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.
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.
[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.
2016, Vol. 56 
