A breakage kernel for use in population balance modelling of twin screw granulation

This paper presents a novel breakage kernel for use in population balance modelling for twin screw granulation (TSG) using mechanistic understanding in different screw elements. Breakage-isolated experiments are conducted using conveying and distributive mixing elements for a range of model formulat...

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Veröffentlicht in:Powder technology 2020-03, Vol.363, p.525-540
Hauptverfasser: Wang, Li Ge, Pradhan, Shankali U., Wassgren, Carl, Barrasso, Dana, Slade, David, Litster, James D.
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Sprache:eng
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Zusammenfassung:This paper presents a novel breakage kernel for use in population balance modelling for twin screw granulation (TSG) using mechanistic understanding in different screw elements. Breakage-isolated experiments are conducted using conveying and distributive mixing elements for a range of model formulations of widely different yield stresses. The breakage kernel, i.e. the selection and breakage functions, are mathematically formed based on the identification of the dominant breakage mechanisms of chipping and fragmentation in the conveying and distributive mixing elements, respectively, and the unique geometries of the two screw elements. A parametric study for the proposed breakage kernel is performed to identify the influential parameters on the breakage kernel. This is the first breakage model specifically developed for a TSG and incorporates a mechanistic understanding of several key parameters, particularly the role of screw geometry. The breakage model is well suited to population balance modelling framework for model-driven design of twin screw granulation. [Display omitted] •A mechanistic-based breakage kernel was developed for twin screw granulation(TSG).•The breakage mechanisms are distinguished based on screw elements.•Two modes of size distribution are considered in the breakage function.•A parametric study of the developed breakage kernel was performed.•This is the first TSG breakage kernel for use in population balance model.
ISSN:0032-5910
1873-328X
DOI:10.1016/j.powtec.2020.01.024