基于粗大涡模拟的三维差热腔内载颗粒流动CFD模拟

IF 2 3区 工程技术 Q3 MECHANICS
M. A. Sayed, A. Dehbi, M. Hadžiabić, B. Ničeno, K. Mikityuk
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引用次数: 0

摘要

封闭空间中的颗粒流动在许多工程应用中都有涉及。本文采用粗大涡模拟(粗大涡模拟)对瑞利数Ra = 109时热驱动三维腔体中颗粒去除的预测进行了研究。在欧拉/拉格朗日框架中报道了空气动力直径在1.4 ~ 14µm之间的SiO2气溶胶的耗竭动力学。因此,这项工作的主要重点是评估当网格分辨率较粗且低于最佳LES标准时,亚网格尺度运动对浮力驱动的3D腔流中颗粒流动预测的影响。该研究的动机是在降低CPU成本的情况下模拟更复杂的颗粒物流动的可行性。边长为0.7 m的立方体空腔被设置为两个面对冷和热的垂直墙之间的温差为39 K。作为第一步,通过将一阶和二阶矩统计数据与先前分辨率较高的LES和实验数据库进行比较,验证载液流动[Kalilainen (J. Aero Sci. 100:73-87, 2016);德比(J. Aero)科学通报,2017,(3):391 - 391。一阶矩欧拉统计量在定性和定量上都与参考数据非常匹配,而高阶矩由于空间分辨率较低而表现出预测不足。第二步,计算跨越大范围粒子斯托克斯数的6个粒子群来预测粒子耗尽。特别是,1.4和3.5 μ m粒子的预测与LES和现有的实验数据进行了比较。低惯性的粒子(即dp < 3.5µm)受SGS效应的影响更大,而较大的粒子(即dp = 3.5 - 14µm)对网格的依赖性要小得多。以定性和定量方式报告的拉格朗日统计数据表明,在最佳LES所需的CPU功率的一小部分上,总体上与参考LES和实验数据库非常一致。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
CFD Simulation of Particle-Laden Flow in a 3D Differentially Heated Cavity Using Coarse Large Eddy Simulation

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 = 109 using Coarse Large Eddy Simulation (CLES). The depletion dynamics of SiO2 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.

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来源期刊
Flow, Turbulence and Combustion
Flow, Turbulence and Combustion 工程技术-力学
CiteScore
5.70
自引率
8.30%
发文量
72
审稿时长
2 months
期刊介绍: Flow, Turbulence and Combustion provides a global forum for the publication of original and innovative research results that contribute to the solution of fundamental and applied problems encountered in single-phase, multi-phase and reacting flows, in both idealized and real systems. The scope of coverage encompasses topics in fluid dynamics, scalar transport, multi-physics interactions and flow control. From time to time the journal publishes Special or Theme Issues featuring invited articles. Contributions may report research that falls within the broad spectrum of analytical, computational and experimental methods. This includes research conducted in academia, industry and a variety of environmental and geophysical sectors. Turbulence, transition and associated phenomena are expected to play a significant role in the majority of studies reported, although non-turbulent flows, typical of those in micro-devices, would be regarded as falling within the scope covered. The emphasis is on originality, timeliness, quality and thematic fit, as exemplified by the title of the journal and the qualifications described above. Relevance to real-world problems and industrial applications are regarded as strengths.
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