Three lightweight Al_(2)O_(3)-MgO castables were fabricated with tabular alumina or microporous corundum as the aggregates,reactiveα-Al_(2)O_(3)micropowder,tabular alumina powder,and fused magnesia powder as the matr...Three lightweight Al_(2)O_(3)-MgO castables were fabricated with tabular alumina or microporous corundum as the aggregates,reactiveα-Al_(2)O_(3)micropowder,tabular alumina powder,and fused magnesia powder as the matrix,calcium aluminate cement as the binder,and MgO ultrafine powder(d50=5.4μm)and Al(OH)3 ultrafine powder(d50=8.2μm)as additives.The influence of aggregates and ultrafine powders on the properties,including pore size distribution,heat conductivity,thermal shock resistance,and slag resistance of lightweight refractory castables was investigated.The results show that the incorporation of microporous corundum reduces the bulk density of Al_(2)O_(3)-MgO castables,and MgO and Al(OH)3 ultrafine powders further increases the proportion of micropores in castables,which is beneficial to reducing the heat conductivity,and improving the thermal shock resistance and slag resistance of castables.Additionally,MgO ultrafine powder and Al(OH)3 ultrafine powder increase the fluidity and the strength of castables.展开更多
The high-temperature performance of iron ore fmes is an important factor in optimizing ore blending in sintering. However, the application of linear regression analysis and the linear combination method in most other ...The high-temperature performance of iron ore fmes is an important factor in optimizing ore blending in sintering. However, the application of linear regression analysis and the linear combination method in most other studies always leads to a large deviation from the desired results. In this study, the fuzzy membership functions of the assimilation ability temperature and the liquid fluidity were proposed based on the fuzzy mathematics theory to construct a model for predicting the high-temperature performance of mixed iron ore. Comparisons of the prediction model and experimental results were presented. The results illustrate that the prediction model is more accurate and effective than previously developed models. In addition, fuzzy constraints for the high-temperature performance of iron ore in this research make the results of ore blending more comparable. A solution for the quantitative calculation as well as the programming of fuzzy constraints is also introduced.展开更多
基金the National Natural Science Foundation of China(grant no.51774218 and 51374162)for providing financial support for this work.
文摘Three lightweight Al_(2)O_(3)-MgO castables were fabricated with tabular alumina or microporous corundum as the aggregates,reactiveα-Al_(2)O_(3)micropowder,tabular alumina powder,and fused magnesia powder as the matrix,calcium aluminate cement as the binder,and MgO ultrafine powder(d50=5.4μm)and Al(OH)3 ultrafine powder(d50=8.2μm)as additives.The influence of aggregates and ultrafine powders on the properties,including pore size distribution,heat conductivity,thermal shock resistance,and slag resistance of lightweight refractory castables was investigated.The results show that the incorporation of microporous corundum reduces the bulk density of Al_(2)O_(3)-MgO castables,and MgO and Al(OH)3 ultrafine powders further increases the proportion of micropores in castables,which is beneficial to reducing the heat conductivity,and improving the thermal shock resistance and slag resistance of castables.Additionally,MgO ultrafine powder and Al(OH)3 ultrafine powder increase the fluidity and the strength of castables.
基金financially supported by the National Natural Science Foundation of China (No. 51204013)the National Key Technology R&D Program in the 12th Five Year Plan of China (No. 2011BAC01B02)
文摘The high-temperature performance of iron ore fmes is an important factor in optimizing ore blending in sintering. However, the application of linear regression analysis and the linear combination method in most other studies always leads to a large deviation from the desired results. In this study, the fuzzy membership functions of the assimilation ability temperature and the liquid fluidity were proposed based on the fuzzy mathematics theory to construct a model for predicting the high-temperature performance of mixed iron ore. Comparisons of the prediction model and experimental results were presented. The results illustrate that the prediction model is more accurate and effective than previously developed models. In addition, fuzzy constraints for the high-temperature performance of iron ore in this research make the results of ore blending more comparable. A solution for the quantitative calculation as well as the programming of fuzzy constraints is also introduced.
