(133d) Large-Scale DEM-CFD Method for an Industrial Fluidized Bed

Authors: 
Mori, Y. - Presenter, The University of Tokyo
Sakai, M., School of Engineering, the University of Tokyo
Numerical simulations of fluidized bed are often performed for the better understanding of complex phenomena. In these numerical simulations, Eulerian-Lagrangian approach [1] is often employed, where solid and fluid phases are modeled by discrete element method (DEM) and computational fluid dynamics (CFD), respectively. Indeed, the DEM-CFD method is applied to various solid-fluid coupling problems. Adequacy of the DEM-CFD method is proven not only in a gas-solid flow system such as a fluidized bed [2,3] but also a wet ball mill [4,5]. Although the DEM-CFD method seems to be established, there is a couple of critical problems such as substantial limit of number of calculated particles and difficulty for stable computation for a gas-solid flow in a complex-shaped boundary. In order to solve these problems, we develop a new methodology that is referred to as DEM-CGM-CDF-SDF-IBM method. In the DEM-CGM-CFD-SDF-IBM method, signed distance function (SDF) [6] and immersed boundary model [7] are used for boundary wall of solid and fluid phases. The coarse grain model (CGM) [8] of the DEM is employed as the scaling law model, where a model particle represents a group of original particles. To show adequacy of the DEM-CGM-CDF-SDF-IBM method, a validation test is performed in a fluidized bed. In the simulation, 200,000 spherical particles whose density, original particle diameter and coarse grain ratio are, respectively, 2500 kg/m3, 0.1 mm and 5. Experiments are performed under fair conditions of the numerical simulations. It is shown that the DEM-CGM-CDF-SDF-IBM method can simulate the bed height and pressure drop obtained from the oroginal system accurately through the validation test. Consequently, we conclude that the DEM-CGM-CDF-SDF-IBM method can simulate industrial scale fluidized bed, and hope that our method becomes standard in numerical simulation method in industrial systems.

References

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[8] M. Sakai and S. Koshizuka, Chem. Eng. Sci., 64, 533-539 (2009)

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