A common feature of wall-bounded turbulent particle-laden flows is enhanced particle concentrations in a thin layer near the wall due to a phenomenon known as turbophoresis. Even at relatively low bulk volume fractions, particle-particle collisions regulate turbophoresis in a critical way, making simulations sensitive to collisional effects. Lagrangian tracking of every particle in the flow can become computationally expensive when the physical number of particles in the system is large. Artificially reducing the number of particles in the simulation can mitigate the computational cost. When particle-particle collisions are an important aspect determining the simulation outcome, as in the case when turbophoresis plays an active role, simply reducing the number of particles in the simulation significantly alters the computed particle statistics. This paper introduces a computational particle treatment for particle-particle collisions which reproduces the results of a full simulation with a reduced number of particles. This is accomplished by artificially enhancing the particle collision radius based on scaling laws for the collision rates. The proposed method retains the use of deterministic collision models and is applicable for both low and high Stokes number regimes.

中文翻译：

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用减少的计算粒子数预测粒子-粒子碰撞对涡轮电泳的影响

壁面湍流颗粒负载流动的一个共同特征是，由于一种称为涡轮电泳的现象，靠近壁面的薄层中的颗粒浓度增加。即使在相对较低的体积分数下，粒子 - 粒子碰撞也会以一种关键的方式调节涡轮电泳，使模拟对碰撞效应敏感。当系统中粒子的物理数量很大时，流中每个粒子的拉格朗日跟踪可能会变得计算成本很高。人为地减少模拟中的粒子数量可以降低计算成本。当粒子 - 粒子碰撞是决定模拟结果的一个重要方面时，如在涡轮电泳发挥积极作用的情况下，简单地减少模拟中的粒子数量会显着改变计算的粒子统计数据。本文介绍了一种用于粒子-粒子碰撞的计算粒子处理方法，该方法可以在减少粒子数量的情况下重现完整模拟的结果。这是通过基于碰撞率的缩放定律人为地增强粒子碰撞半径来实现的。所提出的方法保留了确定性碰撞模型的使用，并且适用于低斯托克斯数和高斯托克斯数制度。