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过程工程学报 ›› 2026, Vol. 26 ›› Issue (10): 1069-1078.DOI: 10.12034/j.issn.1009-606X.225328

• 研究论文 • 上一篇    下一篇

基于CFD-DEM的螺旋气流磨颗粒破碎行为建模与预测

张福宁， 杜少华， 周强*   

  1. 西安交通大学化学工程与技术学院，陕西 西安 710049
  • 收稿日期:2025-12-29 修回日期:2026-03-09 出版日期:2026-10-28 发布日期:2026-10-28
  • 通讯作者: 周强 zhou.590@mail.xjtu.edu.cn
  • 基金资助:
    国家自然科学基金;国家自然科学基金;中央高校基本科研业务费

Modeling and prediction of particle breakage behavior in spiral jet mill based on CFD-DEM

Funing ZHANG,  Shaohua DU,  Qiang ZHOU*   

  1. School of Chemical Engineering and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, China
  • Received:2025-12-29 Revised:2026-03-09 Online:2026-10-28 Published:2026-10-28
  • Contact: Qiang Zhou zhou.590@mail.xjtu.edu.cn
  • Supported by:
    National Natural Science Foundation of China;National Natural Science Foundation of China;Fundamental Research Funds for the Central Universities

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摘要： 螺旋气流磨作为一种高效超细粉碎设备，在化工、材料、医药等领域具有广泛应用，其粉碎性能直接决定了产品的质量和能耗水平。在螺旋气流磨中，颗粒的破碎行为复杂，同时受碰撞频率和冲击能量的综合影响，因此准确预测该过程中不同阶段的颗粒破碎率及产物粒径分布是研究装置性能、评估粉碎效率的关键前提。基于此，本工作提出了一种基于计算流体动力学-离散元方法(Computational Fluid Dynamics-Discrete Element Method, CFD-DEM)的耦合模拟与建模方法，通过获取颗粒冲击能量分布，能够对长周期运行下螺旋气流磨内的颗粒破碎率及产品粒径分布进行有效预测。该方法首先依据CFD-DEM模拟结果统计得到颗粒碰撞能量的概率密度及其累积分布，在此基础上通过蒙特卡洛随机碰撞模拟生成各颗粒在整个运行周期中的累计碰撞能量序列；随后建立基于碰撞频率和冲击能量的颗粒破碎率与产物粒径分布关联模型，并通过实验数据对模型参数进行标定验证。结果表明，该方法不仅能揭示磨腔内颗粒的运动、分布与碰撞细节，还可在长周期条件下较准确预测颗粒破碎率与粒径分布变化规律，从而为不同操作条件下的粉碎性能预测与工业级螺旋气流磨的设计优化与工艺调控提供可靠的预测模型和理论支撑。

关键词: 螺旋气流磨, 离散元方法, 冲击能量分布, 颗粒破碎, 粒径分布

Abstract: As a highly efficient ultrafine grinding equipment, the spiral jet mill has been widely applied in the fields of chemical engineering, materials, and medicine. Its grinding performance directly determines the quality of the product and the energy consumption level. In the spiral jet mill, the particle breakage behavior is complex and is simultaneously influenced by the collision frequency and collision energy. Therefore, accurately predicting the particle breakage rate and product particle size distribution at different stages of the process is a key prerequisite for studying the performance of the device and evaluating the grinding efficiency. Based on this, this work proposes a coupled simulation and modeling method based on computational fluid dynamics-discrete element method (CFD-DEM). By obtaining the distribution of particle impact energy, it can effectively predict the particle breakage rate and product particle size distribution in the spiral jet mill under long-term operation. This method first statistically obtains the probability density and cumulative distribution of particle collision energy based on the CFD-DEM simulation results. On this basis, a cumulative collision energy sequence of each particle throughout the operation cycle is generated through Monte Carlo random collision simulation. Subsequently, a correlation model between the particle breakage rate and product particle size distribution based on collision frequency and impact energy is established, and the model parameters are calibrated and verified through experimental data. The results show that this method can not only reveal the movement, distribution, and collision details of particles in the grinding chamber but also accurately predict the variation laws of particle breakage rate and particle size distribution under long-term conditions, thereby providing a reliable prediction model and theoretical support for the performance prediction of grinding under different operating conditions and the design optimization and process control of industrial-scale spiral jet mills.

Key words: spiral jet mill, discrete element method, impact energy distribution, particle breakage, particle size distribution