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Development and assessment of algorithms for DEM-LES simulations of fluidized bed
Institution:1. State Key Laboratory of Organic-Inorganic Composites, Beijing University of Chemical Technology, Beijing, 100029, China;2. College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, 100029, China;1. Power and Flow Group, Department of Mechanical Engineering, Eindhoven University of Technology, PO Box 513, 5600MB, Eindhoven, the Netherlands;2. Eindhoven Institute for Renewable Energy Systems (EIRES), PO Box 513, 5600MB, Eindhoven, the Netherlands;1. Chongqing University of Science and Technology, Chongqing, 401331, China;2. Department of Mining and Minerals Engineering, Virginia Tech, Blacksburg, VA, 24061, USA;1. Faculty of Metallurgical and Energy Engineering, Kunming University of Science and Technology, Kunming, 650093, China;2. State Key Laboratory of Complex Nonferrous Metal Resources Cleaning Utilization in Yunnan Province, Kunming, 650093, China
Abstract:The use of high-fidelity Discrete Element Method (DEM) coupled with Computational Fluid Dynamics (CFD) for particle-scale simulations demands extensive simulation times and restricts application to small particulate systems. DEM-CFD simulations require good performance and satisfactory scalability on high-performance computing platforms. A reliable parallel computing strategy must be developed to calculate the collision forces, since collisions can occur between particles that are not on the same processor, or even across processors whose domains are disjoint. The present paper describes a parallelization technique and a numerical verification study based on a number of tests that allow for the assessment of the numerical performance of DEM used in conjunction with Large-Eddy Simulation (LES) to model dense flows in fluidized beds. The fluid phase is computed through solving the volume-averaged four-way coupling Navier-Stokes equations, in which the Smagorinsky sub-grid scale tensor model is used. Furthermore, the performance of Sub-Grid Scale (SGS) turbulence models applied to Fluidized Bed Reactor (FBR) configurations has been assessed and compared. The developed numerical solver represents an interesting combination of techniques that work well for the present purpose of studying particle formation in fluidized beds.
Keywords:DEM-LES  Fluidized bed  Computational efficiency  Numerical accuracy
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