematical mechanism input weighted forward neural network. Through the guidance of the mechanism model and neural network nonlinear mapping processing, input by the average temperature of the bellows, carbon ratio of six main factors, output by the CO/CO2.By these means, it can calculate CO/CO2in the sintering process.According to the actual production data and the detected simulation results, carbon gas emission values can show the validity of the modeling methods mentioned herein, and it provides a theoretical basis for further sintering process optimization and control of carbon efficiency.