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Collision statistics in an isotropic particle-laden turbulent suspension. Part 1. Direct numerical simulations

斯托克斯数 物理 湍流 碰撞频率 均匀各向同性湍流 粒子(生态学) 阻力 直接数值模拟 机械 相对速度 航程(航空) 碰撞 颗粒流 粒子数 经典力学 雷诺数 热力学 电子 材料科学 体积热力学 量子力学 海洋学 计算机安全 复合材料 计算机科学 地质学
作者
Shivshankar Sundaram,Lance R. Collins
出处
期刊:Journal of Fluid Mechanics [Cambridge University Press]
卷期号:335: 75-109 被引量:570
标识
DOI:10.1017/s0022112096004454
摘要

Direct numerical simulations of heavy particles suspended in a turbulent fluid are performed to study the rate of inter-particle collisions as a function of the turbulence parameters and particle properties. The particle volume fractions are kept small (∼10 −4 ) so that the system is well within the dilute limit. The fluid velocities are updated using a pseudo-spectral algorithm while the particle forces are approximated by Stokes drag. One unique aspect of the present simulations is that the particles have finite volumes (as opposed to point masses) and therefore particle collisions must be accounted for. The collision frequency is monitored over several eddy turnover times. It is found that particles with small Stokes numbers behave similarly to the prediction of Saffman & Turner (1956). On the other hand, particles with very large Stokes numbers have collision frequencies similar to kinetic theory (Abrahamson 1975). For intermediate Stokes numbers, the behaviour is complicated by two effects: (i) particles tend to collect in regions of low vorticity (high strain) due to a centrifugal effect (preferential concentration); (ii) particle pairs are less strongly correlated with each other, resulting in an increase in their relative velocity. Both effects tend to increase collision rates, however the scalings of the two effects are different, leading to the observed complex behaviour. An explanation for the entire range of Stokes numbers can be found by considering the relationship between the collision frequency and two statistical properties of the particle phase: the radial distribution function and the relative velocity probability density function. Statistical analysis of the data, in the context of this relationship, confirms the relationship and provides a quantitative description of how preferential concentration and particle decorrelation ultimately affect the collision frequency.
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