Rheological Behavior and Parameter Prediction of Steel Slag-Mineral Powder Based Geopolymer
YU Li
ZHANG Shuxiang
ZHU Tao
YANG Qingning
ZHANG Dongsheng
Abstract：In order to explore the influence of steel slags of different fineness on the rheological properties of the steel slag-mineral powder base polymer,the variation law of the rheology of different steel slag fineness was studied by fluidity,rheometer and water film thickness(δWFT)tests,and the rheological parameter prediction model was established by BP neural network based on the correlation between fluidity and δWFT and rheological parameters.The results show that with the increase of steel slag fineness,the fluidity of the freshly mixed polymer mortar is improved,and its setting time and δWFT are shortened.The change in slag fineness does not change the fluid type and the rheological characteristics are in line with the Bingham model.The apparent viscosity gradually decreases with the increase of shear rate,the yield stress,plastic viscosity and thixotropy continue to decrease with the increase of steel slag fineness,the rheological parameters increased with the increase of the standing time,and the growth rate also showed a gradual increasing trend.Meantime,the fluidity is positively correlated with the yield stress,and the δWFT has a good linear relationship with the yield stress and fluidity.The rheological parameter prediction model based on BP neural network was established,and the prediction results were in good agreement with experimental ones.
Keywords：steel slag powdergeopolymer mortarrheologyBP neural networkrheological changes over time
Publication Date：2025-05-30
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：12( 465-476 )