Shock wave interaction with spherical particles: a particle-resolved numerical study of collective effects

冲击波和固体颗粒之间的相互作用是许多技术相关过程的核心，例如冷气喷涂和基于冲击的药物输送。与此同时，与基本颗粒流问题相关的基本问题仍然知之甚少。例如，由于缺乏高质量的数据，尚不清楚集体效应（遮蔽）是否导致格局的形成，以及这种格局如何对全球气流演变产生反馈。因此，工程型模型尚不能忠实地再现受冲击的流体-颗粒系统的相关特征。在这个项目中，我们的目标是填补空白，在目前的艺术状态进行粒子分辨数值模拟的平面冲击波扫过的窗帘上的数千个自由移动的球形粒子。为此目的，我们将对可压缩流采用浸入边界法，允许使用简单的固定网格。大规模模拟将主要集中在无粘性（欧拉）方程，并进行额外的Navier-Stokes运行，以衡量粘性效应在以后的重要性。高保真数据集将使我们能够分析粒子运动的统计和结构特征以及组织间液流，以促进我们对此类系统中集体效应背后机制的理解。这项研究将进一步铺平道路，改进降阶建模，特别是在欧拉-拉格朗日点粒子方法的框架。

The interaction between shock waves and solid particles is at the core of a number of technologically relevant processes such as cold gas spray coating and shock-based drug delivery. At the same time fundamental questions related to the basic particulate flow problem are still poorly understood. For example, due to lack of high-quality data it is not clear whether collective effects (sheltering) lead to pattern formation and how this feeds back upon the global flow evolution. As a consequence, engineering-type models are not yet capable of faithfully reproducing the relevant features of shocked fluid-particle systems. In this project we are aiming to fill a gap in the current state of the art by performing particle-resolved numerical simulation of planar shock waves sweeping over a curtain of thousands of freely-mobile spherical particles. For this purpose we will use an immersed boundary method for compressible flow, allowing the use of a simple fixed grid. The large-scale simulations will mainly focus on the inviscid (Euler) equations, with additional Navier-Stokes runs in order to gauge the importance of viscous effects at later times. The high-fidelity data-sets will enable us to analyze the statistics and structural features of the particle motion as well as the interstitial fluid flow in order to advance our understanding of the mechanisms behind collective effects in such systems. This study will further pave the way for improved reduced-order modeling, in particular in the framework of the Eulerian-Lagrangian point-particle approach.