Statistical modeling of collision frequencies of non-spherical agglomerates

团聚是颗粒物和气溶胶生长的重要机制之一。在颗粒火焰合成的典型工艺条件下，这种生长过程可以很容易地跨越几个数量级，从纳米到微米。颗粒碰撞导致颗粒生长，并根据材料特性和温度的不同而聚集成明显不同的形貌。然而，驱动相对粒子运动和碰撞的机制取决于凝聚体的大小。虽然非常小和非常大的球形粒子的碰撞机制已经被很好地理解，但对于过渡区域中非球形粒子的粒子碰撞还没有得到彻底验证的模型。因此，在本工作中，将对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进行分析和验证。适合于验证的数值模拟需要考虑凝聚体在几个数量级上的增长，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，并且它们需要考虑到分形团聚体形态对生长动力学的影响。由于凝聚体的显著增长，基于小尺度和大尺度之间尺度分离的传统简化不再有效，并且需要解决大范围尺度的问题。该项目的不同之处在于使用了粗粒化方法，允许用较大(较粗)的比例表示最小的比例，并显著减少计算需求。只有通过粗粒化，才能计算出整个长度尺度范围。首先，粗粒化方法将进一步发展，允许直接跟踪所有团聚体，同时解决所有相关的湍流尺度。只有这样，才能对不同大小的团聚体之间的碰撞频率进行明确的分析，并有可能直接评估现有模型的准确性。其次，这些直接模拟的大数据集将被用于自动化粗粒度粒子的附加特征，从而允许减少自由度，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 Conventional simplifications that are based on scale separation between the small and the large scales are no longer valid due to the significant growth of the agglomerates and a wide range of scales needs to be resolved.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.