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Year of Publication
Doctor of Philosophy (PhD)
Prof. Kozo Saito
Dr. Nelson Akafuah
A thorough literature review identified lack of precision control over quality of droplets generated by the currently available industrial sprayers and a growing need for higher quality droplets in the coating industry. Particularly, lack of knowledge and understanding in continuous inkjets (CIJ) and drop-on-demand (DOD) technologies is identified as significant. Motivated by these needs, this dissertation is dedicated to computational fluid dynamics (CFD) and scaling studies to improve existing inkjet technologies and develop new designs of efficient coating with single and/or multiple piezoelectric sensors to produce on-demand droplets. This dissertation study aims at developing a new DOD type coating technology, but it required understanding the effects of paint viscosity on droplet generation mechanism, an effective droplet delivery method to the coating surface, painted surface quality and control system of the DOD among others. Waterborne (WB) paints are chosen as the working liquid to identify three different DOD designs capable of creating a stream of mono-dispersed droplets. Volume-of-fluids (VOF) multiphase model explored the droplet creation process and effects of various parameters on the droplets’ quality. The law approach scaling analysis identified scaling laws to scale up these numerical results conduced for the laboratory-scale DOD to the large industrial scale inkjet nozzles.
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This study was supported by the Institute of Research for Technology Development/College of Engineering research enhancement fund at the University of Kentucky.
Arabghahestani, Masoud Dr., "NUMERICAL AND SCALING STUDY ON APPLICATION OF INKJET TECHNOLOGY TO AUTOMOTIVE COATING" (2022). Theses and Dissertations--Mechanical Engineering. 204.