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Detailed characteristics of drop-laden mixing layers: Large eddy simulation predictions compared to direct numerical simulation

机译:含液滴混合层的详细特征:与直接数值模拟相比,大涡模拟预测

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摘要

Results are compared from direct numerical simulation (DNS) and large eddy simulation (LES) of a temporal mixing layer laden with evaporating drops to assess the ability of LES to reproduce detailed characteristics of DNS. The LES used computational drops, each of which represented eight physical drops, and a reduced flow field resolution using a grid spacing four times larger than that of the DNS. The LES also used models for the filtered source terms, which express the coupling of the drops with the flow, and for the unresolved subgrid-scale (SGS) fluxes of species mass, momentum, and enthalpy. The LESs were conducted using one of three different SGS-flux models: dynamic-coefficient gradient (GRD), dynamic-coefficient Smagorinsky (SMD), and constant-coefficient scale similarity (SSC). The comparison of the LES with the filtered-and-coarsened (FC) DNS considered detailed aspects of the flow that are of interest in ignition or full combustion. All LESs captured the largest-scale vortex, the global amount of vapor emanating from the drops, and the overall size distribution of the drops. All LESs tended to underpredict the global amount of irreversible entropy production (dissipation). The SMD model was found unable to capture either the global or local vorticity variation and had minimal small-scale activity in dynamic and thermodynamic variables compared to the FC-DNS. The SMD model was also deficient in predicting the spatial distribution of drops and of the dissipation. In contrast, the GRD and SSC models did mimic the small-scale activity of the FC-DNS and the spatial distribution of drops and of the dissipation. Therefore, the GRD and SSC models are recommended, while the SMD model seems inappropriate for combustion or other problems where the local activity must be predicted.
机译:将直接数值模拟(DNS)和大涡模拟(LES)的时间混合层中充满蒸发液滴的结果进行比较,以评估LES重现DNS详细特征的能力。 LES使用计算液滴,每个液滴代表八个物理液滴,并使用比DNS大四倍的网格间距降低了流场分辨率。 LES还使用模型来表示已过滤的源项,这些模型表示液滴与流的耦合,以及用于模型的质量,动量和焓的未解析子网格规模(SGS)通量。使用三种不同的SGS通量模型之一进行LES,即动态系数梯度(GRD),动态系数Smagorinsky(SMD)和恒定系数尺度相似度(SSC)。 LES与过滤粗化(FC)DNS的比较考虑了在点火或完全燃烧中感兴趣的流的详细方面。所有LES都捕获了最大规模的涡旋,从液滴中散发出来的蒸气总量以及液滴的整体尺寸分布。所有LES都倾向于低估不可逆熵产生(耗散)的总量。与FC-DNS相比,发现SMD模型无法捕获全局或局部涡度变化,并且在动态和热力学变量中具有最小的小规模活动。 SMD模型还不足以预测液滴的空间分布和耗散。相反,GRD和SSC模型确实模拟了FC-DNS的小规模活动以及液滴和耗散的空间分布。因此,推荐使用GRD和SSC模型,而SMD模型似乎不适用于燃烧或其他必须预测局部活动的问题。

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