Sayed M A, Dehbi A, Hadžiabić M, Ničeno B, Mikityuk K
Paul Scherrer Institut (PSI), 5232 Villigen, Switzerland.
Swiss Federal Institute of Technology Lausanne (EPFL), 1015 Lausanne, Switzerland.
Flow Turbul Combust. 2022;109(4):961-990. doi: 10.1007/s10494-022-00356-4. Epub 2022 Aug 16.
Particulate flow in closed space is involved in many engineering applications. In this paper, the prediction of particle removal is investigated in a thermally driven 3D cavity at turbulent Rayleigh number Ra = 10 using Coarse Large Eddy Simulation (CLES). The depletion dynamics of SiO aerosol with aerodynamic diameters between 1.4 and 14 µm is reported in an Euler/Lagrange framework. The main focus of this work is therefore to assess the effect of the subgrid-scale motions on the prediction of the particulate flow in a buoyancy driven 3D cavity flow when the mesh resolution is coarse and below optimal LES standards. The research is motivated by the feasibility of modeling more complex particulate flows with reduced CPU cost. The cubical cavity of 0.7 m side-length is set to have a temperature difference of 39 K between the two facing cold and hot vertical walls. As a first step, the carrier fluid flow was validated by comparing the first and second-moment statistics against both previous well-resolved LES and experimental databases [Kalilainen (J. Aero Sci. 100:73-87, 2016); Dehbi (J. Aero. Sci. 103:67-82, 2017)]. First moment Eulerian statistics show a very good match with the reference data both qualitatively and quantitatively, whereas higher moments show underprediction due to the lesser spatial resolution. In a second step, six particle swarms spanning a wide range of particle Stokes numbers were computed to predict particle depletion. In particular, predictions of 1.4 and 3.5 µm particles were compared to LES and available experimental data. Particles of low inertia i.e. dp < 3.5 µm are more affected by the SGS effects, while bigger ones i.e. dp = 3.5-14 µm exhibit much less grid-dependency. Lagrangian statistics reported in both qualitative and quantitative fashions show globally a very good agreement with reference LES and experimental databases at a fraction of the CPU power needed for optimal LES.
封闭空间中的颗粒流涉及许多工程应用。本文采用粗大型涡模拟(CLES)方法,研究了在湍流瑞利数Ra = 10的热驱动三维腔内颗粒去除的预测。在欧拉/拉格朗日框架下报告了空气动力学直径在1.4至14μm之间的SiO气溶胶的耗尽动力学。因此,这项工作的主要重点是评估当网格分辨率粗糙且低于最佳大涡模拟标准时,亚网格尺度运动对浮力驱动三维腔内颗粒流预测的影响。该研究的动机是通过降低CPU成本来模拟更复杂颗粒流的可行性。边长为0.7m的立方体腔设置为两个相对的冷热垂直壁之间的温差为39K。第一步,通过将一阶和二阶矩统计量与先前分辨率良好的大涡模拟和实验数据库进行比较,验证了载流体流动[卡里莱宁(《航空科学杂志》100:73 - 87,2016年);德赫比(《航空科学杂志》103:67 - 82,2017年)]。一阶欧拉统计量在定性和定量上都与参考数据非常吻合,而高阶矩由于空间分辨率较低而显示出预测不足。第二步,计算了六个跨越广泛颗粒斯托克斯数范围的粒子群,以预测颗粒耗尽。特别地,将1.4μm和3.5μm颗粒的预测结果与大涡模拟和现有实验数据进行了比较。低惯性颗粒即dp < 3.5μm受亚网格尺度效应的影响更大,而较大颗粒即dp = 3.5 - 14μm表现出的网格依赖性要小得多。以定性和定量方式报告的拉格朗日统计量总体上与参考大涡模拟和实验数据库非常吻合,而所需的CPU算力仅为最佳大涡模拟所需的一小部分。