This paper presents a method by which the maximum possible rate of pulverized coal injection (PCI) in </span><span style="font-family:Verdana;">blast</span> <span style="font-family...This paper presents a method by which the maximum possible rate of pulverized coal injection (PCI) in </span><span style="font-family:Verdana;">blast</span> <span style="font-family:Verdana;">furnace</span><span style="font-family:Verdana;"> can be predicted. The method is based on a two-step approach. First, a </span><span style="font-family:Verdana;">first principle</span><span style="font-family:Verdana;"> 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 </span><span style="font-family:Verdana;">that</span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">,</span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;"> 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.展开更多
文摘This paper presents a method by which the maximum possible rate of pulverized coal injection (PCI) in </span><span style="font-family:Verdana;">blast</span> <span style="font-family:Verdana;">furnace</span><span style="font-family:Verdana;"> can be predicted. The method is based on a two-step approach. First, a </span><span style="font-family:Verdana;">first principle</span><span style="font-family:Verdana;"> 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 </span><span style="font-family:Verdana;">that</span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">,</span></span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;"> 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.
