A sintering burden blending model based on one-step optimization method and high-temperature characteristics of iron ore

A sintering burden blending model is an intelligent system used to obtain the optimal blending proportions of burdens with minimal sintering burden cost. In this study, micro-sintering and sinter pot tests were first carried out to clarify the quantitative relationship between the shatter index (SI) of the sinter and high-temperature characteristics (HTCs) of the ore blends. The result shows that the lowest assimilation temperature (LAT) plays a dual role in SI, whereas the index of liquid phase fluidity (ILF) and compressive strength of the bonding phase (CSB) have positive effects on SI. The effect of the ILF is the largest. Based on the one-step optimization method, suitable ranges of room-temperature characteristics (RTCs) of ore blends, obtained relationship between sinter strength and HTCs of ore blends, sintering theory, and bisection and simplex algorithms, the proposed sintering burden blending model is established. The validation for the model shows that it is effective at utilizing iron ore resources, maintaining high strength of the sinter, while reducing burden costs.