LAPSE:2018.0201
Published Article
LAPSE:2018.0201
Computational Fluid Dynamics (CFD)-Based Droplet Size Estimates in Emulsification Equipment
Jo Janssen, Roy Mayer
July 30, 2018
While academic literature shows steady progress in combining multi-phase computational fluid dynamics (CFD) and population balance modelling (PBM) of emulsification processes, the computational burden of this approach is still too large for routine use in industry. The challenge, thus, is to link a sufficiently detailed flow analysis to the droplet behavior in a way that is both physically relevant and computationally manageable. In this research article we propose the use of single-phase CFD to map out the local maximum stable droplet diameter within a given device, based on well-known academic droplet break-up studies in quasi-steady 2D linear flows. The results of the latter are represented by analytical correlations for the critical capillary number, which are valid across a wide viscosity ratio range. Additionally, we suggest a parameter to assess how good the assumption of quasi-steady 2D flow is locally. The approach is demonstrated for a common lab-scale rotor-stator device (Ultra-Turrax, IKA-Werke GmbH, Staufen, Germany). It is found to provide useful insights with minimal additional user coding and little increase in computational effort compared to the single-phase CFD simulations of the flow field, as such. Some suggestions for further development are briefly discussed.
Keywords
Computational Fluid Dynamics, droplet size, emulsification modelling, population balance
Suggested Citation
Janssen J, Mayer R. Computational Fluid Dynamics (CFD)-Based Droplet Size Estimates in Emulsification Equipment. (2018). LAPSE:2018.0201
Author Affiliations
Janssen J: Unilever R&D Vlaardingen, Olivier van Noortlaan 120, 3133AT Vlaardingen, The Netherlands
Mayer R: FlowMotion, Leeghwaterstraat 21, 2628CA Delft, The Netherlands
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Journal Name
Processes
Volume
4
Issue
4
Article Number
E50
Year
2016
Publication Date
2016-12-13
Published Version
ISSN
2227-9717
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PII: pr4040050, Publication Type: Journal Article
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LAPSE:2018.0201
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doi:10.3390/pr4040050
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Jul 30, 2018
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