Statistical characteristics of falling-film flows: A synergistic approach at the crossroads of direct numerical simulations and experiments
Statistical characteristics of falling-film flows: A synergistic approach at the crossroads of direct numerical simulations and experiments
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DOI：
10.1103/physrevfluids.2.124002
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发表时间：
2017-12-08
影响因子：
2.7
通讯作者：
Markides, Christos N.
中科院分区：
文献类型：
--
作者：
Charogiannis, Alexandros;Denner, Fabian;Markides, Christos N.
我们仔细研究的统计特性的液体膜流过一个倾斜的平面表面上的膜的高度和速度测量的基础上，同时恢复应用平面激光诱导荧光（PLIF）和粒子跟踪测速（PTV），分别。我们的实验是补充直接数值模拟（DNSs）模拟不同条件下的液膜，以扩大我们的调查参数空间。我们的统计分析建立在我们先前关于降膜的研究工作中提出的随时间变化的流速的类似于Colcholds的分解的基础上[Charogiannis等人，Phys. Rev. Fluids 2，014002（2017）]，并且其揭示了非稳态项与平均流速的无量纲比率随着膜高度和体积速度的变化系数的乘积以及努塞尔高度与平均膜高度的比率线性增加，两者都在相同的上游PLIF/PTV测量位置处。基于关系，推导出描述这些结果，用于预测的传质能力（通过的平均值和标准偏差的体积流速度）的这些流量的方法是开发的平均值和标准偏差的膜厚度和平均流速，这是相当容易获得实验比速度分布。与这些预测相关的误差估计在实验中分别为约1.5%和8%，在DNS中分别为< 1%和< 2%。除了基于简单的流动信息生成用于预测重要膜流特性的这些关系之外，所提供的数据可用于设计改进的传热和传质设备反应器或利用膜流的其他过程操作单元，而且还可用于开发和验证其他物理和技术设置中的多相流模型。
We scrutinize the statistical characteristics of liquid films flowing over an inclined planar surface based on film height and velocity measurements that are recovered simultaneously by application of planar laser-induced fluorescence (PLIF) and particle tracking velocimetry (PTV), respectively. Our experiments are complemented by direct numerical simulations (DNSs) of liquid films simulated for different conditions so as to expand the parameter space of our investigation. Our statistical analysis builds upon a Reynolds-like decomposition of the time-varying flow rate that was presented in our previous research effort on falling films in [Charogiannis et al., Phys. Rev. Fluids 2, 014002 (2017)], and which reveals that the dimensionless ratio of the unsteady term to the mean flow rate increases linearly with the product of the coefficients of variation of the film height and bulk velocity, as well as with the ratio of the Nusselt height to the mean film height, both at the same upstream PLIF/PTV measurement location. Based on relations that are derived to describe these results, a methodology for predicting the mass-transfer capability (through the mean and standard deviation of the bulk flow speed) of these flows is developed in terms of the mean and standard deviation of the film thickness and the mean flow rate, which are considerably easier to obtain experimentally than velocity profiles. The errors associated with these predictions are estimated at approximate to 1.5% and 8% respectively in the experiments and at < 1% and < 2% respectively in the DNSs. Beyond the generation of these relations for the prediction of important film flow characteristics based on simple flow information, the data provided can be used to design improved heat-and mass-transfer equipment reactors or other process operation units which exploit film flows, but also to develop and validate multiphase flow models in other physical and technological settings.