Mathematical model of roller-bearing electric steel chemical composition control on the ladle-furnace

被引：0
|
作者：
Panchenko, A.I. [1 ]
Salnikov, A.S. [1 ]
Skripka, L.M. [1 ]
Zhadanos, A.V. [2 ]
Gasik, M.I. [2 ]
机构：
[1] JSC Dneprospetsstal, 81 Yuzhnoe Shosse, Zaporizhzhya, 69008, Ukraine
[2] National Metallurgical Academy of Ukraine, 4 Gagarin Ave., Dnipropetrovsk, 49600, Ukraine
来源：
Metallurgical and Mining Industry | 2010年 / 2卷 / 06期
关键词：
Alloying - Information systems - Chemical analysis - Information use - Ladles - Reducing agents - Binary alloys - Regression analysis - Steelmaking - Chromium - Silicon alloys - Alloying elements - Electric furnaces - Ferroalloys - Chromium alloys - Manganese alloys;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Regression models of chromium, silicon, manganese and carbon content behavior in metal depending on the amount of added carbonaceous materials,ferrosilicomanganese MnS17, ferromanganese FeMn78, ferrosilicon FeSi65, ferrochromium FeCr800 are obtained as a result of analysis of experimental data for bearing electric steel IIIX 15 and IIIX15CT-B. These models enable to forecast chemical composition of steel in order to save reducing agents and alloying elements. The structural diagram of automated information system of ladle-furnace is designed according to results of investigations. © Metallurgical and Mining Industry, 2010.
引用
收藏
页码：390 / 396
相关论文
共 13 条
  • [1] Mathematical Simulation of Nonstationary Mixing of Steel in a Ladle-Furnace Unit
    Erofeev, M. M.
    Agapitov, E. B.
    RUSSIAN METALLURGY, 2009, 2009 (07): : 571 - 575
  • [2] Automatic monitoring of slag composition during steel treatment in a Ladle-Furnace unit
    Nekrasov I.V.
    Sheshukov O.Y.
    Sysolin A.V.
    Lutsenko V.T.
    Bondarenko V.N.
    Steel in Translation, 2009, 39 (10) : 847 - 850
  • [3] Mass-Transfer Model for Steel, Slag, and Inclusions during Ladle-Furnace Refining
    Zhu, Liguang
    Jia, Yanan
    Liu, Zengxun
    Zhang, Caijun
    Wang, Xingjuan
    Xiao, Pengcheng
    HIGH TEMPERATURE MATERIALS AND PROCESSES, 2018, 37 (07) : 665 - 674
  • [4] Development the Automated Information System of Ladle-Furnace Process to Predict the Content of Alloying Elements in Bearing Steel
    Zhadanos, O.
    Derevyanko, I.
    Proydak, Y.
    Gasik, M.
    Panchenko, O.
    Salnikov, A.
    Yakovitsky, O.
    2017 INTERNATIONAL CONFERENCE ON INFORMATION AND DIGITAL TECHNOLOGIES (IDT), 2017, : 452 - 458
  • [5] Ladle furnace on-line reckoner for prediction and control of steel temperature and composition
    Nath, NK
    Mandal, K
    Singh, AK
    Basu, B
    Bhanu, C
    Kumar, S
    Ghosh, A
    IRONMAKING & STEELMAKING, 2006, 33 (02) : 140 - 150
  • [6] Optimal Alkalinity Model of Ladle Furnace Slag for Bearing Steel Production Based on Ion-Molecule Coexistence Theory
    Lei, Jialiu
    Li, Jie
    Yang, Ling
    Zhang, Yucheng
    PROCESSES, 2023, 11 (03)
  • [7] COMPUTER CONTROL OF ELECTRIC-ARC FURNACE STEELMAKING PROCESS BASED ON A MATHEMATICAL-MODEL
    TAKAWA, T
    INOUE, J
    YAMAMURA, H
    TETSU TO HAGANE-JOURNAL OF THE IRON AND STEEL INSTITUTE OF JAPAN, 1988, 74 (11): : 2122 - 2129
  • [8] The effect of chemical composition on the leaching behaviour of electric arc furnace (EAF) carbon steel slag during a standard leaching test
    Mombelli, D.
    Mapelli, C.
    Barella, S.
    Di Cecca, C.
    Le Saout, G.
    Garcia-Diaz, E.
    JOURNAL OF ENVIRONMENTAL CHEMICAL ENGINEERING, 2016, 4 (01): : 1050 - 1060
  • [9] Mathematical model on heat transfer of water-cooling steel-stick bottom electrode of DC electric arc furnace
    Xu, H
    Wen, Z
    Zhu, HX
    Liu, X
    Shi, HZ
    JOURNAL OF UNIVERSITY OF SCIENCE AND TECHNOLOGY BEIJING, 2002, 9 (05): : 338 - 342
  • [10] Mathematical model on heat transfer of water-cooling steel-stick bottom electrode of DC electric arc furnace
    Hai Xu
    Journal of University of Science and Technology Beijing(English Edition), 2002, (05) : 338 - 342
12