Elliptical spreading characteristics of a liquid metal droplet impact on a glass surface under a horizontal magnetic field

被引:24
|
作者
Yang, Juan-Cheng [1 ]
Qi, Tian-Yu [2 ]
Han, Tian-Yang [2 ]
Zhang, Jie [1 ]
Ni, Ming-Jiu [1 ,2 ]
机构
[1] Xi An Jiao Tong Univ, State Key Lab Strength & Vibrat Mech Struct, Sch Aerosp, Xian 710049, Shaanxi, Peoples R China
[2] Univ Chinese Acad Sci, Sch Engn Sci, Beijing 101408, Peoples R China
关键词
SOLID-SURFACE; NUMERICAL-SIMULATION; TENSION; MODELS; FLOWS; WALL;
D O I
10.1063/1.5000054
中图分类号
O3 [力学];
学科分类号
08 ; 0801 ;
摘要
The spreading characteristics of a liquid GaInSn alloy droplet on a glass surface with the action of a horizontal magnetic field have been experimentally investigated in the present paper. With changing the impact velocity from 0.1 m/s to 1.2 m/s and increasing the magnetic field from 0 T to 1.6 T, we focus on studying the influence of the horizontal magnetic field on the spreading characteristics of a liquid metal droplet using the shadow-graph method. The elliptical spreading pattern of a liquid metal droplet induced by the horizontal magnetic field was discovered by experiments. By introducing a numerical method in getting the distribution of current lines and the Lorentz force inside the droplet, we give a detailed explanation on the mechanism of elliptical spreading. Furthermore, some quantitative results on a maximum spreading factor and time at moment of maximum spreading varied with the Hartmann number and Weber number are shown to give us a comprehensive understanding of the elliptical spreading. With the increasing of the magnetic field, the maximum spreading factor in the front view is reduced while that in the side view is increased, which reveals a larger deformation happened during the spreading process. While with the increasing of impact velocity, the spreading factor increased. Finally, we present a non-dimensional parameter to get scaling laws for the averaged maximum spreading factor and the aspect ratio of the maximum spreading factor; results show that the predict data can agree with experimental data in a certain degree. Published by AIP Publishing.
引用
收藏
页数:13
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