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An Overview of the Lagrangian Dispersion Modeling of Heavy Particles in Homogeneous Isotropic Turbulence and Considerations on Related LES Simulations

机译:均匀各向同性湍流中重型粒子拉格朗日色散建模的概述及相关LES模拟的考虑

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Particle tracking is a competitive technique widely used in two-phase flows and best suited to simulate the dispersion of heavy particles in the atmosphere. Most Lagrangian models in the statistical approach to turbulence are based either on the eddy interaction model (EIM) and the Monte-Carlo method or on random walk models (RWMs) making use of Markov chains and a Langevin equation. In the present work, both discontinuous and continuous random walk techniques are used to model the dispersion of heavy spherical particles in homogeneous isotropic stationary turbulence (HIST). Their efficiency to predict particle long time dispersion, mean-square velocity and Lagrangian integral time scales are discussed. Computation results with zero and no-zero mean drift velocity are reported; they are intended to quantify the inertia, gravity, crossing-trajectory and continuity effects controlling the dispersion. The calculations concern dense monodisperse spheres in air, the particle Stokes number ranging from 0.007 to 4. Due to the weaknesses of such models, a more sophisticated matrix method will also be explored, able to simulate the true fluid turbulence experienced by the particle for long time dispersion studies. Computer evolution and performance since allowed to develop, instead of Reynold-Averaged Navier-Stokes (RANS)-based studies, large eddy simulation (LES) and direct numerical simulation (DNS) of turbulence coupled to Generalized Langevin Models. A short review on the progress of the Lagrangian simulations based on large eddy simulation (LES) will therefore be provided too, highlighting preferential concentration. The theoretical framework for the fluid time correlation functions along the heavy particle path is that suggested by Wang and Stock.
机译:粒子跟踪是一种广泛应用于两相流的竞争技术,最适合模拟重质颗粒在大气中的分散。大多数拉格朗日在涉及湍流的统计方法中的模型基于涡互动模型(EIM)和Monte-Carlo方法或在随机步行模型(RWMS)上,利用Markov链和Langevin方程。在本作工作中,不连续和连续的随机步道技术用于模拟重度球形颗粒在均匀各向同性固定湍流(HOST)中的分散。讨论了预测颗粒长时间分散,平均方向速度和拉格朗日积分时间尺度的效率。报告了具有零和无零平均漂移速度的计算结果;它们旨在量化控制分散体的惯性,重力,交叉轨迹和连续性效应。该计算涉及空气中的致密单分散球,粒子斯托克斯号从0.007〜4。由于这种模型的弱点,也将探索更复杂的基质方法,能够模拟粒子长度所经历的真正流体湍流时间分散研究。自允许开发的计算机演变和性能,而不是雷诺瓦德平均的Navier-Stokes(RANS)的研究,大涡模拟(LES)和湍流的直接数值模拟(DNS)耦合到广义Langevin模型。因此,也可以提供关于基于大涡模拟(LES)的拉格朗日模拟进度的简短审查,突出显示优先浓度。沿王和储存的沿重型粒径的流体时间相关函数的理论框架。

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