当前位置: X-MOL 学术Int. J. Heat Mass Transf. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
A computational and experimental study of thermal energy separation by swirl
International Journal of Heat and Mass Transfer ( IF 5.2 ) Pub Date : 2018-09-01 , DOI: 10.1016/j.ijheatmasstransfer.2018.03.058
B. Kobiela , B.A. Younis , B. Weigand , O. Neumann

Abstract When compressed air is introduced into a tube in such a way as to generate a strong axial vortex, an interesting phenomenon is observed wherein the fluid temperature at the vortex core drops below the inlet value, while in the outer part of the vortex, the temperature is higher than at inlet. The most familiar manifestation of this phenomenon is known as the Ranque-Hilsch effect, and several alternative explanations for it have been proposed. In this study, we present an analysis of the heat transfer mechanism underlying this phenomenon, based on consideration of the exact equation governing the conservation of the turbulent heat fluxes. The outcome is a model that explicitly accounts for the dependence of the heat fluxes on the mean rates of strain, and on the gradients of mean pressure. These dependencies, which are absent from conventional closures, are required by the exact equation. To verify the model, an experimental investigation of flow in a swirl chamber was conducted, and the measurements were used to check the model’s performance as obtained by three-dimensional numerical simulations. Comparisons between predictions and measurements demonstrate that the new model yields predictions that are distinctly better than those obtained using conventional closures.

中文翻译:

涡流分离热能的计算与实验研究

摘要 当压缩空气以产生强烈轴向涡流的方式引入管内时,观察到一个有趣的现象,即涡核处的流体温度下降到入口值以下,而在涡流的外部,流体温度下降到入口值以下。温度高于入口。这种现象最常见的表现被称为 Ranque-Hilsch 效应,并且已经提出了几种替代解释。在这项研究中,我们基于对控制湍流热通量守恒的精确方程的考虑,对这种现象背后的传热机制进行了分析。结果是一个模型,该模型明确说明了热通量对平均应变率和平均压力梯度的依赖性。这些依赖,传统闭包中不存在的,是精确方程所要求的。为了验证模型,对涡流室中的流动进行了实验研究,并使用测量结果来检查模型的性能,如通过三维数值模拟获得的。预测和测量之间的比较表明,新模型产生的预测明显优于使用传统闭包获得的预测。
更新日期:2018-09-01
down
wechat
bug