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Multiphysics simulation-based investigation of electro-static precipitation phenomena in the context of coating standard automotive rims
- Publication Year :
- 2024
-
Abstract
- In this extended study, electrostatic precipitation, a cornerstone technology in industrial coating applications, is examined with enhanced depth and breadth, targeting its applicability in coating standard automotive rims. Utilizing an advanced Eulerian- Lagrangian, Extended Discrete Element Method, Finite Volume solver constructed within the OpenFOAM CFD-framework, we present a holistic computational model that incorporates various facets such as airflow dynamics, coating-particle interactions, and intricate particle-substrate phenomena like blow-off and corona formation. Enabled by Massive Simultaneous Cloud Computing technology, our solver permits concurrent exploration of a wide array of industrially relevant conditions. This research goes beyond earlier studies by encompassing not only variations in "Mean Powder Particle Diameters" and "Powder Particle Density," but also conducting a more expansive simulation sweep that incorporates changes in "Particle Diameter Deviation" and "Applied Voltage." This allows for a nuanced understanding of sensitivities and uncertainties linked to these parameters. We apply this comprehensive modeling approach to scrutinize single-burst powder coating on a typical metallic, automotive rim substrate. The study delivers intricate predictions and visualizations of coating patterns, efficiencies, and homogeneity across a range of conditions. Our findings offer valuable insights for optimizing powder properties, which hold considerable implications for material suppliers in the coating industry. Despite these advances, certain limitations remain, underscoring the need for further research in this vital domain.
Details
- Database :
- OAIster
- Notes :
- 18th International Conference of Multiphysics, Graz, Austria, 14-15 December 2023, English
- Publication Type :
- Electronic Resource
- Accession number :
- edsoai.on1427411853
- Document Type :
- Electronic Resource