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

格子Boltzmann方法(LBM)是一种成熟的流体模拟方法，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，实现了多种不同的格子Boltzmann方法及其与刚体和多相模型的耦合。该框架以系统的、以性能为导向的开发过程设计，被用于各种不同的应用，如材料科学、医学和过程工程。WaLBerla也是中尺度模拟的基础，该模拟已经作为之前的DFG/AIF集群项目的一部分进行了[模拟von Proteinschäumen]。自然地，从单个气泡到全过程的尺度转换导致对计算能力的巨大需求。为了有效地模拟这类场景，使用了自适应细化网格，这些网格已经在waLBerla框架中可用于单相流。在这个项目中，自适应网格加密和动态负载平衡将扩展到自由表面流动。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，而不会对性能进行折衷。由此产生的高效代码将用于在该项目中模拟柱中的泡沫。塔中不需要的泡沫会导致高压降、可能的通量减少和分离效率降低。为了避免这些不良影响，有必要详细了解相关的泡沫塑料生成和泡沫塑料销毁效果。数值模拟在这方面可以做出重大贡献。在对单个塔填料进行验证模拟的基础上，对塔内的发泡行为进行了模拟和预测。这个项目的主要目标是(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曲面格子Boltzmann(FSLBM)模拟的性能，(Ii)与集群合作伙伴密切合作，设计一个虚拟的但经过实验验证的过程，以及(Iii)将waLBerla流体模拟与CT重建算法相结合，以改进几何重建。

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.