Lagrangian particles with mixing. II. Sparse-Lagrangian methods in application for turbulent reacting flows
Lagrangian particles with mixing. II. Sparse-Lagrangian methods in application for turbulent reacting flows
复制标题
混合拉格朗日粒子。
DOI：
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发表时间：
2009
期刊：
影响因子：
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通讯作者：
A. Klimenko
中科院分区：
文献类型：
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作者：
A. Klimenko
这两部分的工作提出了一个更详细和具体的分析，在以前发表的信中介绍的想法[物理流体19，031702（2007）]。在论文I [Phys. Fluids 19，065101（2009）]中，我们证明了连续标量输运和扩散可以通过具有标量性质的随机行走拉格朗日粒子之间的混合来精确地指定。在这里，在纸II中，我们处理的情况下，粒子的数量是不足以解决所有尺度的湍流和拉格朗日粒子混合成为一个近似模型，而不是一个随机框架求解精确的标量输运方程。我们认为稀疏拉格朗日方法，使用相对较少的粒子数欧拉网格点的数量相比，并讨论与传统的大涡模拟过滤密度函数（LES-FDF）方法的相似性和差异。特别注意的是多映射条件（MMC）制定的稀疏拉格朗日方程…
Both parts of this work present a more detailed and specific analysis of ideas introduced in the previously published letter [Phys. Fluids 19, 031702 (2007)]. In Paper I [Phys. Fluids 19, 065101 (2009)], we show that the continuous scalar transport and diffusion can be accurately specified by means of mixing between randomly walking Lagrangian particles with scalar properties. Here, in Paper II, we deal with the situation where the number of particles is not sufficient to resolve all scales in turbulent flows and Lagrangian particles with mixing become an approximate model rather than a stochastic framework for solving exact scalar transport equations. We consider sparse-Lagrangian methods that use relatively small numbers of particles compared to the number of Eulerian grid points and discuss similarities and differences with conventional large eddy simulations—filtered density function (LES-FDF) methods. Special attention is paid to multiple mapping conditioning (MMC) formulation for sparse-Lagrangian s...