This research paper presents a comprehensive discrete element method (DEM) examination of the mixing behaviors exhibited by cohesive particles within a twin-paddle blender. A comparative analysis between the simulation and experimental results revealed a relative error of 3.47%, demonstrating a strong agreement between the results from the experimental tests and the DEM simulation. The main focus centers on systematically exploring how operational parameters, such as impeller rotational speed, blender's fill level, and particle mass ratio, influence the process. The investigation also illustrates the significant influence of the mixing time on the mixing quality. To gain a deeper understanding of the DEM simulation findings, an analytical tool called multivariate polynomial regression in machine learning is employed. This method uncovers significant connections between the DEM results and the operational parameters, providing a more comprehensive insight into their interrelationships. The multivariate polynomial regression model exhibited robust predictive performance, with a mean absolute percentage error of less than 3% for both the training and validation sets, indicating a slight deviation from actual values. The model's precision was confirmed by low mean absolute error values of 0.0144 (80% of the dataset in the training set) and 0.0183 (20% of the dataset in the validation set). The study offers valuable insights into granular mixing behaviors, with implications for enhancing the efficiency and predictability of the mixing processes in various industrial applications.

中文翻译：

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双桨搅拌机中粘性颗粒混合行为的分析：DEM 和机器学习应用

本研究论文对双桨搅拌机内粘性颗粒的混合行为进行了全面的离散元方法 (DEM) 检查。模拟与实验结果的对比分析显示，相对误差为3.47%，表明实验测试结果与DEM模拟结果非常吻合。主要重点是系统地探索操作参数（例如叶轮转速、搅拌机的填充水平和颗粒质量比）如何影响该过程。研究还说明了混合时间对混合质量的显着影响。为了更深入地了解 DEM 模拟结果，采用了机器学习中称为多元多项式回归的分析工具。该方法揭示了 DEM 结果与运行参数之间的重要联系，从而更全面地了解它们之间的相互关系。多元多项式回归模型表现出稳健的预测性能，训练集和验证集的平均绝对百分比误差均小于 3%，表明与实际值略有偏差。该模型的精度通过 0.0144（训练集中数据集的 80%）和 0.0183（验证集中数据集的 20%）的低平均绝对误差值得到证实。该研究为颗粒混合行为提供了宝贵的见解，对于提高各种工业应用中混合过程的效率和可预测性具有重要意义。