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Direct numerical simulation and Lagrangian modeling of joint scalar statistics in ternary mixing

机译:三元混合中标量统计量的直接数值模拟和拉格朗日建模

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Direct numerical simulation (DNS) results are presented for the joint statistics of two inhomogeneous scalar fields, one due to a mixing layer source and the other due to a contiguous top-hat source. These two sources form the basis for all scalar mixing across three streams. The results are used to assess the performance of a Lagrangian stochastic modeling system incorporating the interaction with the conditional mean mixing model at two different times: A near-field time when there is little spatial overlap between the two scalar fields, and a far-field time when there is strong overlap. In the near field we find that for both the model and the DNS, the joint probability density function is essentially confined to two lines in concentration phase space; the diagonal psi(1)+ psi(2)= 1 and the axis psi(1)= 0, where psi(1) and psi(2) are the phase space concentrations for the mixing layer and top-hat scalars, respectively. The model and DNS results along these sections are in excellent quantitative agreement for a range of statistics. In the far field the DNS results show significant levels of probability density throughout the concentration domain psi(1)+psi(2) <= 1, but the model results have a much more limited range in the top-hat scalar, with less unmixed fluid reflecting excessive mixing. This inevitably results in quantitative differences in other statistics, but the conditional mean diffusion for the model shows semiquantitative agreement with the DNS. The most striking difference between model and DNS results in the far field is shown in the conditional mean velocity for which the model shows oscillations in sign not present in the DNS. (C) 2008 American Institute of Physics.
机译:给出了直接数值模拟(DNS)结果,用于两个不均匀标量场的联合统计,一个是由于混合层源,另一个是由于连续的礼帽源。这两个来源构成了三个流中所有标量混合的基础。结果用于评估结合了条件均值混合模型在两个不同时间的相互作用的拉格朗日随机建模系统的性能:两个标量场之间几乎没有空间重叠的近场时间,以及远场强烈重叠的时间。在近场中,我们发现对于模型和DNS而言,联合概率密度函数实质上都局限于浓度相空间中的两条线;对角psi(1)+ psi(2)= 1,轴psi(1)= 0,其中psi(1)和psi(2)分别是混合层和礼帽标量的相空间浓度。这些部分中的模型和DNS结果对于一系列统计数据而言,具有极好的定量一致性。在远场中,DNS结果显示整个浓度域psi(1)+ psi(2)<= 1时,概率密度的水平很高,但模型结果在礼帽标量中的范围受限制得多,未混合的较少反映过度混合的流体。这不可避免地导致其他统计数据之间的数量差异,但是该模型的条件均值扩散显示出与DNS的半定量一致性。在远场中,模型与DNS结果之间最显着的区别在于条件平均速度,模型显示了DNS中不存在的符号振荡。 (C)2008美国物理研究所。

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