Large-scale simulations of fully resolved complex moving geometries with partially saturated cells

We employ the Partially Saturated Cells Method to model the interaction between the fluid flow and solid moving objects as an extension to the conventional lattice Boltzmann method. We introduce an efficient and accurate method for mapping complex moving geometries onto uniform Cartesian grids suitable for massively parallel processing. A validation of the physical accuracy of the solid–fluid coupling and the proposed mapping of complex geometries is presented. The implementation is integrated into the code generation pipeline of the waLBerla framework so that highly optimized kernels for Central Processing Unit (CPU) and Graphical Processing Unit (GPU) architectures become available. We study the node-level performance of the automatically generated solver routines. 71% of the theoretical peak performance can be achieved on CPU nodes and 86% on GPU accelerated nodes. Only a moderate overhead is observed for the processing of the solid–fluid coupling when compared to the fluids simulations without moving objects. Finally, a counter-rotating open rotor is presented as a prototype industrial scenario, resulting in a mesh size involving up to 4.3 × 109 fluid grid cells. For this scenario, excellent parallel efficiency is reported in a strong scaling study on up to 32 768 CPU cores on the LUMI-C supercomputer and on up to 1024 NVIDIA A100 GPUs on the JUWELS Booster system.