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Mathematical Model of Forecasting the Iron Ore Materials and Coke Quality Indicators

机译：铁矿石原料和焦炭质量指标预测的数学模型

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The iron ore raw materials and coke quality is the basic reserve of improvement of blast furnace technology. Some of the quality indicators of iron ore raw materials and coke and their influence on the main parameters of the blast furnace smelting are considered in this paper.

机译：铁矿石原料和焦炭质量是高炉技术进步的基本储备。本文考虑了铁矿石原料和焦炭的一些质量指标及其对高炉冶炼主要参数的影响。

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来源
《Diffusion in solids and liquids VI》|2010年|p.1198-1203|共6页
会议地点 Paris(FR);Paris(FR)
作者
A.N. Dmitriev; Yu.A. Chesnokov; G.Yu. Arzhadeeva; Yu.P. Lazebnaya;
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作者单位

Institute of Metallurgy of Ural Branch of Russian Academy of Sciences, 101 Amundsen St., Ekaterinburg, 620016, Russia;

Institute of Metallurgy of Ural Branch of Russian Academy of Sciences, 101 Amundsen St., Ekaterinburg, 620016, Russia;

Institute of Metallurgy of Ural Branch of Russian Academy of Sciences, 101 Amundsen St., Ekaterinburg, 620016, Russia;

Institute of Metallurgy of Ural Branch of Russian Academy of Sciences, 101 Amundsen St., Ekaterinburg, 620016, Russia;

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会议组织
原文格式 PDF
正文语种 eng
中图分类工程材料一般性问题;
关键词
mathematical model; iron ore raw materials; coke; quality; diffusion;

机译：数学模型;铁矿石原料可乐;质量;扩散;

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专利

1. Mathematical Model of Forecasting the Iron Ore Materials and Coke Quality Indicators [J] . A.N. Dmitriev, Yu.A. Chesnokov, G.Yu. Arzhadeeva, Diffusion and Defect Data. Solid State Data, Part A. Defect and Diffusion Forum . 2011,第Pta2期

机译：铁矿石原料和焦炭质量指标预测的数学模型
2. Mathematical Model of Forecasting the Coke Quality Indicators [J] . A.N. Dmitriev, Yu.A. Chesnokov, G.Yu. Arzhadeeva Diffusion and Defect Data. Solid State Data, Part A. Defect and Diffusion Forum . 2010,第Pta2期

机译：预测焦炭质量指标的数学模型
3. The Coke and Iron Ore Materials Kinetic Characteristics andQuantitative Indicators of Blast Furnace Process [J] . A.N. Dmitriev, Yu.A. Chesnokov, G.Yu. Arzhadeeva Diffusion and Defect Data. Solid State Data, Part A. Defect and Diffusion Forum . 2012,第Null期

机译：高炉过程中焦炭和铁矿石材料的动力学特性和定量指标
4. Mathematical Model of Forecasting the Iron Ore Materials and Coke Quality Indicators [C] . A.N. Dmitriev, Yu.A. Chesnokov, G.Yu. Arzhadeeva, International Conference on Diffusion in Solids and Liquids, Mass Transfer-Heat Transfer-Microstructure Properties-Nanodiffusion and Nanostructured Materials . 2010

机译：铁矿石材料预测的数学模型及焦炭质量指标
5. Non-coke smelting reduction of iron ores: Process modelling. [D] . Pichestapong, Pipat. 1997

机译：铁矿石的非焦炭冶炼还原：过程建模。
6. Utilizing Iron Ore Tailing as Cementitious Material for Eco-Friendly Design of Ultra-High Performance Concrete (UHPC) [O] . Gang Ling, Zhonghe Shui, Xu Gao, 2021

机译：利用铁矿石拖尾作为胶凝材料以实现超高性能混凝土的环保设计（UHPC）
7. Mathematical modeling of the processes of estimating reserves of iron ore raw materials in conditions of uncertainty [O] . N. N. Nekrasova, E. G. Kabulova, A. A. Maslov 2016

机译：不确定性条件下铁矿石原料储量储量过程的数学建模
8. Mathematical Modeling of Raw Materials and Energy Needs of the Iron and Steel Industry in the U.S.A. Phase I. A Model of the Raw Materials Requirements of the U.S. Steel Industry. [R] . elliott,john f. 1976

机译：美国钢铁工业原料和能源需求的数学模型第一阶段：美国钢铁工业原料需求模型。

Mathematical Model of Forecasting the Iron Ore Materials and Coke Quality Indicators

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