Please wait a minute...
 首页  期刊介绍 期刊订阅 联系我们 横山亮次奖 百年刊庆
 
最新录用  |  预出版  |  当期目录  |  过刊浏览  |  阅读排行  |  下载排行  |  引用排行  |  横山亮次奖  |  百年刊庆
清华大学学报(自然科学版)  2016, Vol. 56 Issue (7): 728-734    DOI: 10.16511/j.cnki.qhdxxb.2016.24.021
  化学与化学工程 本期目录 | 过刊浏览 | 高级检索 |
遗传-模拟退火算法优化设计管壳式换热器
肖武, 王开锋, 姜晓滨, 贺高红
大连理工大学 精细化工国家重点实验室, 大连 116024
Optimization of a shell-and-tube heat exchanger based on a genetic simulated annealing algorithm
XIAO Wu, WANG Kaifeng, JIANG Xiaobin, HE Gaohong
State Key Laboratory of Fine Chemicals, Dalian University of Technology, Dalian 116024, China
全文: PDF(1045 KB)  
输出: BibTeX | EndNote (RIS)      
摘要 依据Bell-Delaware法对壳程流体进行压降和传热的计算,选择管径、管长、折流挡板数等结构参数作为主要设计变量,参考了美国管式换热器制造商协会(Tubular Exchanger Manufacturers Association, TEMA)标准作为相关约束条件,以换热器的年度总费用最低为目标函数,建立了管壳式换热器优化设计数学模型,并基于遗传-模拟退火算法(GA-SA)进行求解。文献算例的对比结果表明:算法能较好地权衡换热器的换热面积费用和泵的操作费用并搜索到全局最优解,从而获得总费用较低的换热器主要结构参数。针对一个实际工程项目,考虑换热器设计裕度要求,计算结果与商业化软件HTRI的预测值接近,说明所设计的换热器实际可行。同时克服了HTRI需要设计者的经验确定设计变量和无法保证经济性最优的不足。
服务
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章
肖武
王开锋
姜晓滨
贺高红
关键词 管壳式换热器遗传-模拟退火算法(GA-SA)Bell-Delaware法优化设计    
Abstract:A mathematical model was developed to optimize the design of a shell-and-tube heat exchanger based on design data obtained by using the Bell-Delaware method to describe the pressure drop and heat transfer on the shell-side. The design variables were the tube diameter, the tube length, and other geometric parameters with the Tubular Exchanger Manufacturers Association (TEMA) standard taken as the reference for the constraints and the minimum total heat exchanger cost as the objective. The solution used the genetic simulated annealing algorithm (GA-SA). This method more effectively balances the heat exchanger area cost and pumping cost than previous methods by searching for the global optimal solution for the main geometric heat exchanger parameters with the minimum total cost. With the margin requirement for heat exchanger designs for specific industrial projects, these results are close to those given by commercial HTRI software, which indicates that this heat exchanger design method is reliable. This method guarantees the economic optimum without an empirical method to optimize the design variables in the heat exchanger design which is a major weakness of HTRI software packages.
Key wordsshell-and-tube heat exchanger    genetic simulated annealing algorithm (GA-SA)    Bell-Delaware method    design and optimization
收稿日期: 2015-08-30      出版日期: 2016-07-15
ZTFLH:  TK172  
基金资助:国家自然科学基金资助项目(21206014,21125628);中央高校基本科研业务费专项基金资助项目(DUT14LAB14);中国石油化工股份有限公司资助项目(X514001)
引用本文:   
肖武, 王开锋, 姜晓滨, 贺高红. 遗传-模拟退火算法优化设计管壳式换热器[J]. 清华大学学报(自然科学版), 2016, 56(7): 728-734.
XIAO Wu, WANG Kaifeng, JIANG Xiaobin, HE Gaohong. Optimization of a shell-and-tube heat exchanger based on a genetic simulated annealing algorithm. Journal of Tsinghua University(Science and Technology), 2016, 56(7): 728-734.
