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中国科学院大学学报 ›› 2017, Vol. 34 ›› Issue (2): 210-217.DOI: 10.7523/j.issn.2095-6134.2017.02.014

• 研究论文 • 上一篇    下一篇

矩形截面纤维流场压降及细颗粒扩散捕集效率

黄浩凯, 赵海波   

  1. 华中科技大学煤燃烧国家重点实验室, 武汉 430074
  • 收稿日期:2016-04-21 修回日期:2016-05-20 发布日期:2017-03-15
  • 通讯作者: 赵海波,E-mail:klinsmannzhb@163.com
  • 基金资助:
    国家自然科学基金(51522603)资助

Numerical study of pressure drop and diffusional collection efficiency of rectangular fibers in filtration

HUANG Haokai, ZHAO Haibo   

  1. State Key Laboratory of Coal Combustion, Huazhong University of Science and Technology, Wuhan 430074, China
  • Received:2016-04-21 Revised:2016-05-20 Published:2017-03-15

摘要: 采用格子波尔兹曼气固两相流模型模拟扩散机制下矩形纤维捕集颗粒过程,研究纤维周围流场压降和扩散捕集效率随不同纤维布置方式的变化规律。把模拟得到的值(系统压降与捕集效率)与相同体积分数的圆柱纤维所对应的理论值相比,得到相应比例系数。分析规律,并采用Levenberg-Marquardt方法对其进行处理,得到相应比例系数的拟合公式。根据已有的圆形纤维压降与扩散效率的理论公式,再结合求得的拟合公式,对不同工况下的矩形纤维系统压降和扩散捕集效率进行计算。分析结果发现:矩形纤维系统压降与放置角度和长宽比均相关;而扩散捕集效率与长宽比成正比,与放置角度基本无关。

关键词: LB-CA模型, 矩形纤维, 拟合公式, Levenberg-Marquardt方法

Abstract: In this work, we use a lattice Boltzmann-cellular automaton (LB-CA) probabilistic model to simulate the particle filtration processes of rectangular fibers. The pressure drop and collection efficiency for the diffusion dominant regime are investigated. By normalizing the pressure drop and collection efficiency of rectangular fibers with those of the circular fiber calculated by using the existing classical expressions, the corresponding ratios are oftained. Then the Levenberg-Marquardt algorithm is used to obtain the fitting expressions of the ratios. The proposed fitting expressions are used to calculate the pressure drops and diffusional collection efficiencies of rectangular fibers under different operation conditions. The results show that the pressure drop of rectangular fibers is dependent on the orientation angle and the aspect ratio and that the diffusional collection efficiency is proportional to the aspect ratio but almost independent of the orientation angle.

Key words: lattice Boltzmann method, rectangular fiber, fitting expression, Levenberg-Marquardt algorithm

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