{"title":"Optimization of Raceway Parameters in Iron Making Blast Furnace for Maximizing the Pulverized Coal Injection (PCI) Rate","authors":"D. Sau, Rabiranjan Murmu, P. Senapati, H. Sutar","doi":"10.4236/ACES.2021.112009","DOIUrl":null,"url":null,"abstract":"This \npaper presents a method by which the maximum possible rate of pulverized coal \ninjection (PCI) in blast furnace can be predicted. The method is based \non a two-step approach. First, a first principle simulation model of the blast furnace is used to generate data sets for the \ndevelopment of a linear model of pulverized coal injection rate. The data has \nbeen generated randomly in MATLAB software within the range of operating \nparameters (constraints) of the blast furnace. After that, the coefficients of the function have been determined. The inputs and \nthe resulting outputs formed the data on which the linear optimization model \nwas developed. Next, the linear model was used for maximizing the pulverized \ncoal rate injection by optimizing the other variables. Two operating Indian \nBlast Furnaces have been chosen to validate the optimization model.","PeriodicalId":7332,"journal":{"name":"Advances in Chemical Engineering and Science","volume":"12 1","pages":"141-153"},"PeriodicalIF":0.0000,"publicationDate":"2021-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in Chemical Engineering and Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4236/ACES.2021.112009","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
This
paper presents a method by which the maximum possible rate of pulverized coal
injection (PCI) in blast furnace can be predicted. The method is based
on a two-step approach. First, a first principle simulation model of the blast furnace is used to generate data sets for the
development of a linear model of pulverized coal injection rate. The data has
been generated randomly in MATLAB software within the range of operating
parameters (constraints) of the blast furnace. After that, the coefficients of the function have been determined. The inputs and
the resulting outputs formed the data on which the linear optimization model
was developed. Next, the linear model was used for maximizing the pulverized
coal rate injection by optimizing the other variables. Two operating Indian
Blast Furnaces have been chosen to validate the optimization model.