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Statistical model for collisions and recollisions of inertial particles in mixing flows

机译:混合流中惯性粒子碰撞与碰撞的统计模型

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摘要

Finding a quantitative description of the rate of collisions between small particles suspended in mixing flows is a long-standing problem. Here we investigate the validity of a parameterisation of the collision rate for identical particles subject to Stokes force, based on results for relative velocities of heavy particles that were recently obtained within a statistical model for the dynamics of turbulent aerosols. This model represents the turbulent velocity fluctuations by Gaussian random functions. We find that the parameterisation gives quantitatively good results in the limit where the "ghost-particle approximation" applies. The collision rate is a sum of two contributions due to "caustics" and to "clustering". Within the statistical model we compare the relative importance of these two collision mechanisms. The caustic formation rate is high when the particle inertia becomes large, and we find that caustics dominate the collision rate as soon as they form frequently. We compare the magnitude of the caustic contribution to the collision rate to the formation rate of caustics.
机译:对悬浮在混合流中的小颗粒之间的碰撞速率进行定量描述是一个长期存在的问题。在这里,我们根据最近在湍流气溶胶动力学统计模型中获得的重颗粒的相对速度结果,研究了受斯托克斯力作用的相同颗粒的碰撞速率参数化的有效性。该模型通过高斯随机函数表示湍流速度波动。我们发现参数化在“鬼粒子近似”适用的极限条件下给出了定量良好的结果。碰撞率是由于“焦散”和“聚类”而产生的两个贡献之和。在统计模型中,我们比较了这两种碰撞机制的相对重要性。当粒子惯性变大时,苛性碱的形成速率很高,并且我们发现,苛性碱在它们频繁形成后便立即主宰碰撞速率。我们将碱对碰撞速率的贡献程度与碱的形成速率进行比较。

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