A quantitative and generalized assessment of bubble-induced turbulence models for gas-liquid systems

Q1 Engineering
Chemical Engineering Science: X Pub Date : 2019-05-01 Epub Date: 2019-02-05 DOI:10.1016/j.cesx.2019.100009
Ben Magolan, Nazar Lubchenko, Emilio Baglietto
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引用次数: 25

Abstract

In gas-liquid systems, bubble motion and interaction with the surrounding liquid medium serves to dramatically modify the liquid turbulent kinetic energy profile. While several two-equation bubble-induced turbulence (BIT) models have been advanced to predict this phenomenon, the intrinsic non-linearities that accompany the solution of the governing equations, interfacial forces, and turbulence models complicate their assessment. This hinders understanding of model performance and obstructs necessary model improvements. Here, the mathematical formulation of existing BIT models is investigated, and selected models are quantitatively assessed through simulation of the entire Liu (1989) air/water pipe flow experimental database in OpenFOAM. Critical to this work is the approach adopted to decouple the connection between turbulence and momentum closures, which ensures physically consistent volume fraction profiles and enables fair comparison between models. The assessment reveals that existing closures struggle with reliably predicting the turbulent kinetic energy profile as well as routinely worsen mean flow predictions. These observations are used to propose a pathway for the assembly of new BIT model formulations.

气液系统气泡诱导湍流模型的定量和广义评价
在气液系统中,气泡运动和与周围液体介质的相互作用极大地改变了液体湍流动能分布。虽然已经提出了几种双方程气泡诱导湍流(BIT)模型来预测这种现象,但伴随控制方程、界面力和湍流模型的解的固有非线性使其评估复杂化。这阻碍了对模型性能的理解,并阻碍了必要的模型改进。本文对现有BIT模型的数学公式进行了研究,并通过对整个Liu(1989)在OpenFOAM中的空气/水管流动实验数据库进行仿真,对所选模型进行了定量评估。这项工作的关键是采用分离湍流和动量闭合之间联系的方法,这确保了物理上一致的体积分数分布,并使模型之间的公平比较成为可能。评估表明,现有的闭包很难可靠地预测湍流动能分布,并且通常会使平均流量预测变差。这些观察结果被用来提出一个新的BIT模型公式组装的途径。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Chemical Engineering Science: X
Chemical Engineering Science: X Engineering-Industrial and Manufacturing Engineering
CiteScore
11.30
自引率
0.00%
发文量
2
审稿时长
25 weeks
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