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

分散固/液流动研究的一个核心主题是详细分析流场行为和由分散相的存在引起的现象。在稠密的颗粒流体流动中，两相之间的动量和热传递的准确描述是可取的，并且可以从颗粒分辨直接数值模拟（PR-DNS）中导出。当允许颗粒移动时，这些流动的复杂性增加，例如与静态颗粒集合（例如填充床）相比，在流化床中。在这些动态和密集的粒子系统中，粒子速度波动和局部粒子分布的不均匀性发生，这被称为迁移率效应。最近的研究表明，流动性效应对球形颗粒的动量和传热有不可忽视的影响，但仍然缺乏严格的相关性，对于非球形颗粒和耦合传热更是如此。拟议的研究工作的目标是有助于更广泛的基础PR-DNS数据的气体/固体流动涉及传热，其中颗粒被允许自由移动。PR-DNS用于推导动量和热传递的相关性，该相关性首次严格考虑了大范围参数（雷诺数，斯托克斯数，固体体积分数）的流动性影响。这些新的相关性的关键新奇将是动量和热传递的计算基于每个粒子的基础上使用相对粒子的位置和速度信息，其中，基于物理的核平滑方法和基于人工神经网络的方法，都适用。因此，横向颗粒/流体力所产生的局部流动周围的个别颗粒也固有地捕获，这是不充分的描述现有的体积平均模型。为了量化新的相关性优于传统相关性的好处，我们将使用未解决的DEM-CFD方法和PR-DNS方法进行涉及传热的流化床模拟。通过比较积分参数的模拟，我们将能够评估考虑流动性影响的重要性。在项目的第二部分，我们重复这个过程的粒子流体流动，涉及选定的非球形粒子（球柱体，立方体，扁圆）。这些模拟将首次深入了解颗粒形状和颗粒流动性效应之间的关系，并将为更准确的闭合铺平道路，同时考虑到粗糙度。

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.