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Kou M, Zeng W, Zhang Z, She X, Zhang T, Zhao B, Ma X, Zhou H. Central coke charging and its effect on coke collapse at the throat of blast furnace by DEM simulation. POWDER TECHNOL 2022. [DOI: 10.1016/j.powtec.2022.117784] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/16/2022]
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Di Z, Huang M, Zhou X, Liu J, Sun J, Wang P, Wang H. The influence of central coke charging mode on the burden surface shape and distribution of a blast furnace. INTERNATIONAL JOURNAL OF CHEMICAL REACTOR ENGINEERING 2022. [DOI: 10.1515/ijcre-2022-0066] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Abstract
The burden surface shape and distribution in the shaft directly affect the gas distribution, heat transfer and chemical reactions inside the blast furnace. The current study developed a three-dimensional model of bell-less top charging to investigate the influence of the “central coke charging/sub-central coke charging” (CCC/SCCC) mode on the burden surface shape, burden distribution, and mass percentage of ore-to-coke (O/C). The results showed that the burden height of the region between the middle and edge is low by applying the CCC mode, while there is a heap valley in the center and a heap top in the middle region when the SCCC mode was adopted. In radial direction, the mass percentage of bigger size coke in the middle region is largest for the CCC mode, while the largest of the mass percentage was obtained in the center region by applying the SCCC mode. In longitudinal direction, the mass percentages of bigger coke and ore at the top region are largest for both modes. Besides, the mass percentage of O/C increased and then decreased to zero at the center for both modes. And the maximum of the mass percentage of O/C were 7.63 and 7.38, respectively.
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Affiliation(s)
- Zhanxia Di
- School of Metallurgy Engineering, Anhui University of Technology , Ma’anshan , Anhui 243032 , China
| | - Mingrong Huang
- School of Metallurgy Engineering, Anhui University of Technology , Ma’anshan , Anhui 243032 , China
| | - Xiaobin Zhou
- School of Metallurgy Engineering, Anhui University of Technology , Ma’anshan , Anhui 243032 , China
| | - Junhan Liu
- School of Metallurgy Engineering, Anhui University of Technology , Ma’anshan , Anhui 243032 , China
| | - Junjie Sun
- Baosteel Central Research Institute, Baoshan Iron & Steel Co., Ltd , Shanghai 201900 , China
| | - Ping Wang
- School of Metallurgy Engineering, Anhui University of Technology , Ma’anshan , Anhui 243032 , China
| | - Hongtao Wang
- School of Metallurgy Engineering, Anhui University of Technology , Ma’anshan , Anhui 243032 , China
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A blast furnace coke ratio prediction model based on fuzzy cluster and grid search optimized support vector regression. APPL INTELL 2022. [DOI: 10.1007/s10489-022-03234-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
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