Ji Xu, Peng Zhao, Yong Zhang, Junwu Wang, Wei Ge, 'Discrete particle methods for engineering simulation: Reproducing mesoscale structures in multiphase systems', Resources Chemicals and Materials, Volume 1, Issue 1, Pages 69-79, 2022 https://doi.org/10.1016/j.recm.2022.01.002. (https://www.sciencedirect.com/science/article/pii/S2772443322000022)
Abstract: Most natural resources are processed as particle-fluid multiphase systems in chemical, mineral and material industries, therefore, discrete particles methods (DPM) are reasonable choices of simulation method for engineering the relevant processes and equipments. However, direct application of these methods is challenged by the complex multiscale behavior of such systems, which leads to enormous computational cost or otherwise qualitatively inaccurate description of the mesoscale structures. The coarse-grained DPM based on the energy-minimization multi-scale (EMMS) model, or EMMS-DPM, was proposed to reduce the computational cost by several orders while maintaining an accurate description of the mesoscale structures, which paves the way for its engineering applications. Further empowered by the high-efficiency multi-scale DEM software DEMms and the corresponding customized heterogeneous supercomputing facilities with graphics processing units (GPUs), it may even approach realtime simulation of industrial reactors. This short review will introduce the principle of DPM, in particular, EMMS-DPM, and the recent developments in modeling, numerical implementation and application of large-scale DPM which aims to reach industrial scale on one hand and resolves mesoscale structures critical to reaction-transport coupling on the other hand. This review finally prospects on the future developments of DPM in this direction.
Keywords: Coarse-graining; Discrete element method (DEM); EMMS-DPM (EMMS-based discrete particle method); GPU-CPU heterogeneous computing; Mesoscale