Effects of drag model and turbulence model on simulation of air-lift internal-loop reactor

ZHANG Jiabao; CUI Lijie; YANG Ning

doi:10.11949/j.issn.0438-1157.20170830

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Effects of drag model and turbulence model on simulation of air-lift internal-loop reactor

更新时间：2025-12-10

- Effects of drag model and turbulence model on simulation of air-lift internal-loop reactor
- CIESC Journal Issue 1, Pages: 389-395(2018)
- 作者机构：
  
  1. 中国科学院大学化学科学学院,北京,100049
  2. 中国科学院过程工程研究所多相复杂系统国家重点实验室,北京,100190
- 作者简介：
- 基金信息：
- DOI：10.11949/j.issn.0438-1157.20170830
  CLC： Q021.1
- Online First：05 January 2018，
  
  Published：05 January 2018
- 稿件说明：
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ZHANG Jiabao, CUI Lijie, YANG Ning. Effects of drag model and turbulence model on simulation of air-lift internal-loop reactor[J]. CIESC Journal, 2018, (1): 389-395.
DOI：

ZHANG Jiabao, CUI Lijie, YANG Ning. Effects of drag model and turbulence model on simulation of air-lift internal-loop reactor[J]. CIESC Journal, 2018, (1): 389-395. DOI： 10.11949/j.issn.0438-1157.20170830.

摘要

研究了曳力模型和湍流模型对气升式内环流反应器流体力学参数的影响，进一步证实了DBS-Local曳力模型在气升式内环流反应器中的适用性。结果表明：曳力模型决定了是否可以模拟出下降管中的气体；而曳力模型和湍流模型共同作用，决定了气含率模拟结果的准确性。Schiller-Naumann、Tomiyama、Grace、Ishii-Zuber这4种曳力模型均无法预测出下降管含气这一现象，而DBS-Local曳力模型能够模拟出下降管中的气体。DBS-Local曳力模型与standard k-ε mixture湍流模型组合，对气含率的预测值与实验值较为接近，而与RNG k-ε dispersed湍流模型组合，对轴向液速的预测值与实验值更为接近。

Abstract

The influence of drag models and turbulence models on the hydrodynamic parameters in an air-lift internal-loop reactor is evaluated. Drag models determine the existence of gas in downcomer

and drag models and turbulence models jointly determine the accuracy of the simulation of gas holdup. Using uniform size bubbles

the Schiller-Naumann

Tomiyama

Grace and Ishii-Zuber drag models are only suitable for lower superficial gas velocity

and there is no gas in downcomer. The capability of DBS-Local drag model was confirmed. Compared with the other four drag models

only DBS-Local drag model can predict the existence of gas in downcomer. DBS-Local drag model combining with the standard k-ε mixture turbulence model can well predict gas holdup

and combining with RNG k-ε dispersed turbulence model can better predict liquid velocity.

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