Lattice Boltzmann Methods on Parallel Supercomputers for Computing Mass and Momentum Transport of Foams in Filling Columns

晶格玻尔兹曼方法（LBM）是流体模拟的替代方法，因为它们非常适合于复杂场景的高效直接数值模拟。在开源软件waLBerla中，实现了许多不同的晶格玻尔兹曼方法以及它们与刚体和多相模型的耦合。该框架是在一个系统的、面向性能的开发过程中设计的，用于各种不同的应用，如材料科学、医学和工艺工程。waLBerla也是中尺度模拟的基础，已经作为先前DFG/AiF集群项目“Simulation von Proteinschäumen”的一部分进行了中尺度模拟。当然，从单个气泡到整个过程的规模转换会导致对计算能力的巨大需求。为了有效地模拟这些场景，使用了自适应精细网格，这在waLBerla框架中已经可以用于单相流。在这个项目中，自适应网格细化和动态负载平衡将扩展到自由表面流。此外，元编程技术将用于为现代硬件编写灵活、可移植和可维护的代码，而不会牺牲性能。生成的高效代码将在本项目中用于模拟列中的泡沫。不需要的发泡柱可导致高压降，减少可能的吞吐量和降低分离效率。为了避免这些不良影响，有必要详细了解相关的泡沫产生和泡沫破坏效应。数值模拟可以在这里做出重大贡献。在对单个柱状填料进行有效模拟的基础上，对柱状填料的发泡行为进行了模拟和预测。该项目的主要目标是：(i)通过代码生成技术、自适应网格细化和动态负载平衡来提高自由表面晶格玻尔兹曼（FSLBM）模拟的性能；（ii）与集群伙伴密切合作，虚拟但经过实验验证的过程设计；（iii）将waLBerla流体模拟与CT重建算法相结合，以改善几何重建。

Lattice Boltzmann methods (LBM) are established alternatives for fluid simulation, since they are well suited for efficient direct numerical simulation of complex scenarios. In the open source software waLBerla, many different lattice Boltzmann methods are implemented as well as their coupling to rigid body and multiphase models. The framework, designed in a systematic, performance-oriented development process, is used in a variety of different applications, such as material science, medicine and process engineering. waLBerla is also the basis of the mesoscale simulations that have already been carried out as part of a previous DFG/AiF cluster project `` Simulation von Proteinschäumen''.Naturally the scale transition from the single bubble to the full process results in enormous demand on compute power. To efficiently simulate these kind of scenarios, adaptively refined grids are used, that are available in the waLBerla framework already for single phase flows. In this project adaptive grid refinement and dynamic load balancing will be extended for free surface flows. Additionally, metaprogramming techniques will be used to write flexible, portable and maintainable code for modern hardware without performance tradeoffs.The resulting, highly efficient code will be used in this project to simulate foams in columns. Unwanted foaming in columns can lead to high pressure drops, a reduction in possible throughputs and reduced separation efficiency. To avoid these undesirable effects, a detailed understanding of the relevant foam creation and foam destruction effects is necessary. The numerical simulation can make a significant contribution here. On the basis of validated simulations of individual column fillers, the foaming behavior in a column is simulated and predicted. The main goals of this project are (i) increasing the performance of Free Surface Lattice Boltzmann (FSLBM) simulations through code generation techniques, adaptive grid refinement and dynamic load balancing, (ii) in close cooperation with the cluster partners, a virtual but experimentally validated design of processes and (iii) coupling waLBerla fluid simulations to CT reconstruction algorithms to improve geometry reconstruction.