A three-dimensional quantitative study on the hydrodynamic focusing of particles with the immersed boundary - Lattice Boltzmann method
A three-dimensional quantitative study on the hydrodynamic focusing of particles with the immersed boundary - Lattice Boltzmann method
复制标题
浸没边界颗粒流体动力聚焦三维定量研究——格子玻尔兹曼法
DOI：
10.1016/j.ijheatmasstransfer.2015.11.012
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发表时间：
2016-03
影响因子：
5.2
通讯作者：
Sun Bao-De
中科院分区：
文献类型：
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作者：
Sun Dong-Ke;Wang Yong;Dong An-Ping;Sun Bao-De
通过浸入边界-晶格玻尔兹曼方法对粒子的流体动力聚焦进行数值研究。提出粒子聚焦熵来定量表征流体动力聚焦的处理性能和最终结果。对几个直微通道中的流体动力聚焦进行了模拟，以评估聚焦熵的多功能性。对比分析了聚焦熵和粒子轨迹的时间演化。结果表明，聚焦熵是衡量颗粒有序度和流体动力聚焦性能的有效尺度。有序度越高，聚焦熵越低，表明聚焦性能越好。通道横截面、颗粒刚度和通道雷诺数是影响聚焦动力学和最终结果的三个主要因素。矩形微通道比圆形和方形微通道更有利于流体动力聚焦。矩形微通道中不同硬度的颗粒可以通过流动介导得到显着分离。增加通道雷诺数可以带来更高的效率和更好的聚焦性能。
Hydrodynamic focusing of particles is numerically studied by the immersed boundary – lattice Boltzmann method. Particle focusing entropy is proposed to quantitatively characterize processing performance and final results of hydrodynamic focusing. Simulations of hydrodynamic focusing in several straight microchannels are carried out to evaluate versatility of the focusing entropy. Time evolutions of focusing entropies and particle trajectories are analyzed contrastively. The results demonstrate that the focusing entropy is an effective scale to measure particles ordering degree and hydrodynamic focusing performance. Higher ordering degree determines lower focusing entropy, which indicates better focusing performance. Channel cross section, particle rigidness and channel Reynolds number are three major factors influencing focusing dynamics and final results. Rectangular microchannel is more advantageous than circular and square ones in hydrodynamic focusing. Particles of different rigidness in rectangular microchannel can be separated significantly with the flow mediation. Increasing channel Reynolds numbers can lead to higher efficiency and better focusing performance.
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DOI：
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发表时间：
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期刊：
--
影响因子：
--
作者：
D. K. Sun;M. F. Zhu;S. Pan;C. Yang;D. Raabe
通讯作者：
D. K. Sun;M. F. Zhu;S. Pan;C. Yang;D. Raabe
影响因子：
4.6
作者：
Kilimnik, Alex;Mao, Wenbin;Alexeev, Alexander
通讯作者：
Alexeev, Alexander
影响因子：
4.6
作者：
D. Qi;G. He;Ying-ming Liu
通讯作者：
D. Qi;G. He;Ying-ming Liu
影响因子：
2.9
作者：
Krueger, T.;Varnik, F.;Raabe, D.
通讯作者：
Raabe, D.
影响因子：
13.3
作者：
Weiqiang Chen;Yubing Sun;Jianping Fu
通讯作者：
Weiqiang Chen;Yubing Sun;Jianping Fu