Optimal Matching of Thermodynamics Behavior of Iron Tailings during BF molten slag conditioning Process
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摘要: 为进一步研究和优化不同铁尾矿配比在调质过程中与高炉熔渣间的优化匹配关系。在调质特性的基础上, 基于热平衡原理和数学模型, 利用热力学软件Fact Sage7.0模拟计算不同配比的铁尾矿对高炉熔渣体系热力学的影响, 结合三次样条插值算法得出铁尾矿为调质剂高炉炉渣的熔化性温度的关系, 模拟出在不同温度下不同配比的铁尾矿在适宜酸度内高炉熔渣体系的温降关系, 并利用遗传优化灰色神经网络的算法对不同配比的调质剂铁尾矿与热补偿量之间的优化匹配关系进行模拟和预测, 为研究铁尾矿调质机理提供了理论参考。Abstract: In order to study and optimize the matching relationship between different iron tailings and blast furnace slag during conditioning process,the effect of iron tailings in different proportions on the thermodynamic system of blast furnace slag had been predicated by using the software Fact Sage 7.0 based on the heat balance principle and mathematical model,and the melting temperature of the blast furnace slag with iron tailings as conditioning agent had been calculated through three spline interpolation algorithm.Meanwhile,the temperature drop of blast furnace slag system in different acidity at different temperature had been determined.The optimal matching between different ratio of modifying agent of iron tailings and thermal compensation had been simulated and predicated by using genetic optimization of grey neural network algorithm.
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Key words:
- BF slag /
- slag wool /
- conditioning /
- iron tailings /
- cubic spline interpolation /
- genetic optimization /
- matching optimization
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