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A parametric simulation model for HVOF coating thickness control.

Authors :
Ren, Jiangzhuo
Ahmad, Rafiq
Zhang, Guofeng
Rong, Yiming
Ma, Yongsheng
Source :
International Journal of Advanced Manufacturing Technology. Sep2021, Vol. 116 Issue 1/2, p293-314. 22p. 4 Color Photographs, 2 Black and White Photographs, 3 Diagrams, 5 Charts, 14 Graphs.
Publication Year :
2021

Abstract

High-velocity oxygen-fuel (HVOF) thermal spraying is a coating process involving multidisciplinary aspects, e.g., fuel–oxidant combustion, flame–particle jet, particle deposition, mass and heat transfer, and even robotic kinematics. Like most coating processes, in HVOF processes, coating thickness is a significant property determining the coating performance; hence, this property should be accurately controlled during the process. In view of green, smart, and digital manufacturing, the coating thickness prediction model is demanded to produce high-quality coatings efficiently. This paper presents an approach to parametrically simulate the coating thickness in HVOF processes via an integrated numerical model. Firstly, an axisymmetric computational fluid dynamics (CFD) model is constructed to compute the behaviors of the fuel–oxidant combustion, flame–particle jet, and particle deposition distribution. Secondly, based on the particle distribution in a 2D axisymmetric model, a 3D single coating thickness profile model is developed by constructing a circular pattern using the axis of the nozzle. Further, this profile is smoothened by a Gaussian model, and its mathematical expression is obtained. Finally, a numerical model couples spray paths with the mathematical expression to model the coating thickness distribution on a substrate surface under industrial scenarios. At the end of this paper, to verify the proposed model's effectiveness, four sets of operating parameters with a single straight path were experimentally implemented. The width and height of the bead-like shape coating were in good agreement with the simulated results. The normalized root-mean-square errors of the cross-sectional profile heights were around 10%. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
02683768
Volume :
116
Issue :
1/2
Database :
Academic Search Index
Journal :
International Journal of Advanced Manufacturing Technology
Publication Type :
Academic Journal
Accession number :
151704357
Full Text :
https://doi.org/10.1007/s00170-021-07429-0