The heat transfer optimization of conical fin by shape modification

Jiansheng Wang; Xiao Wang

doi:10.1016/j.cjche.2016.05.010

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The heat transfer optimization of conical fin by shape modification

Fluid Dynamics and Transport Phenomena | Updated：2026-01-06

- The heat transfer optimization of conical fin by shape modification
- The heat transfer optimization of conical fin by shape modification
- 中国化学工程学报（英文版） 2016年24卷第8期页码：972-978
- Affiliations：
  
  Key Laboratory of Efficient Utilization of Low and Medium Grade Energy, MOE, School of Mechanical Engineering, Tianjin University,Tianjin,China,300072
- Author bio：
- Funds：
- DOI：10.1016/j.cjche.2016.05.010
  中图分类号：
- 纸质出版：2016
- Accepted：
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Jiansheng Wang, Xiao Wang. The heat transfer optimization of conical fin by shape modification[J]. 中国化学工程学报（英文版）, 2016,24(8):972-978.

Jiansheng Wang, Xiao Wang. The heat transfer optimization of conical fin by shape modification[J]. , 2016, 24(8): 972-978.
Jiansheng Wang, Xiao Wang. The heat transfer optimization of conical fin by shape modification[J]. 中国化学工程学报（英文版）, 2016,24(8):972-978. DOI： 10.1016/j.cjche.2016.05.010.

Jiansheng Wang, Xiao Wang. The heat transfer optimization of conical fin by shape modification[J]. , 2016, 24(8): 972-978. DOI： 10.1016/j.cjche.2016.05.010.

摘要

Abstract

In present work

a stepping optimization algorithm is proposed for the geometric optimization of conical fin

and the heat transfer rate of the fin is treated as the objective function in the optimization algorithm. The conical fin is divided into finite elements which have different generatrix slopes

and the geometry of the conical fin is finally determined by ensuring that every divided element can maintain the maximum heat transfer rate. Based on the actual condition of every element of the fin

the heat conduction equation is solved step by step. The present result shows that the optimized conical fin has more heat transfer quantity and higher fin efficiency compared with those of some typical fins. Furthermore

the theoretical feasibility and the error analysis of present optimization algorithm have been performed as well.

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