Kernel identification in continuous fluidized bed spray agglomeration from steady state data

[Display omitted] •Population balance modeling of continuously operated fluidized bed spray agglomeration process.•Model adaption to experimental data and analysis of model parameter inference.•Identification of functional dependencies of agglomeration kernel on process parameters from experimental...

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Bibliographic Details
Published in:Advanced powder technology : the international journal of the Society of Powder Technology, Japan Japan, 2021-07, Vol.32 (7), p.2517-2529
Main Authors: Otto, Eric, Dürr, Robert, Strenzke, Gerd, Palis, Stefan, Bück, Andreas, Tsotsas, Evangelos, Kienle, Achim
Format: Article
Language:English
Subjects:
Agglomeration kernel
Continuous spray agglomeration
Kapur kernel
Parameter identification
Population balance equation
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Summary:[Display omitted] •Population balance modeling of continuously operated fluidized bed spray agglomeration process.•Model adaption to experimental data and analysis of model parameter inference.•Identification of functional dependencies of agglomeration kernel on process parameters from experimental data. Fluidized bed spray agglomeration is an important industrial particle formation process. In particular, the continuous operation mode is able to provide a constant stream of product particles with constant quality in terms of particle properties. Mathematical process modeling represents a valuable tool for a thorough analysis of the involved mechanistic processes and can further be used for process intensification and control. Sophisticated models describing the quantitative effect of process conditions on particle properties are particularly important. Therefore, in this contribution the influence of the seven most important operational parameters on the particle size distribution is modeled, including fluidization and binder properties. To this end, a population balance process model with the three-parametric Kapur kernel is fitted to experimental data. The first main result of this contribution is the quantitative description of the dependency between the agglomeration rate and the process conditions by multidimensional paraboloids. The second main result is the introduction of a general method by which this quantitative formulation is obtained.
ISSN:0921-8831
1568-5527
DOI:10.1016/j.apt.2021.05.028