Effect of operating conditions on the particle size distribution and specific energy input of fine grinding in a stirred mill: Modeling cumulative undersize distribution. (January 2022)

• Record Type: Journal Article
• Authors: Guo, Wang; Han, Yuexin; Gao, Peng; Tang, Zhidong
• Is Part Of: Minerals engineering. Volume 176(2022)
• Publication Date: 2022-01
• Subjects: Fine grinding -- Stirred mill -- Specific energy input -- Cumulative undersize distribution -- Prediction; Mines and mineral resources -- Periodicals; Ressources minérales -- Périodiques; Mines and mineral resources; Periodicals; Electronic journals; 622
• DOI: 10.1016/j.mineng.2021.107347
• Languages: English
• ISSNs: 0892-6875

Abstract

Graphical abstract: Highlights: The effect of operating conditions on particle size distribution was examined. The parameter k increased linearly with the grinding time. The characteristic particle and specific energy input followed the Walker model. The modified model could predict the cumulative undersize distribution. Abstract: Simulation of the fine or ultra-fine grinding process by Population Balance Model (PBM) has its restrictions because some coarse particles maybe disappear or the breakage rate exhibits complex non-first-order breakage kinetics during the grinding process. In this study, the influence of grinding media diameter, stirrer tip speed, media fulling rate, and powder filling rate on the uniformity of particle size distribution and specific energy input were studied in a stirred mill. The cumulative undersize distribution of ground products was simulated by the Rosin-Rammler-Benne (RRB) function, from which the parameter k and characteristic particle xe of the RRB function were obtained. The time-dependence of the parameter k was investigated. And, the Walker model for describing the reduction in characteristic particle xe with specific energy input was examined. Based on these results, combining the Walker model with the RRB function to simulate the cumulative undersize distribution of ground products. Thereby, a new cumulative undersize distribution of the prediction model was developed, which was successfully validated by the experimental data against predicted data.