链接本文:  
http://jst.tsinghuajournals.com/CN/10.16511/j.cnki.qhdxxb.2016.24.021  或          http://jst.tsinghuajournals.com/CN/Y2016/V56/I7/728
  图1 换热器设计内循环流程图
  表1 管壳式换热器所采用的管子内径和外径
  图2 基于遗传模拟退火算法优化设计管壳式换热器流程图
  表2 算例1中冷热流股数据
  表3 算例1中换热器设计参数与文献的对比
  表4 算例1中设计结果与文献的对比
  表5 算例2中冷热流股数据
  表6 算例2中算法优化后的换热器设计参数
  表7 算例2中GAGSA 算法对传热和压降的计算结果和HTRI预测结果的对比
[1] Yang J, Oh S R, Liu W. Optimization of shell-and-tube heat exchangers using a general design approach motivated by constructal theory[J].International Journal of Heat and Mass Transfer,2014,77(4):1144-1154.
[2] Bahadori A. Simple method for estimation of effectiveness in one tube pass and one shell pass counter-flow heat exchangers[J].Applied Energy, 2011,88(11):4191-4196.
[3] Fesanghary M, Damangir E, Soleimani I. Design optimization of shell and tube heat exchangers using global sensitivity analysis and harmony search algorithm[J].Applied Thermal Engineering, 2009,29(5):1026-1031.
[4] Caputo A C, Pelagagge P M, Salini P. Heat exchanger design based on economic optimisation[J].Applied Thermal Engineering,2008,28(10):1151-1159.
[5] Fettaka S, Thibault J, Gupta Y. Design of shell-and-tube heat exchangers using multiobjective optimization[J]. International Journal of Heat and Mass Transfer,2013,60(1):343-354.
[6] Babu B V, Munawar S A. Differential evolution strategies for optimal design of shell-and-tube heat exchangers[J].Chemical Engineering Science, 2007,62(14):3720-3739.
[7] Serna-González M, Ponce-Ortega J M, Castro-Montoya A J, et al. Feasible design space for shell-and-tube heat exchangers using the Bell-Delaware method[J].Industrial & Engineering Chemistry Research, 2007,46(1):143-155.
[8] Mizutani F T, Pessoa F L P, Queiroz E M, et al. Mathematical programming model for heat-exchanger network synthesis including detailed heat-exchanger designs. 1. Shell-and-tube heat-exchanger design[J].Industrial & Engineering Chemistry Research,2003,42(17):4009-4018.
[9] Onishi V C, Ravagnani M A S S, Caballero J A. Mathematical programming model for heat exchanger design through optimization of partial objectives[J].Energy Conversion and Management, 2013,74:60-69.
[10] Khosravi R, Khosravi A, Nahavandi S. Assessing performance of genetic and firefly algorithms for optimal design of heat exchangers[C]//2014 IEEE International Conference on Systems, Man and Cybernetics (SMC). San Diego, USA:IEEE, 2014:3296-3301.
[11] Hadidi A, Nazari A. Design and economic optimization of shell-and-tube heat exchangers using biogeography-based (BBO) algorithm[J].Applied Thermal Engineering, 2013,51(1):1263-1272.
[12] ?ahin A ?ç, Kiliç B, Kiliç U. Design and economic optimization of shell and tube heat exchangers using Artificial Bee Colony (ABC) algorithm[J].Energy Conversion and Management, 2011,52(11):3356-3362.
[13] Selba? R, Kizilkan Ö, Reppich M. A new design approach for shell-and-tube heat exchangers using genetic algorithms from economic point of view[J].Chemical Engineering and Processing:Process Intensification, 2006,45(4):268-275.
[14] Ponce-Ortega J M, Serna-González M, Jiménez-Gutiérrez A. Use of genetic algorithms for the optimal design of shell-and-tube heat exchangers[J].Applied Thermal Engineering,2009,29(2):203-209.
[15] Ravagnani M A S S, Silva A P, Biscaia Jr E C, et al. Optimal design of shell-and-tube heat exchangers using particle swarm optimization[J].Industrial & Engineering Chemistry Research, 2009,48(6):2927-2935.
