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首页> 外文期刊>Journal of Fluids Engineering: Transactions of the ASME >Theoretical Parameter Study of Aerodynamic Vectoring Particle Sorting
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Theoretical Parameter Study of Aerodynamic Vectoring Particle Sorting

机译:气动矢量粒子分类的理论参数研究。

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摘要

A new particle sorting technique called aerodynamic vectoring particle sorting (AVPS) has recently been shown to be effective at sorting particles without particles contacting surfaces. The technique relies on turning a free jet sharply without extended control surfaces. The flow turning results in a balance of particle inertia and several forces (pressure, drag, added mass, and body forces) that depend on particle size and density. The present paper describes a theoretical study of particle sorting in a turning flow. The purpose of this study is to extend AVPS to parameter spaces other than those that are currently under investigation. Spherical particles are introduced into a turning flow in which the velocity magnitude increases like r. The trajectory of each particle is calculated using the particle equation of motion with drag laws that are appropriate for various Knudsen number regimes. Large data sets can be collected rapidly for various particle sizes, densities, turning radii, flow speeds, and fluid properties. Ranges of particle sizes that can be sorted are determined by finding an upper bound (where particles move in a straight line) and a lower bound (where particles follow flow streamlines). It is found that the size range of particles that can be sorted is larger for smaller turning radii, and that the range moves toward smaller particles as the flow speed and the particle-to-fluid density ratio are increased. Since this flow is laminar and 2-D, and particle loading effects are ignored, the results represent a "best case" scenario.
机译:最近已显示一种称为空气动力学矢量粒子分选(AVPS)的新粒子分选技术可有效地分选没有接触表面的粒子。该技术依靠在没有扩展控制面的情况下急剧转动自由射流。流动转向导致颗粒惯性和取决于颗粒大小和密度的多个力(压力,阻力,附加质量和体力)之间的平衡。本文描述了转向流中颗粒分类的理论研究。这项研究的目的是将AVPS扩展到当前正在研究的参数空间以外的参数空间。球形颗粒被引入转向流中,在该转向流中速度幅度像r一样增加。使用适用于各种克努森数制的阻力定律,使用运动的粒子方程来计算每个粒子的轨迹。可针对各种粒径,密度,转弯半径,流速和流体性质快速收集大型数据集。可以分类的粒度范围是通过找到上限(粒子沿直线移动)和下限(粒子沿流线移动)确定的。已经发现,对于较小的转弯半径,可以分选的颗粒的尺寸范围较大,并且随着流速和颗粒/流体密度比的增加,该范围向较小的颗粒移动。由于此流是层流和二维的,并且忽略了粒子加载效果,因此结果表示“最佳情况”。

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