DNS和湍流混合层中被动和主动标量的水平集动力学和混合效率

B. Geurts, Bert Vreman, H. Kuerten, K. Luo
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摘要

紊流混合层的混合效率是通过监测标量场水平集的表面积来量化的。应用拉普拉斯变换对任意水平集上的积分进行数值计算。该分析包括直接模拟和大涡模拟,并用于评估特定子网格参数化在预测混合效率方面的适用性。我们采用了几种子网格模型进行比较,如Bardina的尺度相似模型、动态涡粘模型和动态混合模型。为了准确预测,动态模型更受青睐。结果表明,les滤波器宽度Δ与栅格间距h的比值对其影响较大;比率为4似乎比较合适。重力驱动的流动可以通过与动量和能量方程耦合的“活动”标量场来建模。浮力效应对混合效率的显著提高进行了直接量化。
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LEVEL-SET DYNAMICS AND MIXING EFFICIENCY OF PASSIVE AND ACTIVE SCALARS IN DNS AND LES OF TURBULENT MIXING LAYERS
The mixing efficiency in a turbulent mixing layer is quantified by monitoring the surface-area of level-sets of scalar fields. The Laplace transform is applied to numerically calculate integrals over arbitrary level-sets. The analysis includes both direct and large-eddy simulation and is used to assess the suitability of specific subgrid parameterizations in relation to predicting mixing efficiency. We incorporate several subgrid models in the comparison, e.g. the scale similarity model of Bardina, the dynamic eddy-viscosity model and the dynamic mixed model. For accurate predictions, dynamic models are favored. It is observed that the ratio between LES-filterwidth Δ and grid-spacing h has a considerable influence; a ratio of four appears suitable. Gravity driven flows can be modeled by 'active' scalar fields which couple to the momentum and energy equations. The significant increase in mixing efficiency due to buoyancy effects is directly quantified.
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