The blast furnace ironmaking process is a crucial step in the steel industry.Effectively modelling the blast furnaces is significant in ensuring smooth operation and accelerating the digitalisation transformation of b...The blast furnace ironmaking process is a crucial step in the steel industry.Effectively modelling the blast furnaces is significant in ensuring smooth operation and accelerating the digitalisation transformation of blast furnaces.The authors focus on the mechanism modelling of the blast furnace operation process,using a digital twin model development platform to simulate the main reaction processes inside the blast furnaces.Under on-site production conditions,Si,Mn and Ti contents of molten iron and the corresponding indicators for model accuracy are calculated.For Si,Mn,and Ti content,the Root Mean Square Error values are 0.0678,0.0108 and 0.0093 for dataset 1,while 0.0933,0.0120 and 0.0111 for dataset 2,respectively,indicating that the model has a small simulation error and high accuracy.By comparing the simulation results with accurate laboratory results,the model is validated to have satisfactory simulation reliability and compensates for the existing shortcomings in the blast furnace mechanism modelling field.展开更多
基金National Natural Science Foundation of China,Grant/Award Numbers:61933015,62394341Postdoctoral Fellowship Program of CPSF,Grant/Award Number:GZC20232288。
文摘The blast furnace ironmaking process is a crucial step in the steel industry.Effectively modelling the blast furnaces is significant in ensuring smooth operation and accelerating the digitalisation transformation of blast furnaces.The authors focus on the mechanism modelling of the blast furnace operation process,using a digital twin model development platform to simulate the main reaction processes inside the blast furnaces.Under on-site production conditions,Si,Mn and Ti contents of molten iron and the corresponding indicators for model accuracy are calculated.For Si,Mn,and Ti content,the Root Mean Square Error values are 0.0678,0.0108 and 0.0093 for dataset 1,while 0.0933,0.0120 and 0.0111 for dataset 2,respectively,indicating that the model has a small simulation error and high accuracy.By comparing the simulation results with accurate laboratory results,the model is validated to have satisfactory simulation reliability and compensates for the existing shortcomings in the blast furnace mechanism modelling field.
