Andre Fellipe Vilanova de Araujo Aquino    LinkedIn

PhD Candidate, University of New South Wales, Australia. 

 

PhD Topic:

"Investigating the airflow instability in inkjet printer to understand the tiger striping print defect"

Research interests: CFD, microfluidics, inkjet systems, flow stability and external aerodynamics

Email: Andre.aquino@unsw.edu.au

The use of inkjet printers has been expanded to manufacturing electronics, solar panels, rapid prototypes, and reinforced composites. The expansion of the inkjet technology to other applications is yet limited by the restrictive print gaps (distance between media and printer head) that inkjet printers need to operate. Small print gaps prevent the printer from accommodating medias with variable thickness and increase the likelihood of the media striking the printer head and damaging the nozzles. At large print gaps, however, the print quality is likely to be compromised due to the misplacement of droplets that creates a printing defect commonly referred to as tiger-stripe. The goal of this project is to define, with the aid of CFD simulations and experiments, the airflow regimes where the tiger-striping problem occurs and characterize the flow features while relating them to the severity of problem.

Education/Employment

2019-present PhD Mechanical Engineering, UNSW, Sydney

2020-2021 Simulation Engineer, 5b – solar reinvented, Sydney

2019-2020 Engineering Internship, Memjet, Macquarie Park

2019-2019 Casual Academic, Macquarie University, Sydney

2018-2019 Masters of Research in Science and Engineering, Macquarie University, Macquarie Park

2012-2017 Bachelors of Mechanical Engineering, Universidade Federal de Sergipe, Sao Cristovao (SE) - Brazil

Publications

 

Aquino, A., Mallinson, S., McBain, G.D., Horrocks, G. and Barber, T., 2020. Two-dimensional numerical simulation of inkjet print-zone flows.

Mallinson, S., Aquino, A., McBain, G., Horrocks, G., Barber, T. and Yeoh, G., 2020. Three-dimensional numerical simulation of air-flow in inkjet print-zones.    

    

Jeong, C., Santos Peixoto, A.C., Aquino, A., Lloyd, S. and Arhin, S., 2017. Genetic Algorithm–Based Acoustic-Source Inversion Approach to Detect Multiple Moving Wave Sources of an Arbitrary Number. Journal of Computing in Civil Engineering, 31(5), p.04017020.

Copyright © 2020 Tracie Barber. All rights reserved.