Statistical modeling of collision frequencies of non-spherical agglomerates

团聚是颗粒和气溶胶生长的关键机制之一。在典型的粒子火焰合成工艺条件下，这种生长过程可以很容易地跨越几个数量级，从纳米尺度到微尺度。粒子碰撞导致粒子生长，并根据材料性能和温度的不同，形成具有明显不同形态的团块。然而，驱动粒子相对运动和碰撞的机制取决于团聚体的大小。虽然非常小和非常大的球形颗粒的碰撞机制已经被很好地理解，但对于过渡区非球形颗粒的碰撞，还没有经过彻底验证的模型。在目前的工作中，将分析和验证颗粒火焰合成中典型尺寸的非球形团聚体碰撞频率的新模型。适合验证的数值模拟需要允许团块生长跨越几个数量级，它们需要考虑所有相关长度尺度的正确比例，例如初级颗粒直径和湍流长度尺度，并且它们需要考虑分形团块形态对生长动力学的影响。由于团聚体的显著增长，基于小尺度和大尺度分离的传统简化不再有效，需要解决大范围尺度的问题。该项目的区别在于使用了粗粒度方法，该方法允许用更大（更粗）的尺度表示最小的尺度，并显著减少计算需求。只有通过粗粒度化，才能计算出长度尺度的整个范围。首先，将进一步发展粗粒度方法，以便在解决所有相关湍流尺度的同时直接跟踪所有团块。只有这样，才能对不同大小团块之间的碰撞频率进行明确的分析，并对现有模型的准确性进行直接评估。其次，这些直接模拟的大型数据集将用于自动化粗粒度粒子的附加特征，从而降低自由度，并使用深度学习方法生成碰撞频率的替代模型。

Agglomeration is one of the key mechanisms for particle and aerosol growth. This growth process can easily span several orders of magnitude from the nanoscale to the microscale under process conditions that are typical for particle flame synthesis. Particle collision leads to particle growth and – depending on material properties and temperature – to agglomerate with clearly varying morphology. The mechanisms, however, that drive relative particle motion and collision depend on the agglomerates’ size. While collision mechanisms for very small and very large, spherical particles are well understood, there is no thoroughly validated model for particle collision of non-spherical particles in the transition region. In the present work, new models for collision frequencies of non-spherical agglomerates at sizes typical for particle flame synthesis will therefore be analysed and validated.Numerical simulations suitable for validation need to allow for agglomerate growth across several orders of magnitude, they need to account for the correct ratio of all relevant length scales such as primary particle diameter and turbulent length scales, and they need allow for effects of fractal agglomerate morphology on growth dynamics. Conventional simplifications that are based on scale separation between the small and the large scales are no longer valid due to the significant growth of the agglomerates and a wide range of scales needs to be resolved. The distinction of the project is the use of a coarse-graining approach that allows to represent the smallest scales by larger (coarser) scales and to significantly reduce computational requirements. Only by coarse-graining, the entire range of length scales can be computed.Firstly, the coarse-graining approach will be further developed to allow for a direct tracking of all agglomerates while resolving all relevant turbulent scales. Only then, an explicit analysis of collision frequencies between agglomerates of different sizes can be conducted and direct evaluation of the accuracy of existing models is possible. Secondly, the large data sets of these direct simulations will be used to automatize the additional characteristics of the coarse-grained particles that allow for the reduction in the degrees of freedom and to generate alternative models for the collision frequencies using deep learning methods.