Conference article

Solving the population balance equation for granulation processes: particle layering and agglomeration

Ludmila Vesjolaja
Department of Electrical Engineering, IT and Cybernetics, University of South-Eastern Norway

Bjørn Glemmestad
Process Modeling and Control Department, Yara Technology Center, Norway

Bernt Lie
Department of Electrical Engineering, IT and Cybernetics, University of South-Eastern Norway

Download articlehttps://doi.org/10.3384/ecp20176180

Published in: Proceedings of The 61st SIMS Conference on Simulation and Modelling SIMS 2020, September 22-24, Virtual Conference, Finland

Linköping Electronic Conference Proceedings 176:25, p. 180-187

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Published: 2021-03-03

ISBN: 978-91-7929-731-2

ISSN: 1650-3686 (print), 1650-3740 (online)

Abstract

Granulation processes are frequently used in the fertilizer industry to produce different grades of mineral fertilizers. Large recycle ratios and poor product quality control are some of the problems faced by such industries. Thus, for real time model based process control and optimization, it is necessary to ?nd an appropriate numerical scheme can find solution of the model sufficiently accurate and fast. In this study, population balance principles were used to model particle granulation processes. Different numerical schemes were tested to find simple yet sufficiently accurate solution schemes for population balance equation. Numerical schemes were applied to find the solution of both the layering term and the agglomeration term that appear in the population balance equation. The accuracies of the numerical schemes were assessed by comparing the numerical results with analytical, tractable solutions. Comparison of the accuracy of numerical schemes showed that a high resolution scheme with Koren flux limiter function might be a good choice for the layering term discretization, while a cell averaging technique and a new finite volume method of Kumar et al. produce a sufficiently accurate solution for the agglomeration term discretization.

Keywords

population balance, numerical scheme, layering, agglomeration

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