首页> 外文期刊>Numerical Heat Transfer, Part B. Fundamentals: An International Journal of Computation and Methodology >A TIME-SERIES STOCHASTIC SEPARATED FLOW (TSSSF) MODEL FOR TURBULENT TWO-PHASE FLOWS
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A TIME-SERIES STOCHASTIC SEPARATED FLOW (TSSSF) MODEL FOR TURBULENT TWO-PHASE FLOWS

机译:湍流两相流的时间序列随机分离(TSSSF)模型

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摘要

A time-series stochastic separated flow (TSSSF) model is proposed to obtain more reasonable statistical characteristics of two-phase turbulent flows. The sampled instantaneous fluctuating velocities of the gas phase u'_i(t) are imposed on the particle's motion for n time steps determined by the calculation of the auto-correlation coefficient between u'_i(t) and u'_i(t-nΔt) at each time step. An application of the model is performed in a turbulent two-phase flow over a backward facing step. The statistical particle phase velocities and particle concentration contours agree well with the experimental data and large-eddy simulation results, respectively. The present model can represent the unsteady flow mechanisms and therefore improves the prediction of particle dispersion.
机译:为了获得更合理的两相湍流统计特性,提出了一种时间序列随机分离流模型。气相的瞬时瞬时波动速度u'_i(t)通过计算u'_i(t)和u'_i(t-nΔt之间的自相关系数)确定的n个时间步长施加在粒子的运动上)。该模型的应用是在朝后的步骤中,在湍流的两相流中进行的。统计的粒子相速度和粒子浓度等高线分别与实验数据和大涡模拟结果吻合良好。本模型可以表示非稳态流动机理,因此改善了颗粒扩散的预测。

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