颗粒流体系统是一个具有时空多尺度结构的复杂系统，其中，颗粒聚团是一种常见的非均匀结构。聚团的特性对于流化床等各类反应器的正常运行具有重要影响。目前人们对于聚团的研究局限于参数影响的考察以及聚团尺寸的宏观理论分析，其结构特性与机理均有待进一步研究。本文利用离散颗粒模型（DPM）模拟了含有数百万个粘附性颗粒的液固体系，提出了一种适于DPM模拟的聚团识别和量化方法。这种方法可以充分发挥DPM模拟能够精确量化任意时刻每一个颗粒速度和位置的优势，从聚团的尺寸、形状、稳定性角度表征其结构特征，通过跟踪颗粒进入或离开聚团的状态量化聚团生长和破碎的过程，从颗粒受力的角度探究聚团生长与破碎的机理。第二章总结了离散颗粒模型及其求解方法，介绍了实验装置及模拟参数的设置。在实验和模拟中均观察到聚团现象，且反应器中心区域的颗粒平均速度与颗粒体积分数在实验和模拟中基本一致。第三章提出了一种适于DPM模拟的聚团定义，探究了反应器厚度、进料状态、粘附力系数对模拟结果的影响，从尺寸、形状、稳定性三个角度考察了聚团的结构特征。聚团内颗粒数目可以表示聚团尺寸的大小，聚团内颗粒的平均配位数及配位数分布可以表示聚团的形状，配位颗粒的平均表面距离及颗粒在聚团内的平均停留时间可以表示聚团的稳定性。第四章提出了聚团生长与破碎的定义，对聚团的生长率和破碎率进行了量化，研究表明聚团的生长与破碎的过程可能以循序渐进或者突变的方式进行，绝大部分聚团的生长与破碎都以循序渐进的方式进行。找到了生长与破碎平衡时的聚团尺寸，这一平衡点与聚团内颗粒数最大概率处一致，这一结论在不同的条件下均得到验证。分别考察了粘附力、曳力、碰撞力对聚团净变化率、尺寸、形状的不同影响。这种方法适于量化DPM模拟的粘性颗粒形成的聚团，对于进一步探究聚团的内在机理具有一定价值。第五章对本文进行了总结同时展望了未来的研究方向。;The particle-fluid flow featuring spatio-temporal multi-scale structures are typically complex systems, in which agglomerates are common inhomogeneous structures. The characteristic of agglomerates has a significant effect on the normal operation of fluidized bed or other reactors. At present, the research on agglomerates is limited to the influence of the parameters and the macroscopic theoretical analysis of the sizes. Therefore, the structural characteristics of agglomerates as well as the mechanism of growth and breakage need to be further investigated.In this paper, a fluid-particle flow including millions of cohesive particles is simulated by the discrete particle model (DPM). A method for determining and quantifying the agglomerates based on DPM is proposed. Taking full advantage of DPM that the location and velocity of any particles at any moment can be tracked, the structure of the agglomerates are characterized by the size, shape and stability of the agglomerates, the state of particles entering or leaving agglomerates can be tracked, the growth and breakage process of all agglomerates therefore can be monitored quantitatively, the mechanism of growth and breakage of agglomerates is then explored in terms of force analysis.In chapter 2, we introduce the physical model, the computational implementation, the experiment and simulation layout. The agglomerates are observed in both experiment and simulation. The average velocity as well as the volume fraction of particles in the central region of the reactor has a fair agreement between the experiment and the simulation.In chapter 3, a method for determining agglomerates based on DPM is proposed, the influences of the reactor thickness, feed state, and cohesive coefficient on the results are explored, and the structure characteristics of agglomerates are investigated from the aspects of size, shape and stability. The number of particles in the agglomerates represents the size of the agglomerates, the average coordination number and the distribution of coordination number of particles in the agglomerates indicate the shape of the agglomerates, and the average surface distance of coordination particles and the average residence time of particles in agglomerates indicate the stability of the agglomerates.In chapter 4, we put forward the definition of the growth and breakage of agglomerates, and quantify the growth rate and breakage rate of agglomerates. It is found that the process of growth and breakage of agglomerates may proceed in a continuous or abrupt manner, and most of them are continuous. The balance size of the growth and the breakage of agglomerates mark the most probable agglomerate size, which is verified in different conditions. The influence of series parameters including cohesive force, drag force, collision force on the net change rate, size and shape of agglomerates are investigated. This method is suitable for quantifying the agglomerates of cohesive particles in DPM simulation, and it is of some value for further exploring deeply in the inner mechanism of agglomerates.In chapter 5, we summarize the main conclusions and present the perspective of the work.