GPU-accelerated CFD–DEM coupling strategy for large-scale solid–liquid–gas flows in moving mesh systems, with application to wet grinding in an autogenous mill

Large-scale CFD–DEM simulations are often constrained by high computational costs, particularly for multiphase flows with moving mesh systems, which restricts their application to full-scale industrial systems. In this work, a fully GPU-based coupling strategy was developed within a CPU–GPU hybrid CFD–VOF–DEM framework. This strategy incorporated a bounding-box method for efficient dynamic cell mapping, achieving an 800 × speedup in particle-to-cell identification, enabling rapid retrieval of flow-field information and exchange momentum and volume fractions within moving mesh systems, supporting large-scale multiphase simulation. To demonstrate its practical utility, the model was validated and applied to simulate the wet grinding in a full-scale autogenous grinding (AG) mill and examine particle size effects. For the wet grinding case involving 10 million particles, a 50-second double-precision simulation was completed in 28 h, with coupling interface accounting for