Bulletin of the American Physical Society
71st Annual Meeting of the APS Division of Fluid Dynamics
Volume 63, Number 13
Sunday–Tuesday, November 18–20, 2018; Atlanta, Georgia
Session F11: Spreading and Evaporation of Binary Drops
8:00 AM–10:10 AM,
Monday, November 19, 2018
Georgia World Congress Center
Room: B216
Chair: Justin Burton, Emory University
Abstract ID: BAPS.2018.DFD.F11.1
Abstract: F11.00001 : Development of stereoscopic three-dimensional particle tracking velocimetry using machine learning technique*
8:00 AM–8:13 AM
Presenter:
Han Seo Ko
(Sungkyunkwan Univ)
Authors:
Han Seo Ko
(Sungkyunkwan Univ)
Yeonghyeon Gim
(Sungkyunkwan Univ)
Dong Kyu Jang
(Sungkyunkwan Univ)
Dong Kee Sohn
(Sungkyunkwan Univ)
Hyoungsoo Kim
(KAIST)
A three-dimensional Particle Tracking Velocimetry (3D-PTV) technique is a method to extract velocity data inside target fluid. Unlike a three-dimensional Particle Image Velocimetry (3D-PIV) technique, the 3D-PTV technique focuses on three-dimensional movement of particles inside the target. Thus, it is appropriate to analyze sedimentation patterns during droplet evaporation phenomena. In this study, the 3D-PTV technique was applied to visualize evaporation flow pattern inside a binary mixture droplet. The technique was developed by a machine learning technique and verified by a numerical simulation. Then, the three-dimensional flow structure inside the droplet was obtained. The droplet consists of DI water, ethanol, and particles with a diameter of 15 µm. The images of particles inside the droplet were captured by two high-speed cameras. The images were revised by the image processing procedure, and successfully used for reconstructing the three-dimensional trajectories of the particles inside the droplet.
*This work was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF), funded by the Korean government (MEST) (2016R1A2B4011087).
To cite this abstract, use the following reference: http://meetings.aps.org/link/BAPS.2018.DFD.F11.1
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