Publication type: Conference other
Type of review: Peer review (abstract)
Title: Eliminating anomalies of CFD model results of the powder coating process by refining aerodynamic flow-particle interaction and by introducing a dynamic particle charging model
Authors: Boiger, Gernot Kurt
DOI: 10.4172/2168-9873-C1-017
Published in: Journal of Applied Mechanical Engineering
Proceedings: Scientific tracks & abstracts : day 1
Volume(Issue): 2018
Issue: 7
Conference details: 3rd International Conference on Fluid Dynamics & Aerodynamics, Berlin, Germany, 25-26 October 2018
Issue Date: Oct-2018
Publisher / Ed. Institution: conferenceseries.com
Publisher / Ed. Institution: London
ISSN: 2168-9873
Language: English
Subjects: Powder coating; OpenFoam; Simulation; CFD; RAS; Algorithm
Subject (DDC): 530: Physics
Abstract: A computational fluid dynamic model of the powder coating process has been developed using OpenFoamĀ®. It considers particle-dynamic-, aerodynamic-, electro-static- and gravitational effects. While being fully functional, the Eulerian-LaGrangian model has in some cases shown anomalies, yielding coating predictions, which were not observed in comparable experiments. In order to analyse and amend the problem, the underlying Reynolds Average Stress (RAS) turbulence modelling approach was (i) re-evaluated, compared to (ii) Direct Numerical Simulation (DNS) and (iii) Large Eddie Simulation (LES) flow modelling methods, (iv) improved to account for turbulence impact on flow-particle interaction and (v) extended by a dynamic particle charging algorithm. The effects of the said model improvements were investigated and model-results were compared to measurements of experimentally obtained coating thickness values. It can be shown that the modified simulation model yields a much higher level of correspondence to experiments than previous versions.
URI: https://digitalcollection.zhaw.ch/handle/11475/14445
Fulltext version: Published version
License (according to publishing contract): Licence according to publishing contract
Departement: School of Engineering
Organisational Unit: Institute of Computational Physics (ICP)
Appears in collections:Publikationen School of Engineering

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Boiger, G. K. (2018). Eliminating anomalies of CFD model results of the powder coating process by refining aerodynamic flow-particle interaction and by introducing a dynamic particle charging model [Conference presentation]. Journal of Applied Mechanical Engineering, 2018(7). https://doi.org/10.4172/2168-9873-C1-017
Boiger, G.K. (2018) ‘Eliminating anomalies of CFD model results of the powder coating process by refining aerodynamic flow-particle interaction and by introducing a dynamic particle charging model’, in Journal of Applied Mechanical Engineering. London: conferenceseries.com. Available at: https://doi.org/10.4172/2168-9873-C1-017.
G. K. Boiger, “Eliminating anomalies of CFD model results of the powder coating process by refining aerodynamic flow-particle interaction and by introducing a dynamic particle charging model,” in Journal of Applied Mechanical Engineering, Oct. 2018, vol. 2018, no. 7. doi: 10.4172/2168-9873-C1-017.
BOIGER, Gernot Kurt, 2018. Eliminating anomalies of CFD model results of the powder coating process by refining aerodynamic flow-particle interaction and by introducing a dynamic particle charging model. In: Journal of Applied Mechanical Engineering. Conference presentation. London: conferenceseries.com. Oktober 2018
Boiger, Gernot Kurt. 2018. “Eliminating Anomalies of CFD Model Results of the Powder Coating Process by Refining Aerodynamic Flow-Particle Interaction and by Introducing a Dynamic Particle Charging Model.” Conference presentation. In Journal of Applied Mechanical Engineering. Vol. 2018. London: conferenceseries.com. https://doi.org/10.4172/2168-9873-C1-017.
Boiger, Gernot Kurt. “Eliminating Anomalies of CFD Model Results of the Powder Coating Process by Refining Aerodynamic Flow-Particle Interaction and by Introducing a Dynamic Particle Charging Model.” Journal of Applied Mechanical Engineering, vol. 2018, no. 7, conferenceseries.com, 2018, https://doi.org/10.4172/2168-9873-C1-017.


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