Multi-scale investigation on the mobility effect of spherical and non-spherical particles as part of disperse solid/fluid systems with respect to momentum and heat exchange

研究分散固液两相流动的一个核心问题是详细分析分散相的存在引起的流场行为和现象。在稠密颗粒-流体流动中，需要准确地描述两相之间的动量和热传递，这可以通过颗粒分辨直接数值模拟(PR-DNS)得到。当颗粒被允许移动时，这些流动的复杂性增加，例如在流态化床中，而不是静态颗粒集合，例如填充床。在这些动态和密集的粒子系统中，粒子速度的波动和局部粒子分布的不均匀被称为迁移率效应。最近的研究表明，迁移率效应对球形颗粒的动量和热传递有不可忽视的影响，但仍然缺乏对关联的严格包含，对于非球形颗粒和耦合热传递更是如此。拟议研究工作的目的是为涉及热传递的气/固流动的PR-DNS数据提供更广泛的基础，在这种流动中，颗粒可以自由移动。PR-DNS首次在广泛的参数范围(雷诺数、斯托克斯数、固体体积分数)上严格考虑了流动效应，得到了动量和换热的关联式。这些新关联式的主要创新之处将是使用相对粒子位置和速度信息基于每个粒子来计算动量和热传递，对于这两种方法，都采用了基于物理的核平滑方法和基于人工神经网络的方法。因此，由单个颗粒周围的局部流动产生的横向颗粒/流体力也被固有地捕捉到，这是现有的体积平均模型所不能描述的。为了量化新关联式相对于传统关联式的益处，我们将使用未解析的DEM-CFD方法和PR-DNS法进行涉及传热的沸腾床模拟。通过比较积分参数的模拟，我们将能够评估考虑迁移率影响的重要性。在项目的第二部分，我们对涉及选定的非球形粒子(球柱体、立方体、扁圆形)的颗粒-流体流动重复这一过程。这些模拟将首次深入了解颗粒形状和颗粒流动效果之间的关系，并将为更准确地闭合铺平道路，此外还考虑了粗糙度。

A core theme in the study of disperse solid/fluid flows is the detailed analysis of the flow field behavior and the phenomena induced by the presence of the dispersed phase. In dense particle-fluid flows an accurate description of the momentum and heat transfer between the two phases is desirable and can be derived from particle-resolved direct numerical simulations (PR-DNS). The complexity of these flows increases when particles are allowed to move, such as in fluidized beds in contrast to static particle ensembles such as packed beds. In these dynamic and dense particle systems, particle velocity fluctuations and inhomogeneities in the local particle distribution occur, which are referred to as mobility effects. Very recent studies have shown that mobility effects have a non-negligible influence on momentum and heat transfer of spherical particles, but a rigorous inclusion into correlations is still lacking, which is even more the case for non-spherical particles and coupled heat transfer. The objective of the proposed research work is to contribute to a broader base of PR-DNS data for gas/solid flows involving heat transfer, where particles are allowed to move freely. The PR-DNS serve to derive correlations for momentum and heat transfer that rigorously take into account mobility effects over a wide range of parameters (Reynolds number, Stokes number, solid volume fraction) for the first time. The key novelty of these new correlations will be the computation of momentum and heat transfer based on a per particle basis using relative particle position and velocity information, for which both, a physics based kernel smoothing approach and an approach based on an artificial neural network, are applied. Thereby, transversal particle/fluid forces arising from the local flow around individual particles are also inherently captured, which are insufficiently described by existing volume-averaged models. In order to quantify the benefit of the new correlations over conventional correlations, we will perform fluidized bed simulations involving heat transfer using the unresolved DEM-CFD approach and the PR-DNS approach. By comparing the simulations with respect to integral parameters, we will be able to assess the importance of considering mobility effects. In the second part of the project, we repeat this procedure for particle-fluid flows involving selected non-spherical particles (sphero-cylinder, cube, oblate). These simulations will allow insights into the relationship between particle shape and particle mobility effects for the first time and will pave the way for more accurate closures additionally taking into account the aspericity.