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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。
In order to further study and optimize the different iron tailings ratio in the quenching and tempering process with the optimal matching between the slag. On the basis of the properties of heat and mass balance, based on the principle of heat balance and mathematical model, thermodynamic software FactSage7.0 was used to simulate the influence of different proportions of iron tailings on the thermodynamics of blast furnace slag system. The cubic spline interpolation The relation between the temperature and the melting temperature of the blast furnace slag was investigated. The temperature dependence of blast furnace slag system with different ratios of iron tailings at different temperatures was simulated and the algorithm of genetic optimization gray neural network The simulation and prediction of the optimal matching relationship between different tailings and the amount of thermal compensation iron tailings provide a theoretical reference for the study of quenching mechanism of iron tailings.