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A DEM-PBM multiscale coupling approach for the prediction of an impact pin mill

机译:用于预测冲击针磨机的DEM-PBM多尺度耦合方法

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Despite many attempts to establish material grindability in a milling process, it remains very difficult to predict the milling performance. In this study, impact milling tests were carried out under varying operational conditions in a UPZ100 impact pin mill. The product size distribution and fineness of milled alumina particle are reported and analyzed. A multiscale framework coupling discrete element method (DEM) and population balance model (PBM) is proposed to predict the milling performance of the mill. The impact velocity and impact frequency information from DEM is utilized to inform the mill operation parameters of the PBM model at the process scale, whilst the material grindability parameters are evaluated using constrained optimization to match a milling lest. The predictions of the product size distribution show very good agreement with the experimental results. This indicates that the multiscale model is promising for optimizing the design and operation of mills. (C) 2020 Published by Elsevier B.V.
机译:尽管许多尝试在铣削过程中建立材料研磨性,但预测铣削性能仍然很困难。在该研究中,在UPZ100冲击销轧机中的不同操作条件下进行冲击铣削测试。报道并分析了研磨氧化铝粒子的产品尺寸分布和细度。提出了一种多尺度框架耦合离散元件方法(DEM)和人口平衡模型(PBM)以预测研磨机的研磨性能。来自DEM的冲击速度和冲击频率信息利用在过程规模上通知轧机操作参数,而使用受约束优化评估材料磨削性参数以匹配铣削以最终匹配。产品尺寸分布的预测表现出与实验结果非常好的一致性。这表明多尺度模型是有希望优化磨机的设计和操作。 (c)2020由elsevier b.v发布。

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