Fluid flow and heat transfer study for flower baffle heat exchanger

王英双

doi:10.3969/j.issn.0438-1157.2012.z1.019

您当前的位置：

首页 >

文章列表页 >

Fluid flow and heat transfer study for flower baffle heat exchanger

更新时间：2025-12-10

- Fluid flow and heat transfer study for flower baffle heat exchanger
- CIESC Journal Issue S1, Pages: 99-106(2012)
- 作者机构：
  
  华中科技大学能源与动力工程学院,湖北,武汉,430074
- 作者简介：
- 基金信息：
- DOI：10.3969/j.issn.0438-1157.2012.z1.019
  CLC： Q021
- Online First：28 May 2012，
  
  Published：28 May 2012
- 稿件说明：
移动端阅览
王英双. Fluid flow and heat transfer study for flower baffle heat exchanger[J]. CIESC Journal, 2012, (S1): 99-106.
DOI：

王英双. Fluid flow and heat transfer study for flower baffle heat exchanger[J]. CIESC Journal, 2012, (S1): 99-106. DOI： 10.3969/j.issn.0438-1157.2012.z1.019.

摘要

花格板换热器作为一种新型的管壳式换热器，其流动和传热机理研究目前尚未有较深入的研究。通过CFD技术，对花格板换热器的流动和传热性能进行了研究，并将结果与传统的弓形折流板换热器进行了比较，结果表明，在相同的Reynolds数下，花格板换热器的压降仅为折流板换热器的0.45倍左右，而两者的传热系数相差不大，因而花格板换热器的综合性能参数约为折流板换热器的2.2倍左右。

Abstract

As a novel type of shell-and-tube heat exchanger，the fluid flow and heat transfer mechanism in flower baffle heat exchanger(FBHX) has not been studied deeply.In the present paper，the CFD simulation method is adopted to investigate the mechanism of fluid flow and heat transfer of FBHX.With the comparison of calculated results between heat exchangers with flower baffle and traditional segmental baffle respectively，it shows that the pressure drop of the former is only 45% of that of the latter，while the difference of heat transfer coefficient between the two exchangers are minor，therefore，the comprehensive performance of the former is 2.2 times of that of the latter.

关键词

Keywords

references

Views

1132

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Engineering verification and NO emission control of rare earth Y2O3-based catalytic coatings on a metal fiber surface burner

Study on microwave enhanced removal performance of organic matter in coking waste salt

Oxygen mass transfer performance of hollow fiber non-bubble aeration membrane based on gas/liquid-phase measurement method

Corrosion health status assessment method for refining unit pipeline based on GLAE-MLP

Recent advances in machine learning for modeling and control of crystallization processes

Related Author

No data

Related Institution

No data

⁰