Modeling effectiveness analysis of momentum and heat transfer in a fixed bed silo-dryer through computational fluid-dynamics




The drying procedure is capable of increasing the shelf life of many products, and facilitates its transport and storage. However, in the subsequent stages of the drying, the operation can display inefficiencies. An alternative to mitigate this is the use of a silo-dryer, an equipment that allows the simultaneous drying and storage of the material. Coffee is a product of great importance in the industry, and its market value is linked to the physical and sensorial qualities of the seed. The silo-drier can ensure these qualities through intermittent drying and optimizations in the energy consumption. In this work the operation of a cylindrical silo-dryer through computational fluid-dynamics was analyzed, studying the convergence for different numerical models. The behavior of volumetric fraction, air velocity and seed temperature were qualitatively examined with hot air at the inlet. The simulations were carried out through the software FLUENT® 19.2 using three different numerical models: the Eulerian Multiphase Model for Granular flow with packed bed configuration disabled, the same model but with the packed bed configuration enabled, and the porous zone single-phase modelling. It was found that the momentum relaxation factor influenced the results. Moderately lower factors allowed for faster convergence without significant particle behavior change. Monitoring the mass residue, the enabled packed bed modelling presented lower residuals, while the porous zone modelling presented higher residuals. The packed bed and porous zone modelling reported lower air velocities in comparison to the disabled packed bed modelling, and presented satisfactory heat transfer through the temperature profiles.

Key words: Cfd; Coffee; Drying; Eulerian; Multiphase.


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How to Cite

MATEUS, F. L. B.; PETRI JÚNIOR, I. Modeling effectiveness analysis of momentum and heat transfer in a fixed bed silo-dryer through computational fluid-dynamics. Coffee Science - ISSN 1984-3909, [S. l.], v. 16, p. e161902, 2021. DOI: 10.25186/.v16i.1902. Disponível em: Acesso em: 24 jun. 2022.