Double-hyperplane fuzzy classifier design for tendency prediction of silicon content in molten iron

Author(s):  
Junpeng Li ◽  
Xiaofei Wei ◽  
Changchun Hua ◽  
Yana Yang ◽  
Limin Zhang
2019 ◽  
Vol 38 (2019) ◽  
pp. 143-150
Author(s):  
Yong Deng ◽  
Jianliang Zhang ◽  
Kexin Jiao

AbstractIn order to improve the reduction rate of titania in molten iron, various iron powders containing C, Si, Mn and S were melted. The experiments were carried out on the reduction of titania through a high-temperature tube furnace at 1,723–1,823 K. The quantitative effects of C, Si, Mn, S and temperature on the reduction of titania were investigated in the current study. The results demonstrated that when the carbon content, the manganese content and the temperature increased by 1 %, 0.1 % and 100 K, the reduction rate increased by 0.008 %/h, 0.001125 %/h and 0.0235 %/h, respectively; when the sulfur content increased by 0.01 %, the reduction rate decreased by 0.004875 %/h; the reduction rate was irregular with the change of silicon content in molten iron. The phase at the reaction interface after the experiment was confirmed to be the Fe2Ti3O9 which was considered to be the combination product between iron oxide and titania; the lower titanium oxides were unstable and hard to be observed. The reduction was affected by the concentration of various elements in molten iron and the activity interaction coefficients between various elements. The rate constants for reduction were calculated at 1,723 K, 1,773 K and 1,823 K; the apparent activation energy was calculated as 209 kJ/mol through the rate constants and temperatures according to the Arrhenius equation.


2006 ◽  
Vol 55 (7) ◽  
pp. 3343
Author(s):  
Luo Shi-Hua ◽  
Liu Xiang-Guan

Author(s):  
Phạm Đình Phong ◽  
Nguyễn Cát Hồ ◽  
Trần Thái Sơn ◽  
Nguyễn Thanh Thủy

2007 ◽  
Vol 40 (12) ◽  
pp. 3401-3414 ◽  
Author(s):  
Enwang Zhou ◽  
Alireza Khotanzad

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