A Fast and Improved Tunable Aggregation Model for Stochastic Simulation of Spray Fluidized Bed Agglomeration

Abhinandan Kumar Singh and Evangelos Tsotsas
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Abhinandan Kumar Singh: Thermal Process Engineering, Faculty of Process and Systems Engineering, Otto von Guericke University, Universitätsplatz 2, 39106 Magdeburg, Germany
Evangelos Tsotsas: Thermal Process Engineering, Faculty of Process and Systems Engineering, Otto von Guericke University, Universitätsplatz 2, 39106 Magdeburg, Germany

Energies, 2021, vol. 14, issue 21, 1-18

Abstract: Agglomeration in spray fluidized bed (SFB) is a particle growth process that improves powder properties in the chemical, pharmaceutical, and food industries. In order to analyze the underlying mechanisms behind the generation of SFB agglomerates, modeling of the growth process is essential. Morphology plays an imperative role in understanding product behavior. In the present work, the sequential tunable algorithm developed in previous studies to generate monodisperse SFB agglomerates is improved and extended to polydisperse primary particles. The improved algorithm can completely retain the given input fractal properties (fractal dimension and prefactor) for polydisperse agglomerates (with normally distributed radii of primary particles having a standard deviation of 10% from the mean value). Other morphological properties strongly agreed with the experimental SFB agglomerates. Furthermore, this tunable aggregation model is integrated into the Monte Carlo (MC) simulation. The kinetics of the overall agglomeration at various operating conditions, like binder concentration and inlet fluidized gas temperature, are investigated. The present model accurately predicts the morphological descriptors of SFB agglomerates and the overall kinetics under various operating parameters.

Keywords: agglomeration; morphology; Monte Carlo; tunable aggregation model; polydisperse primary particles (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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