
doi: 10.1002/cjce.23686
AbstractCFD‐DEM combines computational fluid dynamics (CFD), which solves the equation of motion of gas or liquids, with the discrete element method (DEM), a simulation technique based on a Lagrangian description of particle motion that predicts the flow of granular matter and powders. Resolved CFD‐DEM solves the fluid motion with CFD at a scale smaller than the particle diameter (d p), assuming no‐slip on the particle surface to couple the phases. The fluid solver scale is coarser than d p in unresolved CFD‐DEM and virtual mass, drag, and other solid‐fluid forces couple the phases. Resolved CFD‐DEM is more accurate, but is orders of magnitude more computationally intensive. Unresolved CFD‐DEM predicts solid distribution, pressure loss, mass flow rate, and dense and dilute phase flow patterns when the solid to fluid and fluid to solid coupling between the fluid phase and the solid phase are non‐trivial. Researchers apply CFD‐DEM to predict gas‐fluid dynamics of fluidized beds, spouted beds, hoppers, cyclones, costal erosion, and rock slides. Open source codes, commercial software, and parallel computer architectures have accelerated its adoption in pharmaceutical, agro‐industrial, and reactor design. Current research targets improving the solid‐fluid coupling strategies and multiphysics problems including heat transfer, mass transfer, and chemical reactions within or at the surface of the particles. The field has grown to over 200 indexed articles per year (Web of Science) in 2018. This article is part of a special series dedicated to experimental methods in chemical engineering that reviews the most important concepts, applications, and limitations of each technique.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 60 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 1% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 1% |
