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A multiscale DEM-PBM approach for a continuous comilling process using a mechanistically developed breakage kernel
Chemical Engineering Science ( IF 4.1 ) Pub Date : 2018-03-01 , DOI: 10.1016/j.ces.2017.12.016
Nirupaplava Metta , Marianthi Ierapetritou , Rohit Ramachandran

Abstract The population balance approach (PBM) is generally used in the literature to simulate a milling process. The formulation of a breakage kernel to represent particle breakage phenomenon is an important part of the model. This study proposes a methodology to estimate parameters of a breakage kernel that captures material property dependent particle level dynamics through discrete element method (DEM) simulations of a comill process. The DEM model takes into account a threshold impact energy that if exceeded, results in granule breakage. The impact energy distribution data for various size classes and impellor speeds is obtained from DEM. Comill experiments at various impeller speeds result in different observed size distributions and other process variables such as hold up amount, and time required for process to reach steady state. An iterative algorithm is proposed that uses mechanistic information from DEM and process variables from experiments to calibrate the breakage kernel through which material specific kernel parameters are estimated. A multi-scale modeling framework utilizing DEM, PBM as well as experimental data is developed. The framework is implemented to estimate material specific properties using milling experimental data at various impeller speeds. The milled particle size distribution predicted from the model with parameters estimated using this framework, demonstrated excellent agreement with experimental results.

中文翻译:

使用机械开发的破碎内核的连续共铣过程的多尺度 DEM-PBM 方法

摘要 文献中通常使用群体平衡法(PBM)来模拟研磨过程。表示颗粒破碎现象的破碎核的公式化是模型的重要组成部分。本研究提出了一种估计破损内核参数的方法,该方法通过 commill 过程的离散元方法 (DEM) 模拟捕获依赖于材料特性的粒子级动力学。DEM 模型考虑了阈值冲击能量,如果超过该阈值,则会导致颗粒破裂。各种尺寸等级和叶轮速度的冲击能量分布数据是从 DEM 获得的。Comill 在不同叶轮速度下的实验导致观察到的尺寸分布和其他过程变量不同,例如滞留量和过程达到稳定状态所需的时间。提出了一种迭代算法,该算法使用来自 DEM 的机械信息和来自实验的过程变量来校准破损内核,通过该内核估计材料特定内核参数。开发了一个利用 DEM、PBM 以及实验数据的多尺度建模框架。该框架用于使用各种叶轮速度下的铣削实验数据来估计材料的特定属性。使用该框架估计的参数从模型预测的研磨粒度分布与实验结果非常吻合。开发了一个利用 DEM、PBM 以及实验数据的多尺度建模框架。该框架用于使用各种叶轮速度下的铣削实验数据来估计材料的特定属性。使用该框架估计的参数从模型预测的研磨粒度分布与实验结果非常吻合。开发了一个利用 DEM、PBM 以及实验数据的多尺度建模框架。该框架用于使用各种叶轮速度下的铣削实验数据来估计材料的特定属性。使用该框架估计的参数从模型预测的研磨粒度分布与实验结果非常吻合。
更新日期:2018-03-01
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