[16] Patel V K, Rao R V. Design optimization of shell-and-tube heat exchanger using particle swarm optimization technique[J].Applied Thermal Engineering, 2010,30(11):1417-1425.
[17] Khalfe N M, Lahiri K S, Wadhwa K S. Simulated annealing technique to design minimum cost exchanger[J].Chemical Industry and Chemical Engineering Quarterly,2011,17(4):409-427.
[18] Lahiri S K, Khalfe N. Improve shell and tube heat exchangers design by hybrid differential evolution and ant colony optimization technique[J].Asia-Pacific Journal of Chemical Engineering, 2014,9(3):431-448.
[19] Hadidi A, Hadidi M, Nazari A. A new design approach for shell-and-tube heat exchangers using imperialist competitive algorithm (ICA) from economic point of view[J].Energy conversion and Management,2013,67:66-74.
[20] Sinnott R K. Chemical Engineering Design:SI Edition[M]. London, UK:Elsevier, 2009.
[21] Ravagnani M, Caballero J A. A MINLP model for the rigorous design of shell and tube heat exchangers using the TEMA standards[J].Chemical Engineering Research and Design, 2007,85(10):1423-1435.
[22] Shah R K, Sekulic D P. Fundamentals of Heat Exchanger Design[M]. New York, USA:John Wiley & Sons, 2003.
[23] TEMA-2007. Standards of the Tubular Exchanger Manufacturers Association. Tubular Exchanger Manufacturers Association[S]. New York, USA:Tubular Exchanger Manufacturers Association, 2007.
[24] WEI Guanfeng, YAO Pingjing, LUO Xing, et al. Study on multi-stream heat exchanger network synthesis with parallel genetic/simulated annealing algorithm[J].Chinese Journal of Chemical Engineering, 2004,12(1):66-77.
[1] 张明, 王恩志, 刘耀儒, 齐文彪, 王德辉. 利用多项式混沌展开的结构可靠性分析[J]. 清华大学学报(自然科学版), 2022, 62(8): 1314-1320.
[2] 王啸宸, 李雪松, 任晓栋, 吴宏, 顾春伟. 多级压气机通流与CFD一体化优化设计方法[J]. 清华大学学报(自然科学版), 2022, 62(4): 774-784.
[3] 杨继锋, 姚蕊, 陈捷. 索牵引弹体装填机器人的尺寸优化设计[J]. 清华大学学报(自然科学版), 2021, 61(3): 217-223.
[4] 赵越, 强茂山, 王淏. EPC项目业主与承包商设计决策博弈[J]. 清华大学学报(自然科学版), 2021, 61(10): 1195-1201.
[5] 李东杰, 周伯豪, 梁骞, 兰旭东. 微型涡喷发动机燃烧室优化设计[J]. 清华大学学报(自然科学版), 2021, 61(10): 1212-1220.
[6] 薛春辉, 董玉杰. 自然循环熔盐球床堆中间换热器的优化设计[J]. 清华大学学报(自然科学版), 2018, 58(5): 445-449.
[7] 张铁山, 蒋晓华. 基于RB-IGBT的矩阵变换器中杂散电感的影响与优化[J]. 清华大学学报(自然科学版), 2017, 57(11): 1212-1219.
[8] 孙靖譞, 吕振华. 车辆受垂向强冲击时座椅安全带的防护效果比较分析与锚点位置优化[J]. 清华大学学报(自然科学版), 2016, 56(12): 1302-1311.
[9] 李培元, 顾春伟, 宋寅. 某MW级燃机低压离心压气机优化设计[J]. 清华大学学报(自然科学版), 2015, 55(10): 1110-1116.
[10] 韩俊, 温风波, 赵广播. 小展弦比涡轮叶片的弯曲优化设计[J]. 清华大学学报(自然科学版), 2014, 54(1): 102-108.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
版权所有 © 《清华大学学报(自然科学版)》编辑部
本系统由北京玛格泰克科技发展有限公司设计开发 技术支持:support@magtech.com.cn