SiO_2-Al_2O_3-CaO-MgO四元矿渣棉体系的表面张力测定与模型预报

Surface tension investigation and model forecasting of SiO_2- Al_2O_3-CaO-MgO quaternary mineral wool slag

表面张力是矿物棉生产的重要参数，直接影响到配料和工艺参数的选择.通过实验测量并建立模型预报系统研究了以高炉渣为主要原料制备矿物棉时熔体的表面张力.首先测量了SiO2（40%-60%）- Al2O3（5%-20%）- CaO（20%-30%）-MgO（5%）四元系的表面张力，其值处于350-500 m·m^-1之间；然后结合文献报道的表面张力数据，利用人工神经网络技术建立了SiO2（35%-60%）-Al2O3（5%-20%）-CaO（20%-45%）-MgO（0-10%）四元渣系的表面张力预报模型.该模型对成分范围内的表面张力预报平均误差为9.32%，预报精度较高，可以预报矿物棉熔体成分范围内的表面张力.

Surface tension is one of the major parameters for mineral wool production, and it may influence burdening and processing parameter selection. The surface tension of melts for mineral wool production using blast furnace slag as a major material was systematically investigated by experiment measurements and model forecasting. Firstly, a series of surface tension values of SiO2 （40%- 60%）-Al2O3 （5%-20%）-CaO（20%-30%）-MgO（5%） quaternary systems were measured, and they showed in the range of 350 to 500 m·m^-1 . Then in combination with data from reports in literature, an artificial neural network （ANN） model was constructed to calculate the surface tension of melts in an extension system of SiO2 （35%-60%）-Al2O3 （5%-20%）-CaO（20%-45%）-MgO（0- 10%）. The average error of the developed model is 9. 32%, proving a higher accuracy for predicting the surface tension of those melts in the extension system.