Title:
Computational fluid dynamics simulation of sloshing inside beverage cans on a rotary filling machine
Authors:
- Federico Solari
- Natalya Lysova
- Roberto Montanari
- Federico Scano
- Enrico Bedogni
- Gabriele Copelli
Published in:
(2024). ECMS 2024, 38th Proceedings
Edited by: Daniel Grzonka, Natalia Rylko, Grazyna Suchacka, Vladimir Mityushev, European Council for Modelling and Simulation.
DOI: http://doi.org/10.7148/2024
ISSN: 2522-2422 (ONLINE)
ISSN: 2522-2414 (PRINT)
ISSN: 2522-2430 (CD-ROM)
ISBN: 978-3-937436-84-5
ISBN: 978-3-937436-83-8 (CD) Communications of the ECMS Volume 38, Issue 1, June 2024, Cracow, Poland June 4th – June 7th, 2024
DOI:
https://doi.org/10.7148/2024-0394
Citation format:
Federico solari, Natalya lysova, Roberto montanari, Federico scano, Enrico bedogni, Gabriele copelli (2024). Computational fluid dynamics simulation of sloshing inside beverage cans on a rotary filling machine, ECMS 2024, Proceedings Edited by: Daniel Grzonka, Natalia Rylko, Grazyna Suchacka, Vladimir Mityushev, European Council for Modelling and Simulation. doi:10.7148/2024-0394
Abstract:
Sloshing is a critical issue in many industrial contexts. In the food industry, it becomes particularly relevant during the filling of beverage cans and bottles with automatic rotary machines, when the uncapped filled containers move to the transfer star wheel, suddenly changing direction of motion and potentially causing the spilling of the product. Deep knowledge of the system behavior and the fluid dynamics in the domain is essential to guarantee the safety and quality of the final products and of the processing environment. In this study, Computational Fluid Dynamics (CFD) was used to simulate sloshing in beverage cans using two CFD software: commercial ANSYS Fluent and open-source OpenFOAM. Some modeling strategies are explored with the aim of making the simulation more efficient without impacting the results, and an approach for tracking the maximum fluid level in the can is proposed. The modeling methodology was validated by means of an analytical model and by comparing the results calculated by the two software. Finally, operational insights were derived based on the results of a sensitivity analysis carried out by varying the star wheel diameter and the system productivity.
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